1414 lines
307 KiB
Plaintext
1414 lines
307 KiB
Plaintext
2024-11-13 11:33:55,185 (logging:124) INFO: the current machine is at 127.0.1.1
|
|
2024-11-13 11:33:55,185 (logging:126) INFO: the current dir is /home/czzhangheng/code/FederatedScope
|
|
2024-11-13 11:33:55,186 (logging:127) INFO: the output dir is exp/FedAvg_FedDGCN_on_trafficflow_lr0.01_lstep1/sub_exp_20241113113355
|
|
2024-11-13 11:34:13,264 (config:243) INFO: the used configs are:
|
|
aggregator:
|
|
BFT_args:
|
|
|
|
byzantine_node_num: 0
|
|
inside_weight: 1.0
|
|
num_agg_groups: 1
|
|
num_agg_topk: []
|
|
outside_weight: 0.0
|
|
robust_rule: fedavg
|
|
asyn:
|
|
use: False
|
|
attack:
|
|
alpha_TV: 0.001
|
|
alpha_prop_loss: 0
|
|
attack_method:
|
|
attacker_id: -1
|
|
classifier_PIA: randomforest
|
|
edge_num: 100
|
|
edge_path: edge_data/
|
|
freq: 10
|
|
info_diff_type: l2
|
|
inject_round: 0
|
|
insert_round: 100000
|
|
label_type: dirty
|
|
max_ite: 400
|
|
mean: [0.9637]
|
|
mia_is_simulate_in: False
|
|
mia_simulate_in_round: 20
|
|
pgd_eps: 2
|
|
pgd_lr: 0.1
|
|
pgd_poisoning: False
|
|
poison_ratio: 0.5
|
|
reconstruct_lr: 0.01
|
|
reconstruct_optim: Adam
|
|
scale_para: 1.0
|
|
scale_poisoning: False
|
|
self_epoch: 6
|
|
self_lr: 0.05
|
|
self_opt: False
|
|
setting: fix
|
|
std: [0.1592]
|
|
target_label_ind: -1
|
|
trigger_path: trigger/
|
|
trigger_type: edge
|
|
backend: torch
|
|
cfg_file:
|
|
check_completeness: False
|
|
criterion:
|
|
type: MAPE
|
|
data:
|
|
add_day_in_week: True
|
|
add_time_in_day: True
|
|
args: []
|
|
batch_size: 64
|
|
cSBM_phi: [0.5, 0.5, 0.5]
|
|
cache_dir:
|
|
column_wise: False
|
|
consistent_label_distribution: True
|
|
days_per_week: 7
|
|
default_graph: True
|
|
drop_last: False
|
|
file_path:
|
|
hetero_data_name: []
|
|
hetero_synth_batch_size: 32
|
|
hetero_synth_feat_dim: 128
|
|
hetero_synth_prim_weight: 0.5
|
|
horizon: 12
|
|
is_debug: False
|
|
lag: 12
|
|
loader:
|
|
max_query_len: 128
|
|
max_seq_len: 384
|
|
max_tgt_len: 128
|
|
normalizer: std
|
|
num_contrast: 0
|
|
num_nodes: 170
|
|
num_of_client_for_data: []
|
|
num_steps: 30
|
|
num_workers: 0
|
|
pre_transform: []
|
|
quadratic:
|
|
dim: 1
|
|
max_curv: 12.5
|
|
min_curv: 0.02
|
|
root: data/trafficflow/PeMS08
|
|
save_data: False
|
|
scaler: [229.843136, 145.625531]
|
|
server_holds_all: False
|
|
shuffle: True
|
|
sizes: [10, 5]
|
|
splits: [0.8, 0.1, 0.1]
|
|
splitter: trafficflowprediction
|
|
splitter_args: []
|
|
steps_per_day: 288
|
|
subsample: 1.0
|
|
target_transform: []
|
|
test_pre_transform: []
|
|
test_ratio: 0.2
|
|
test_target_transform: []
|
|
test_transform: []
|
|
tod: False
|
|
transform: []
|
|
trunc_stride: 128
|
|
type: trafficflow
|
|
val_pre_transform: []
|
|
val_ratio: 0.2
|
|
val_target_transform: []
|
|
val_transform: []
|
|
walk_length: 2
|
|
dataloader:
|
|
batch_size: 64
|
|
drop_last: True
|
|
num_steps: 30
|
|
num_workers: 0
|
|
pin_memory: False
|
|
shuffle: True
|
|
sizes: [10, 5]
|
|
theta: -1
|
|
type: trafficflow
|
|
walk_length: 2
|
|
device: 0
|
|
distribute:
|
|
use: False
|
|
early_stop:
|
|
delta: 0.0
|
|
improve_indicator_mode: best
|
|
patience: 15
|
|
eval:
|
|
best_res_update_round_wise_key: val_loss
|
|
count_flops: True
|
|
freq: 1
|
|
metrics: ['avg_loss']
|
|
monitoring: []
|
|
report: ['weighted_avg', 'avg', 'fairness', 'raw']
|
|
split: ['test', 'val']
|
|
expname: FedAvg_FedDGCN_on_trafficflow_lr0.01_lstep1
|
|
expname_tag:
|
|
feat_engr:
|
|
num_bins: 5
|
|
scenario: hfl
|
|
secure:
|
|
dp:
|
|
|
|
encrypt:
|
|
type: dummy
|
|
key_size: 3072
|
|
type: encrypt
|
|
selec_threshold: 0.05
|
|
selec_woe_binning: quantile
|
|
type:
|
|
federate:
|
|
atc_load_from:
|
|
atc_vanilla: False
|
|
client_num: 10
|
|
data_weighted_aggr: False
|
|
ignore_weight: False
|
|
join_in_info: []
|
|
make_global_eval: False
|
|
master_addr: 127.0.0.1
|
|
master_port: 29500
|
|
merge_test_data: False
|
|
merge_val_data: False
|
|
method: FedAvg
|
|
mode: standalone
|
|
online_aggr: False
|
|
process_num: 1
|
|
resource_info_file:
|
|
restore_from:
|
|
sample_client_num: 10
|
|
sample_client_rate: -1.0
|
|
sampler: uniform
|
|
save_to:
|
|
share_local_model: False
|
|
total_round_num: 70
|
|
unseen_clients_rate: 0.0
|
|
use_diff: False
|
|
use_ss: False
|
|
fedopt:
|
|
use: False
|
|
fedprox:
|
|
use: False
|
|
fedsageplus:
|
|
a: 1.0
|
|
b: 1.0
|
|
c: 1.0
|
|
fedgen_epoch: 200
|
|
gen_hidden: 128
|
|
hide_portion: 0.5
|
|
loc_epoch: 1
|
|
num_pred: 5
|
|
fedswa:
|
|
use: False
|
|
finetune:
|
|
batch_or_epoch: epoch
|
|
before_eval: False
|
|
epoch_linear: 10
|
|
freeze_param:
|
|
local_param: []
|
|
local_update_steps: 1
|
|
lr_linear: 0.005
|
|
optimizer:
|
|
lr: 0.1
|
|
type: SGD
|
|
scheduler:
|
|
type:
|
|
warmup_ratio: 0.0
|
|
simple_tuning: False
|
|
weight_decay: 0.0
|
|
flitplus:
|
|
factor_ema: 0.8
|
|
lambdavat: 0.5
|
|
tmpFed: 0.5
|
|
weightReg: 1.0
|
|
gcflplus:
|
|
EPS_1: 0.05
|
|
EPS_2: 0.1
|
|
seq_length: 5
|
|
standardize: False
|
|
grad:
|
|
grad_accum_count: 1
|
|
grad_clip: 5.0
|
|
hpo:
|
|
fedex:
|
|
cutoff: 0.0
|
|
diff: False
|
|
eta0: -1.0
|
|
flatten_ss: True
|
|
gamma: 0.0
|
|
pi_lr: 0.01
|
|
psn: False
|
|
sched: auto
|
|
ss:
|
|
use: False
|
|
fts:
|
|
M: 100
|
|
M_target: 200
|
|
allow_load_existing_info: True
|
|
diff: False
|
|
fed_bo_max_iter: 50
|
|
g_var: 1e-06
|
|
gp_opt_schedule: 1
|
|
local_bo_epochs: 50
|
|
local_bo_max_iter: 50
|
|
ls: 1.0
|
|
obs_noise: 1e-06
|
|
ss:
|
|
target_clients: []
|
|
use: False
|
|
v_kernel: 1.0
|
|
var: 0.1
|
|
init_cand_num: 16
|
|
larger_better: False
|
|
metric: client_summarized_weighted_avg.val_loss
|
|
num_workers: 0
|
|
pbt:
|
|
max_stage: 5
|
|
perf_threshold: 0.1
|
|
pfedhpo:
|
|
discrete: False
|
|
ss:
|
|
target_fl_total_round: 1000
|
|
train_anchor: False
|
|
train_fl: False
|
|
use: False
|
|
scheduler: rs
|
|
sha:
|
|
budgets: []
|
|
elim_rate: 3
|
|
iter: 0
|
|
ss:
|
|
table:
|
|
eps: 0.1
|
|
idx: 0
|
|
num: 27
|
|
trial_index: 0
|
|
working_folder: hpo
|
|
model:
|
|
cheb_order: 2
|
|
contrast_temp: 1.0
|
|
contrast_topk: 100
|
|
downstream_tasks: []
|
|
dropout: 0.1
|
|
embed_dim: 10
|
|
embed_size: 8
|
|
gamma: 0
|
|
graph_pooling: mean
|
|
hidden: 256
|
|
horizon: 12
|
|
in_channels: 0
|
|
input_dim: 1
|
|
input_shape: ()
|
|
label_smoothing: 0.1
|
|
lambda_: 0.1
|
|
layer: 2
|
|
length_penalty: 2.0
|
|
max_answer_len: 30
|
|
max_length: 200
|
|
max_tree_depth: 3
|
|
min_length: 1
|
|
model_num_per_trainer: 1
|
|
model_type: google/bert_uncased_L-2_H-128_A-2
|
|
n_best_size: 20
|
|
no_repeat_ngram_size: 3
|
|
null_score_diff_threshold: 0.0
|
|
num_beams: 5
|
|
num_item: 0
|
|
num_labels: 1
|
|
num_layers: 1
|
|
num_nodes: 17
|
|
num_of_trees: 10
|
|
num_user: 0
|
|
out_channels: 1
|
|
output_dim: 1
|
|
pretrain_tasks: []
|
|
rnn_units: 64
|
|
stage:
|
|
task: TrafficFlowPrediction
|
|
type: FedDGCN
|
|
use_bias: True
|
|
use_contrastive_loss: False
|
|
use_day: True
|
|
use_week: True
|
|
nbafl:
|
|
use: False
|
|
outdir: exp/FedAvg_FedDGCN_on_trafficflow_lr0.01_lstep1/sub_exp_20241113113355
|
|
personalization:
|
|
K: 5
|
|
beta: 1.0
|
|
epoch_feature: 1
|
|
epoch_linear: 2
|
|
local_param: []
|
|
local_update_steps: 1
|
|
lr: 0.01
|
|
lr_feature: 0.1
|
|
lr_linear: 0.1
|
|
regular_weight: 0.1
|
|
share_non_trainable_para: False
|
|
weight_decay: 0.0
|
|
print_decimal_digits: 6
|
|
quantization:
|
|
method: none
|
|
nbits: 8
|
|
regularizer:
|
|
mu: 0.0
|
|
type:
|
|
seed: 10
|
|
sgdmf:
|
|
use: False
|
|
train:
|
|
batch_or_epoch: epoch
|
|
batch_size: 64
|
|
data_para_dids: []
|
|
early_stop: False
|
|
early_stop_patience: 15
|
|
epochs: 300
|
|
grad_norm: True
|
|
local_update_steps: 1
|
|
loss_func: mae
|
|
lr_decay: False
|
|
lr_decay_rate: 0.3
|
|
lr_decay_step: [5, 20, 40, 70]
|
|
lr_init: 0.003
|
|
max_grad_norm: 5
|
|
optimizer:
|
|
lr: 0.01
|
|
type: Adam
|
|
weight_decay: 0.0
|
|
real_value: True
|
|
scheduler:
|
|
type:
|
|
warmup_ratio: 0.0
|
|
seed: 10
|
|
weight_decay: 0
|
|
trainer:
|
|
disp_freq: 50
|
|
local_entropy:
|
|
alpha: 0.75
|
|
eps: 0.0001
|
|
gamma: 0.03
|
|
inc_factor: 1.0
|
|
log_dir: ./
|
|
sam:
|
|
adaptive: False
|
|
eta: 0.0
|
|
rho: 1.0
|
|
type: trafficflowtrainer
|
|
val_freq: 100000000
|
|
use_gpu: True
|
|
verbose: 1
|
|
vertical:
|
|
use: False
|
|
wandb:
|
|
use: False
|
|
2024-11-13 11:34:13,474 (utils:147) INFO: The device information file is not provided
|
|
2024-11-13 11:34:13,540 (fed_runner:173) INFO: Server has been set up ...
|
|
2024-11-13 11:34:13,569 (fed_runner:225) INFO: Client 1 has been set up ...
|
|
2024-11-13 11:34:13,591 (fed_runner:225) INFO: Client 2 has been set up ...
|
|
2024-11-13 11:34:13,609 (fed_runner:225) INFO: Client 3 has been set up ...
|
|
2024-11-13 11:34:13,626 (fed_runner:225) INFO: Client 4 has been set up ...
|
|
2024-11-13 11:34:13,646 (fed_runner:225) INFO: Client 5 has been set up ...
|
|
2024-11-13 11:34:13,668 (fed_runner:225) INFO: Client 6 has been set up ...
|
|
2024-11-13 11:34:13,692 (fed_runner:225) INFO: Client 7 has been set up ...
|
|
2024-11-13 11:34:13,712 (fed_runner:225) INFO: Client 8 has been set up ...
|
|
2024-11-13 11:34:13,734 (fed_runner:225) INFO: Client 9 has been set up ...
|
|
2024-11-13 11:34:13,756 (fed_runner:225) INFO: Client 10 has been set up ...
|
|
2024-11-13 11:34:13,757 (trainer:345) INFO: Model meta-info: <class 'federatedscope.trafficflow.model.FedDGCN.FedDGCN'>.
|
|
2024-11-13 11:34:13,758 (trainer:353) INFO: Num of original para names: 50.
|
|
2024-11-13 11:34:13,758 (trainer:354) INFO: Num of original trainable para names: 50.
|
|
2024-11-13 11:34:13,758 (trainer:356) INFO: Num of preserved para names in local update: 50.
|
|
Preserved para names in local update: {'encoder2.DGCRM_cells.0.gate.fc.fc3.bias', 'encoder1.DGCRM_cells.0.gate.fc.fc2.bias', 'encoder2.DGCRM_cells.0.gate.fc.fc2.weight', 'encoder1.DGCRM_cells.0.gate.weights', 'encoder2.DGCRM_cells.0.update.weights', 'encoder1.DGCRM_cells.0.gate.fc.fc1.weight', 'encoder2.DGCRM_cells.0.gate.weights_pool', 'encoder1.DGCRM_cells.0.update.weights_pool', 'encoder1.DGCRM_cells.0.update.fc.fc3.weight', 'encoder2.DGCRM_cells.0.update.fc.fc1.bias', 'encoder1.DGCRM_cells.0.gate.weights_pool', 'encoder1.DGCRM_cells.0.update.fc.fc1.bias', 'encoder2.DGCRM_cells.0.update.weights_pool', 'encoder2.DGCRM_cells.0.update.bias_pool', 'encoder2.DGCRM_cells.0.update.fc.fc2.bias', 'node_embeddings2', 'D_i_W_emb', 'end_conv3.bias', 'encoder2.DGCRM_cells.0.gate.bias', 'encoder1.DGCRM_cells.0.update.fc.fc2.bias', 'encoder1.DGCRM_cells.0.update.fc.fc3.bias', 'encoder2.DGCRM_cells.0.update.fc.fc2.weight', 'encoder2.DGCRM_cells.0.gate.fc.fc1.weight', 'encoder2.DGCRM_cells.0.update.bias', 'node_embeddings1', 'encoder1.DGCRM_cells.0.gate.fc.fc3.bias', 'encoder2.DGCRM_cells.0.update.fc.fc3.bias', 'encoder2.DGCRM_cells.0.gate.fc.fc3.weight', 'encoder1.DGCRM_cells.0.update.bias_pool', 'encoder1.DGCRM_cells.0.gate.bias_pool', 'end_conv2.weight', 'encoder1.DGCRM_cells.0.gate.fc.fc1.bias', 'encoder1.DGCRM_cells.0.gate.fc.fc2.weight', 'encoder1.DGCRM_cells.0.gate.bias', 'encoder1.DGCRM_cells.0.update.weights', 'encoder2.DGCRM_cells.0.update.fc.fc1.weight', 'encoder2.DGCRM_cells.0.gate.bias_pool', 'end_conv2.bias', 'end_conv3.weight', 'encoder1.DGCRM_cells.0.gate.fc.fc3.weight', 'T_i_D_emb', 'end_conv1.bias', 'encoder2.DGCRM_cells.0.gate.weights', 'encoder2.DGCRM_cells.0.gate.fc.fc2.bias', 'end_conv1.weight', 'encoder2.DGCRM_cells.0.gate.fc.fc1.bias', 'encoder1.DGCRM_cells.0.update.fc.fc2.weight', 'encoder1.DGCRM_cells.0.update.fc.fc1.weight', 'encoder2.DGCRM_cells.0.update.fc.fc3.weight', 'encoder1.DGCRM_cells.0.update.bias'}.
|
|
2024-11-13 11:34:13,758 (trainer:360) INFO: Num of filtered para names in local update: 0.
|
|
Filtered para names in local update: set().
|
|
2024-11-13 11:34:13,759 (trainer:365) INFO: After register default hooks,
|
|
the hooks_in_train is:
|
|
{
|
|
"on_fit_start": [
|
|
"_hook_on_data_parallel_init",
|
|
"_hook_on_fit_start_init",
|
|
"_hook_on_fit_start_calculate_model_size"
|
|
],
|
|
"on_epoch_start": [
|
|
"_hook_on_epoch_start"
|
|
],
|
|
"on_batch_start": [
|
|
"_hook_on_batch_start_init"
|
|
],
|
|
"on_batch_forward": [
|
|
"_hook_on_batch_forward",
|
|
"_hook_on_batch_forward_regularizer",
|
|
"_hook_on_batch_forward_flop_count"
|
|
],
|
|
"on_batch_backward": [
|
|
"_hook_on_batch_backward"
|
|
],
|
|
"on_batch_end": [
|
|
"_hook_on_batch_end"
|
|
],
|
|
"on_fit_end": [
|
|
"_hook_on_fit_end"
|
|
]
|
|
};
|
|
the hooks_in_eval is:
|
|
t{
|
|
"on_fit_start": [
|
|
"_hook_on_data_parallel_init",
|
|
"_hook_on_fit_start_init"
|
|
],
|
|
"on_epoch_start": [
|
|
"_hook_on_epoch_start"
|
|
],
|
|
"on_batch_start": [
|
|
"_hook_on_batch_start_init"
|
|
],
|
|
"on_batch_forward": [
|
|
"_hook_on_batch_forward"
|
|
],
|
|
"on_batch_end": [
|
|
"_hook_on_batch_end"
|
|
],
|
|
"on_fit_end": [
|
|
"_hook_on_fit_end"
|
|
]
|
|
}
|
|
2024-11-13 11:34:13,780 (server:843) INFO: ----------- Starting training (Round #0) -------------
|
|
2024-11-13 11:34:53,557 (client:354) INFO: {'Role': 'Client #9', 'Round': 0, 'Results_raw': {'train_loss': 45.335725, 'val_loss': 23.365322, 'test_loss': 20.292845}}
|
|
2024-11-13 11:35:29,344 (client:354) INFO: {'Role': 'Client #3', 'Round': 0, 'Results_raw': {'train_loss': 16.022708, 'val_loss': 9.969433, 'test_loss': 10.354877}}
|
|
2024-11-13 11:36:04,575 (client:354) INFO: {'Role': 'Client #6', 'Round': 0, 'Results_raw': {'train_loss': 21.522213, 'val_loss': 12.07181, 'test_loss': 11.694696}}
|
|
2024-11-13 11:36:41,247 (client:354) INFO: {'Role': 'Client #7', 'Round': 0, 'Results_raw': {'train_loss': 31.370819, 'val_loss': 15.493028, 'test_loss': 14.451414}}
|
|
2024-11-13 11:37:15,131 (client:354) INFO: {'Role': 'Client #4', 'Round': 0, 'Results_raw': {'train_loss': 14.528873, 'val_loss': 7.888442, 'test_loss': 7.832286}}
|
|
2024-11-13 11:37:51,964 (client:354) INFO: {'Role': 'Client #2', 'Round': 0, 'Results_raw': {'train_loss': 29.138543, 'val_loss': 13.656109, 'test_loss': 12.907554}}
|
|
2024-11-13 11:38:25,408 (client:354) INFO: {'Role': 'Client #1', 'Round': 0, 'Results_raw': {'train_loss': 15.513411, 'val_loss': 9.512045, 'test_loss': 9.773874}}
|
|
2024-11-13 11:39:01,642 (client:354) INFO: {'Role': 'Client #8', 'Round': 0, 'Results_raw': {'train_loss': 14.660121, 'val_loss': 14.802662, 'test_loss': 9.299267}}
|
|
2024-11-13 11:39:39,334 (client:354) INFO: {'Role': 'Client #5', 'Round': 0, 'Results_raw': {'train_loss': 12.763765, 'val_loss': 7.854776, 'test_loss': 7.427119}}
|
|
2024-11-13 11:40:17,050 (client:354) INFO: {'Role': 'Client #10', 'Round': 0, 'Results_raw': {'train_loss': 53.134039, 'val_loss': 23.074534, 'test_loss': 21.774615}}
|
|
2024-11-13 11:40:17,091 (server:353) INFO: Server: Starting evaluation at the end of round 0.
|
|
2024-11-13 11:40:17,091 (server:359) INFO: ----------- Starting a new training round (Round #1) -------------
|
|
2024-11-13 11:41:52,534 (client:354) INFO: {'Role': 'Client #6', 'Round': 1, 'Results_raw': {'train_loss': 13.787932, 'val_loss': 11.552593, 'test_loss': 11.205648}}
|
|
2024-11-13 11:42:32,240 (client:354) INFO: {'Role': 'Client #4', 'Round': 1, 'Results_raw': {'train_loss': 10.406317, 'val_loss': 8.433093, 'test_loss': 8.36533}}
|
|
2024-11-13 11:43:07,924 (client:354) INFO: {'Role': 'Client #5', 'Round': 1, 'Results_raw': {'train_loss': 9.195242, 'val_loss': 7.486047, 'test_loss': 7.301868}}
|
|
2024-11-13 11:43:43,204 (client:354) INFO: {'Role': 'Client #8', 'Round': 1, 'Results_raw': {'train_loss': 10.922584, 'val_loss': 16.009171, 'test_loss': 9.160499}}
|
|
2024-11-13 11:44:17,803 (client:354) INFO: {'Role': 'Client #7', 'Round': 1, 'Results_raw': {'train_loss': 20.596406, 'val_loss': 16.260316, 'test_loss': 15.252113}}
|
|
2024-11-13 11:44:52,648 (client:354) INFO: {'Role': 'Client #9', 'Round': 1, 'Results_raw': {'train_loss': 22.423121, 'val_loss': 22.071845, 'test_loss': 18.220542}}
|
|
2024-11-13 11:45:33,597 (client:354) INFO: {'Role': 'Client #10', 'Round': 1, 'Results_raw': {'train_loss': 27.128937, 'val_loss': 19.379354, 'test_loss': 18.247889}}
|
|
2024-11-13 11:46:10,733 (client:354) INFO: {'Role': 'Client #3', 'Round': 1, 'Results_raw': {'train_loss': 12.097025, 'val_loss': 10.272578, 'test_loss': 10.69386}}
|
|
2024-11-13 11:46:46,538 (client:354) INFO: {'Role': 'Client #2', 'Round': 1, 'Results_raw': {'train_loss': 17.934688, 'val_loss': 13.727891, 'test_loss': 12.949097}}
|
|
2024-11-13 11:47:23,242 (client:354) INFO: {'Role': 'Client #1', 'Round': 1, 'Results_raw': {'train_loss': 11.505897, 'val_loss': 9.639636, 'test_loss': 9.956574}}
|
|
2024-11-13 11:47:23,254 (server:615) INFO: {'Role': 'Server #', 'Round': 0, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(66.042807), 'test_loss': np.float64(232470.681757), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(69.313518), 'val_loss': np.float64(243983.583453)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(66.042807), 'test_loss': np.float64(232470.681757), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(69.313518), 'val_loss': np.float64(243983.583453)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(46.251132), 'test_avg_loss_bottom_decile': np.float64(26.195873), 'test_avg_loss_top_decile': np.float64(156.573859), 'test_avg_loss_min': np.float64(25.715192), 'test_avg_loss_max': np.float64(156.573859), 'test_avg_loss_bottom10%': np.float64(25.715192), 'test_avg_loss_top10%': np.float64(156.573859), 'test_avg_loss_cos1': np.float64(0.819109), 'test_avg_loss_entropy': np.float64(2.07647), 'test_loss_std': np.float64(162803.984082), 'test_loss_bottom_decile': np.float64(92209.471863), 'test_loss_top_decile': np.float64(551139.982422), 'test_loss_min': np.float64(90517.476074), 'test_loss_max': np.float64(551139.982422), 'test_loss_bottom10%': np.float64(90517.476074), 'test_loss_top10%': np.float64(551139.982422), 'test_loss_cos1': np.float64(0.819109), 'test_loss_entropy': np.float64(2.07647), 'val_avg_loss_std': np.float64(49.111579), 'val_avg_loss_bottom_decile': np.float64(26.396308), 'val_avg_loss_top_decile': np.float64(161.359076), 'val_avg_loss_min': np.float64(25.376707), 'val_avg_loss_max': np.float64(161.359076), 'val_avg_loss_bottom10%': np.float64(25.376707), 'val_avg_loss_top10%': np.float64(161.359076), 'val_avg_loss_cos1': np.float64(0.815944), 'val_avg_loss_entropy': np.float64(2.07183), 'val_loss_std': np.float64(172872.756838), 'val_loss_bottom_decile': np.float64(92915.005676), 'val_loss_top_decile': np.float64(567983.946045), 'val_loss_min': np.float64(89326.009033), 'val_loss_max': np.float64(567983.946045), 'val_loss_bottom10%': np.float64(89326.009033), 'val_loss_top10%': np.float64(567983.946045), 'val_loss_cos1': np.float64(0.815944), 'val_loss_entropy': np.float64(2.07183)}}
|
|
2024-11-13 11:47:23,295 (server:353) INFO: Server: Starting evaluation at the end of round 1.
|
|
2024-11-13 11:47:23,295 (server:359) INFO: ----------- Starting a new training round (Round #2) -------------
|
|
2024-11-13 11:48:56,245 (client:354) INFO: {'Role': 'Client #2', 'Round': 2, 'Results_raw': {'train_loss': 15.998278, 'val_loss': 13.176533, 'test_loss': 12.106976}}
|
|
2024-11-13 11:49:38,009 (client:354) INFO: {'Role': 'Client #7', 'Round': 2, 'Results_raw': {'train_loss': 15.267664, 'val_loss': 13.752513, 'test_loss': 12.880882}}
|
|
2024-11-13 11:50:17,552 (client:354) INFO: {'Role': 'Client #3', 'Round': 2, 'Results_raw': {'train_loss': 11.387607, 'val_loss': 9.850684, 'test_loss': 10.257393}}
|
|
2024-11-13 11:50:57,561 (client:354) INFO: {'Role': 'Client #6', 'Round': 2, 'Results_raw': {'train_loss': 14.605648, 'val_loss': 10.930031, 'test_loss': 10.643045}}
|
|
2024-11-13 11:51:37,582 (client:354) INFO: {'Role': 'Client #8', 'Round': 2, 'Results_raw': {'train_loss': 10.148942, 'val_loss': 17.910816, 'test_loss': 9.805055}}
|
|
2024-11-13 11:52:17,348 (client:354) INFO: {'Role': 'Client #9', 'Round': 2, 'Results_raw': {'train_loss': 21.689953, 'val_loss': 18.456924, 'test_loss': 15.398244}}
|
|
2024-11-13 11:52:58,387 (client:354) INFO: {'Role': 'Client #10', 'Round': 2, 'Results_raw': {'train_loss': 23.623237, 'val_loss': 17.81453, 'test_loss': 17.212272}}
|
|
2024-11-13 11:53:38,965 (client:354) INFO: {'Role': 'Client #1', 'Round': 2, 'Results_raw': {'train_loss': 10.964001, 'val_loss': 9.38537, 'test_loss': 9.601957}}
|
|
2024-11-13 11:54:20,740 (client:354) INFO: {'Role': 'Client #4', 'Round': 2, 'Results_raw': {'train_loss': 9.485399, 'val_loss': 7.648842, 'test_loss': 7.712469}}
|
|
2024-11-13 11:55:01,372 (client:354) INFO: {'Role': 'Client #5', 'Round': 2, 'Results_raw': {'train_loss': 8.425368, 'val_loss': 7.295429, 'test_loss': 6.958464}}
|
|
2024-11-13 11:55:01,377 (server:615) INFO: {'Role': 'Server #', 'Round': 1, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(21.47121), 'test_loss': np.float64(75578.659326), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(22.822089), 'val_loss': np.float64(80333.753839)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(21.47121), 'test_loss': np.float64(75578.659326), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(22.822089), 'val_loss': np.float64(80333.753839)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(11.229912), 'test_avg_loss_bottom_decile': np.float64(11.290623), 'test_avg_loss_top_decile': np.float64(43.957139), 'test_avg_loss_min': np.float64(11.275739), 'test_avg_loss_max': np.float64(43.957139), 'test_avg_loss_bottom10%': np.float64(11.275739), 'test_avg_loss_top10%': np.float64(43.957139), 'test_avg_loss_cos1': np.float64(0.886118), 'test_avg_loss_entropy': np.float64(2.178098), 'test_loss_std': np.float64(39529.291731), 'test_loss_bottom_decile': np.float64(39742.992371), 'test_loss_top_decile': np.float64(154729.129883), 'test_loss_min': np.float64(39690.600677), 'test_loss_max': np.float64(154729.129883), 'test_loss_bottom10%': np.float64(39690.600677), 'test_loss_top10%': np.float64(154729.129883), 'test_loss_cos1': np.float64(0.886118), 'test_loss_entropy': np.float64(2.178098), 'val_avg_loss_std': np.float64(11.663798), 'val_avg_loss_bottom_decile': np.float64(11.977663), 'val_avg_loss_top_decile': np.float64(47.321731), 'val_avg_loss_min': np.float64(11.610422), 'val_avg_loss_max': np.float64(47.321731), 'val_avg_loss_bottom10%': np.float64(11.610422), 'val_avg_loss_top10%': np.float64(47.321731), 'val_avg_loss_cos1': np.float64(0.890448), 'val_avg_loss_entropy': np.float64(2.183131), 'val_loss_std': np.float64(41056.567754), 'val_loss_bottom_decile': np.float64(42161.374756), 'val_loss_top_decile': np.float64(166572.49231), 'val_loss_min': np.float64(40868.68512), 'val_loss_max': np.float64(166572.49231), 'val_loss_bottom10%': np.float64(40868.68512), 'val_loss_top10%': np.float64(166572.49231), 'val_loss_cos1': np.float64(0.890448), 'val_loss_entropy': np.float64(2.183131)}}
|
|
2024-11-13 11:55:01,421 (server:353) INFO: Server: Starting evaluation at the end of round 2.
|
|
2024-11-13 11:55:01,422 (server:359) INFO: ----------- Starting a new training round (Round #3) -------------
|
|
2024-11-13 11:56:40,968 (client:354) INFO: {'Role': 'Client #1', 'Round': 3, 'Results_raw': {'train_loss': 10.447135, 'val_loss': 9.518381, 'test_loss': 9.870626}}
|
|
2024-11-13 11:57:20,683 (client:354) INFO: {'Role': 'Client #8', 'Round': 3, 'Results_raw': {'train_loss': 9.379929, 'val_loss': 16.137447, 'test_loss': 9.055021}}
|
|
2024-11-13 11:58:00,097 (client:354) INFO: {'Role': 'Client #6', 'Round': 3, 'Results_raw': {'train_loss': 12.093281, 'val_loss': 10.399544, 'test_loss': 10.092796}}
|
|
2024-11-13 11:58:38,578 (client:354) INFO: {'Role': 'Client #3', 'Round': 3, 'Results_raw': {'train_loss': 10.673559, 'val_loss': 9.832192, 'test_loss': 10.190034}}
|
|
2024-11-13 11:59:24,800 (client:354) INFO: {'Role': 'Client #4', 'Round': 3, 'Results_raw': {'train_loss': 9.071435, 'val_loss': 7.655443, 'test_loss': 7.634042}}
|
|
2024-11-13 12:00:11,649 (client:354) INFO: {'Role': 'Client #10', 'Round': 3, 'Results_raw': {'train_loss': 22.060699, 'val_loss': 18.127292, 'test_loss': 17.134902}}
|
|
2024-11-13 12:01:02,981 (client:354) INFO: {'Role': 'Client #7', 'Round': 3, 'Results_raw': {'train_loss': 14.506285, 'val_loss': 12.050048, 'test_loss': 11.166877}}
|
|
2024-11-13 12:02:08,162 (client:354) INFO: {'Role': 'Client #5', 'Round': 3, 'Results_raw': {'train_loss': 8.088537, 'val_loss': 7.616791, 'test_loss': 7.325094}}
|
|
2024-11-13 12:03:11,499 (client:354) INFO: {'Role': 'Client #9', 'Round': 3, 'Results_raw': {'train_loss': 17.924012, 'val_loss': 17.637173, 'test_loss': 14.44952}}
|
|
2024-11-13 12:04:15,334 (client:354) INFO: {'Role': 'Client #2', 'Round': 3, 'Results_raw': {'train_loss': 16.720463, 'val_loss': 13.507298, 'test_loss': 12.801738}}
|
|
2024-11-13 12:04:15,388 (server:615) INFO: {'Role': 'Server #', 'Round': 2, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(18.759611), 'test_loss': np.float64(66033.830493), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(20.171405), 'val_loss': np.float64(71003.346829)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(18.759611), 'test_loss': np.float64(66033.830493), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(20.171405), 'val_loss': np.float64(71003.346829)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(9.710537), 'test_avg_loss_bottom_decile': np.float64(10.009128), 'test_avg_loss_top_decile': np.float64(37.81352), 'test_avg_loss_min': np.float64(9.963496), 'test_avg_loss_max': np.float64(37.81352), 'test_avg_loss_bottom10%': np.float64(9.963496), 'test_avg_loss_top10%': np.float64(37.81352), 'test_avg_loss_cos1': np.float64(0.888077), 'test_avg_loss_entropy': np.float64(2.181324), 'test_loss_std': np.float64(34181.088621), 'test_loss_bottom_decile': np.float64(35232.129181), 'test_loss_top_decile': np.float64(133103.588867), 'test_loss_min': np.float64(35071.504242), 'test_loss_max': np.float64(133103.588867), 'test_loss_bottom10%': np.float64(35071.504242), 'test_loss_top10%': np.float64(133103.588867), 'test_loss_cos1': np.float64(0.888077), 'test_loss_entropy': np.float64(2.181324), 'val_avg_loss_std': np.float64(10.303462), 'val_avg_loss_bottom_decile': np.float64(10.521167), 'val_avg_loss_top_decile': np.float64(41.497891), 'val_avg_loss_min': np.float64(10.266102), 'val_avg_loss_max': np.float64(41.497891), 'val_avg_loss_bottom10%': np.float64(10.266102), 'val_avg_loss_top10%': np.float64(41.497891), 'val_avg_loss_cos1': np.float64(0.890549), 'val_avg_loss_entropy': np.float64(2.183574), 'val_loss_std': np.float64(36268.185652), 'val_loss_bottom_decile': np.float64(37034.508392), 'val_loss_top_decile': np.float64(146072.574829), 'val_loss_min': np.float64(36136.678497), 'val_loss_max': np.float64(146072.574829), 'val_loss_bottom10%': np.float64(36136.678497), 'val_loss_top10%': np.float64(146072.574829), 'val_loss_cos1': np.float64(0.890549), 'val_loss_entropy': np.float64(2.183574)}}
|
|
2024-11-13 12:04:15,517 (server:353) INFO: Server: Starting evaluation at the end of round 3.
|
|
2024-11-13 12:04:15,519 (server:359) INFO: ----------- Starting a new training round (Round #4) -------------
|
|
2024-11-13 12:07:28,914 (client:354) INFO: {'Role': 'Client #3', 'Round': 4, 'Results_raw': {'train_loss': 10.437573, 'val_loss': 9.471943, 'test_loss': 9.88872}}
|
|
2024-11-13 12:08:31,255 (client:354) INFO: {'Role': 'Client #1', 'Round': 4, 'Results_raw': {'train_loss': 10.217944, 'val_loss': 9.221074, 'test_loss': 9.424388}}
|
|
2024-11-13 12:09:31,969 (client:354) INFO: {'Role': 'Client #10', 'Round': 4, 'Results_raw': {'train_loss': 22.449156, 'val_loss': 17.731198, 'test_loss': 16.736166}}
|
|
2024-11-13 12:10:33,228 (client:354) INFO: {'Role': 'Client #6', 'Round': 4, 'Results_raw': {'train_loss': 11.788916, 'val_loss': 11.101729, 'test_loss': 10.758002}}
|
|
2024-11-13 12:11:35,735 (client:354) INFO: {'Role': 'Client #5', 'Round': 4, 'Results_raw': {'train_loss': 7.551911, 'val_loss': 7.179509, 'test_loss': 6.876809}}
|
|
2024-11-13 12:12:46,212 (client:354) INFO: {'Role': 'Client #2', 'Round': 4, 'Results_raw': {'train_loss': 14.648255, 'val_loss': 12.184578, 'test_loss': 11.30515}}
|
|
2024-11-13 12:13:53,752 (client:354) INFO: {'Role': 'Client #8', 'Round': 4, 'Results_raw': {'train_loss': 9.287185, 'val_loss': 16.70614, 'test_loss': 8.834589}}
|
|
2024-11-13 12:14:59,187 (client:354) INFO: {'Role': 'Client #9', 'Round': 4, 'Results_raw': {'train_loss': 19.946752, 'val_loss': 17.299284, 'test_loss': 14.123088}}
|
|
2024-11-13 12:16:02,862 (client:354) INFO: {'Role': 'Client #7', 'Round': 4, 'Results_raw': {'train_loss': 14.311608, 'val_loss': 12.879522, 'test_loss': 12.048819}}
|
|
2024-11-13 12:17:06,874 (client:354) INFO: {'Role': 'Client #4', 'Round': 4, 'Results_raw': {'train_loss': 8.772715, 'val_loss': 7.418618, 'test_loss': 7.386343}}
|
|
2024-11-13 12:17:06,889 (server:615) INFO: {'Role': 'Server #', 'Round': 3, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(18.332937), 'test_loss': np.float64(64531.93674), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(19.855774), 'val_loss': np.float64(69892.323291)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(18.332937), 'test_loss': np.float64(64531.93674), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(19.855774), 'val_loss': np.float64(69892.323291)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(9.378613), 'test_avg_loss_bottom_decile': np.float64(9.447549), 'test_avg_loss_top_decile': np.float64(35.57519), 'test_avg_loss_min': np.float64(9.36048), 'test_avg_loss_max': np.float64(35.57519), 'test_avg_loss_bottom10%': np.float64(9.36048), 'test_avg_loss_top10%': np.float64(35.57519), 'test_avg_loss_cos1': np.float64(0.890268), 'test_avg_loss_entropy': np.float64(2.181779), 'test_loss_std': np.float64(33012.718628), 'test_loss_bottom_decile': np.float64(33255.374237), 'test_loss_top_decile': np.float64(125224.668762), 'test_loss_min': np.float64(32948.890961), 'test_loss_max': np.float64(125224.668762), 'test_loss_bottom10%': np.float64(32948.890961), 'test_loss_top10%': np.float64(125224.668762), 'test_loss_cos1': np.float64(0.890268), 'test_loss_entropy': np.float64(2.181779), 'val_avg_loss_std': np.float64(9.989815), 'val_avg_loss_bottom_decile': np.float64(9.932719), 'val_avg_loss_top_decile': np.float64(39.569957), 'val_avg_loss_min': np.float64(9.613061), 'val_avg_loss_max': np.float64(39.569957), 'val_avg_loss_bottom10%': np.float64(9.613061), 'val_avg_loss_top10%': np.float64(39.569957), 'val_avg_loss_cos1': np.float64(0.89331), 'val_avg_loss_entropy': np.float64(2.184426), 'val_loss_std': np.float64(35164.150553), 'val_loss_bottom_decile': np.float64(34963.170013), 'val_loss_top_decile': np.float64(139286.248291), 'val_loss_min': np.float64(33837.974548), 'val_loss_max': np.float64(139286.248291), 'val_loss_bottom10%': np.float64(33837.974548), 'val_loss_top10%': np.float64(139286.248291), 'val_loss_cos1': np.float64(0.89331), 'val_loss_entropy': np.float64(2.184426)}}
|
|
2024-11-13 12:17:06,963 (server:353) INFO: Server: Starting evaluation at the end of round 4.
|
|
2024-11-13 12:17:06,964 (server:359) INFO: ----------- Starting a new training round (Round #5) -------------
|
|
2024-11-13 12:20:14,396 (client:354) INFO: {'Role': 'Client #2', 'Round': 5, 'Results_raw': {'train_loss': 13.489656, 'val_loss': 11.941731, 'test_loss': 11.171935}}
|
|
2024-11-13 12:21:14,108 (client:354) INFO: {'Role': 'Client #5', 'Round': 5, 'Results_raw': {'train_loss': 7.374814, 'val_loss': 6.815362, 'test_loss': 6.59002}}
|
|
2024-11-13 12:22:16,678 (client:354) INFO: {'Role': 'Client #10', 'Round': 5, 'Results_raw': {'train_loss': 21.126793, 'val_loss': 18.793358, 'test_loss': 17.86883}}
|
|
2024-11-13 12:23:18,246 (client:354) INFO: {'Role': 'Client #6', 'Round': 5, 'Results_raw': {'train_loss': 11.451532, 'val_loss': 9.888646, 'test_loss': 9.681423}}
|
|
2024-11-13 12:24:20,673 (client:354) INFO: {'Role': 'Client #4', 'Round': 5, 'Results_raw': {'train_loss': 8.649138, 'val_loss': 7.467019, 'test_loss': 7.39832}}
|
|
2024-11-13 12:25:23,372 (client:354) INFO: {'Role': 'Client #1', 'Round': 5, 'Results_raw': {'train_loss': 10.01877, 'val_loss': 8.679882, 'test_loss': 8.997763}}
|
|
2024-11-13 12:26:23,672 (client:354) INFO: {'Role': 'Client #9', 'Round': 5, 'Results_raw': {'train_loss': 18.921569, 'val_loss': 19.111854, 'test_loss': 15.915066}}
|
|
2024-11-13 12:27:25,284 (client:354) INFO: {'Role': 'Client #8', 'Round': 5, 'Results_raw': {'train_loss': 8.931017, 'val_loss': 16.675466, 'test_loss': 9.238759}}
|
|
2024-11-13 12:28:28,281 (client:354) INFO: {'Role': 'Client #7', 'Round': 5, 'Results_raw': {'train_loss': 13.689856, 'val_loss': 12.277091, 'test_loss': 11.407194}}
|
|
2024-11-13 12:29:32,394 (client:354) INFO: {'Role': 'Client #3', 'Round': 5, 'Results_raw': {'train_loss': 10.132846, 'val_loss': 9.158646, 'test_loss': 9.566369}}
|
|
2024-11-13 12:29:32,398 (server:615) INFO: {'Role': 'Server #', 'Round': 4, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(17.169764), 'test_loss': np.float64(60437.568243), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(18.656055), 'val_loss': np.float64(65669.314523)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(17.169764), 'test_loss': np.float64(60437.568243), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(18.656055), 'val_loss': np.float64(65669.314523)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(8.162313), 'test_avg_loss_bottom_decile': np.float64(9.642089), 'test_avg_loss_top_decile': np.float64(31.955522), 'test_avg_loss_min': np.float64(9.27214), 'test_avg_loss_max': np.float64(31.955522), 'test_avg_loss_bottom10%': np.float64(9.27214), 'test_avg_loss_top10%': np.float64(31.955522), 'test_avg_loss_cos1': np.float64(0.903141), 'test_avg_loss_entropy': np.float64(2.198522), 'test_loss_std': np.float64(28731.341906), 'test_loss_bottom_decile': np.float64(33940.153961), 'test_loss_top_decile': np.float64(112483.438293), 'test_loss_min': np.float64(32637.933807), 'test_loss_max': np.float64(112483.438293), 'test_loss_bottom10%': np.float64(32637.933807), 'test_loss_top10%': np.float64(112483.438293), 'test_loss_cos1': np.float64(0.903141), 'test_loss_entropy': np.float64(2.198522), 'val_avg_loss_std': np.float64(8.829449), 'val_avg_loss_bottom_decile': np.float64(10.160913), 'val_avg_loss_top_decile': np.float64(35.804847), 'val_avg_loss_min': np.float64(9.49732), 'val_avg_loss_max': np.float64(35.804847), 'val_avg_loss_bottom10%': np.float64(9.49732), 'val_avg_loss_top10%': np.float64(35.804847), 'val_avg_loss_cos1': np.float64(0.903881), 'val_avg_loss_entropy': np.float64(2.198117), 'val_loss_std': np.float64(31079.65935), 'val_loss_bottom_decile': np.float64(35766.412079), 'val_loss_top_decile': np.float64(126033.062744), 'val_loss_min': np.float64(33430.566162), 'val_loss_max': np.float64(126033.062744), 'val_loss_bottom10%': np.float64(33430.566162), 'val_loss_top10%': np.float64(126033.062744), 'val_loss_cos1': np.float64(0.903881), 'val_loss_entropy': np.float64(2.198117)}}
|
|
2024-11-13 12:29:32,460 (server:353) INFO: Server: Starting evaluation at the end of round 5.
|
|
2024-11-13 12:29:32,461 (server:359) INFO: ----------- Starting a new training round (Round #6) -------------
|
|
2024-11-13 12:32:45,177 (client:354) INFO: {'Role': 'Client #6', 'Round': 6, 'Results_raw': {'train_loss': 10.850411, 'val_loss': 9.822811, 'test_loss': 9.6897}}
|
|
2024-11-13 12:33:47,443 (client:354) INFO: {'Role': 'Client #5', 'Round': 6, 'Results_raw': {'train_loss': 7.180994, 'val_loss': 6.764968, 'test_loss': 6.614311}}
|
|
2024-11-13 12:34:50,668 (client:354) INFO: {'Role': 'Client #9', 'Round': 6, 'Results_raw': {'train_loss': 16.776422, 'val_loss': 16.422513, 'test_loss': 13.449312}}
|
|
2024-11-13 12:35:52,069 (client:354) INFO: {'Role': 'Client #2', 'Round': 6, 'Results_raw': {'train_loss': 13.141578, 'val_loss': 12.032729, 'test_loss': 11.159965}}
|
|
2024-11-13 12:36:53,693 (client:354) INFO: {'Role': 'Client #4', 'Round': 6, 'Results_raw': {'train_loss': 8.553746, 'val_loss': 7.536608, 'test_loss': 7.476297}}
|
|
2024-11-13 12:37:56,893 (client:354) INFO: {'Role': 'Client #8', 'Round': 6, 'Results_raw': {'train_loss': 8.802004, 'val_loss': 17.382233, 'test_loss': 8.55516}}
|
|
2024-11-13 12:38:55,836 (client:354) INFO: {'Role': 'Client #7', 'Round': 6, 'Results_raw': {'train_loss': 13.842068, 'val_loss': 11.87142, 'test_loss': 11.024109}}
|
|
2024-11-13 12:39:58,347 (client:354) INFO: {'Role': 'Client #1', 'Round': 6, 'Results_raw': {'train_loss': 9.9808, 'val_loss': 9.627188, 'test_loss': 10.003885}}
|
|
2024-11-13 12:41:01,763 (client:354) INFO: {'Role': 'Client #3', 'Round': 6, 'Results_raw': {'train_loss': 10.118209, 'val_loss': 9.200985, 'test_loss': 9.632586}}
|
|
2024-11-13 12:42:04,418 (client:354) INFO: {'Role': 'Client #10', 'Round': 6, 'Results_raw': {'train_loss': 20.120117, 'val_loss': 18.693008, 'test_loss': 17.828205}}
|
|
2024-11-13 12:42:04,422 (server:615) INFO: {'Role': 'Server #', 'Round': 5, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(17.491204), 'test_loss': np.float64(61569.038196), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(19.04069), 'val_loss': np.float64(67023.227155)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(17.491204), 'test_loss': np.float64(61569.038196), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(19.04069), 'val_loss': np.float64(67023.227155)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(8.68813), 'test_avg_loss_bottom_decile': np.float64(9.337096), 'test_avg_loss_top_decile': np.float64(34.206757), 'test_avg_loss_min': np.float64(9.130771), 'test_avg_loss_max': np.float64(34.206757), 'test_avg_loss_bottom10%': np.float64(9.130771), 'test_avg_loss_top10%': np.float64(34.206757), 'test_avg_loss_cos1': np.float64(0.895601), 'test_avg_loss_entropy': np.float64(2.188781), 'test_loss_std': np.float64(30582.218954), 'test_loss_bottom_decile': np.float64(32866.577728), 'test_loss_top_decile': np.float64(120407.786072), 'test_loss_min': np.float64(32140.313995), 'test_loss_max': np.float64(120407.786072), 'test_loss_bottom10%': np.float64(32140.313995), 'test_loss_top10%': np.float64(120407.786072), 'test_loss_cos1': np.float64(0.895601), 'test_loss_entropy': np.float64(2.188781), 'val_avg_loss_std': np.float64(9.379272), 'val_avg_loss_bottom_decile': np.float64(9.812088), 'val_avg_loss_top_decile': np.float64(36.026094), 'val_avg_loss_min': np.float64(9.359573), 'val_avg_loss_max': np.float64(36.026094), 'val_avg_loss_bottom10%': np.float64(9.359573), 'val_avg_loss_top10%': np.float64(36.026094), 'val_avg_loss_cos1': np.float64(0.89707), 'val_avg_loss_entropy': np.float64(2.188932), 'val_loss_std': np.float64(33015.037612), 'val_loss_bottom_decile': np.float64(34538.549561), 'val_loss_top_decile': np.float64(126811.849365), 'val_loss_min': np.float64(32945.698303), 'val_loss_max': np.float64(126811.849365), 'val_loss_bottom10%': np.float64(32945.698303), 'val_loss_top10%': np.float64(126811.849365), 'val_loss_cos1': np.float64(0.89707), 'val_loss_entropy': np.float64(2.188932)}}
|
|
2024-11-13 12:42:04,456 (server:353) INFO: Server: Starting evaluation at the end of round 6.
|
|
2024-11-13 12:42:04,457 (server:359) INFO: ----------- Starting a new training round (Round #7) -------------
|
|
2024-11-13 12:45:24,256 (client:354) INFO: {'Role': 'Client #8', 'Round': 7, 'Results_raw': {'train_loss': 8.633814, 'val_loss': 14.44905, 'test_loss': 8.358004}}
|
|
2024-11-13 12:46:24,985 (client:354) INFO: {'Role': 'Client #4', 'Round': 7, 'Results_raw': {'train_loss': 8.369158, 'val_loss': 7.104688, 'test_loss': 7.006277}}
|
|
2024-11-13 12:47:25,601 (client:354) INFO: {'Role': 'Client #6', 'Round': 7, 'Results_raw': {'train_loss': 10.844008, 'val_loss': 10.255941, 'test_loss': 10.352626}}
|
|
2024-11-13 12:48:27,347 (client:354) INFO: {'Role': 'Client #10', 'Round': 7, 'Results_raw': {'train_loss': 19.336011, 'val_loss': 16.780985, 'test_loss': 16.096778}}
|
|
2024-11-13 12:49:29,995 (client:354) INFO: {'Role': 'Client #9', 'Round': 7, 'Results_raw': {'train_loss': 16.37159, 'val_loss': 18.97525, 'test_loss': 15.886051}}
|
|
2024-11-13 12:50:33,339 (client:354) INFO: {'Role': 'Client #7', 'Round': 7, 'Results_raw': {'train_loss': 13.442195, 'val_loss': 12.340389, 'test_loss': 11.503361}}
|
|
2024-11-13 12:51:34,647 (client:354) INFO: {'Role': 'Client #1', 'Round': 7, 'Results_raw': {'train_loss': 9.782895, 'val_loss': 8.680391, 'test_loss': 9.060678}}
|
|
2024-11-13 12:52:38,635 (client:354) INFO: {'Role': 'Client #3', 'Round': 7, 'Results_raw': {'train_loss': 10.011179, 'val_loss': 9.19894, 'test_loss': 9.648618}}
|
|
2024-11-13 12:53:41,394 (client:354) INFO: {'Role': 'Client #5', 'Round': 7, 'Results_raw': {'train_loss': 7.050746, 'val_loss': 6.743985, 'test_loss': 6.405131}}
|
|
2024-11-13 12:54:43,777 (client:354) INFO: {'Role': 'Client #2', 'Round': 7, 'Results_raw': {'train_loss': 13.123382, 'val_loss': 11.809266, 'test_loss': 11.008886}}
|
|
2024-11-13 12:54:43,780 (server:615) INFO: {'Role': 'Server #', 'Round': 6, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(17.400037), 'test_loss': np.float64(61248.130539), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(19.024658), 'val_loss': np.float64(66966.79487)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(17.400037), 'test_loss': np.float64(61248.130539), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(19.024658), 'val_loss': np.float64(66966.79487)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(8.909265), 'test_avg_loss_bottom_decile': np.float64(9.082845), 'test_avg_loss_top_decile': np.float64(34.370055), 'test_avg_loss_min': np.float64(8.966442), 'test_avg_loss_max': np.float64(34.370055), 'test_avg_loss_bottom10%': np.float64(8.966442), 'test_avg_loss_top10%': np.float64(34.370055), 'test_avg_loss_cos1': np.float64(0.890105), 'test_avg_loss_entropy': np.float64(2.182323), 'test_loss_std': np.float64(31360.611348), 'test_loss_bottom_decile': np.float64(31971.615295), 'test_loss_top_decile': np.float64(120982.593018), 'test_loss_min': np.float64(31561.87738), 'test_loss_max': np.float64(120982.593018), 'test_loss_bottom10%': np.float64(31561.87738), 'test_loss_top10%': np.float64(120982.593018), 'test_loss_cos1': np.float64(0.890105), 'test_loss_entropy': np.float64(2.182323), 'val_avg_loss_std': np.float64(9.707593), 'val_avg_loss_bottom_decile': np.float64(9.564867), 'val_avg_loss_top_decile': np.float64(36.942876), 'val_avg_loss_min': np.float64(9.176421), 'val_avg_loss_max': np.float64(36.942876), 'val_avg_loss_bottom10%': np.float64(9.176421), 'val_avg_loss_top10%': np.float64(36.942876), 'val_avg_loss_cos1': np.float64(0.89074), 'val_avg_loss_entropy': np.float64(2.181396), 'val_loss_std': np.float64(34170.7263), 'val_loss_bottom_decile': np.float64(33668.332581), 'val_loss_top_decile': np.float64(130038.923096), 'val_loss_min': np.float64(32301.000519), 'val_loss_max': np.float64(130038.923096), 'val_loss_bottom10%': np.float64(32301.000519), 'val_loss_top10%': np.float64(130038.923096), 'val_loss_cos1': np.float64(0.89074), 'val_loss_entropy': np.float64(2.181396)}}
|
|
2024-11-13 12:54:43,812 (server:353) INFO: Server: Starting evaluation at the end of round 7.
|
|
2024-11-13 12:54:43,813 (server:359) INFO: ----------- Starting a new training round (Round #8) -------------
|
|
2024-11-13 12:57:58,024 (client:354) INFO: {'Role': 'Client #6', 'Round': 8, 'Results_raw': {'train_loss': 10.786526, 'val_loss': 9.757758, 'test_loss': 9.685482}}
|
|
2024-11-13 12:58:42,807 (client:354) INFO: {'Role': 'Client #7', 'Round': 8, 'Results_raw': {'train_loss': 13.373115, 'val_loss': 12.005146, 'test_loss': 11.14821}}
|
|
2024-11-13 12:59:26,693 (client:354) INFO: {'Role': 'Client #2', 'Round': 8, 'Results_raw': {'train_loss': 12.537958, 'val_loss': 12.224236, 'test_loss': 11.218508}}
|
|
2024-11-13 13:00:11,929 (client:354) INFO: {'Role': 'Client #4', 'Round': 8, 'Results_raw': {'train_loss': 8.20069, 'val_loss': 7.27954, 'test_loss': 7.226707}}
|
|
2024-11-13 13:00:57,317 (client:354) INFO: {'Role': 'Client #1', 'Round': 8, 'Results_raw': {'train_loss': 9.661942, 'val_loss': 8.554383, 'test_loss': 8.885039}}
|
|
2024-11-13 13:01:43,586 (client:354) INFO: {'Role': 'Client #8', 'Round': 8, 'Results_raw': {'train_loss': 8.558252, 'val_loss': 16.363578, 'test_loss': 8.527757}}
|
|
2024-11-13 13:02:28,269 (client:354) INFO: {'Role': 'Client #5', 'Round': 8, 'Results_raw': {'train_loss': 6.917355, 'val_loss': 6.583423, 'test_loss': 6.404859}}
|
|
2024-11-13 13:03:11,396 (client:354) INFO: {'Role': 'Client #3', 'Round': 8, 'Results_raw': {'train_loss': 9.851516, 'val_loss': 9.222545, 'test_loss': 9.658188}}
|
|
2024-11-13 13:03:53,112 (client:354) INFO: {'Role': 'Client #10', 'Round': 8, 'Results_raw': {'train_loss': 18.50007, 'val_loss': 16.678955, 'test_loss': 15.9291}}
|
|
2024-11-13 13:04:36,102 (client:354) INFO: {'Role': 'Client #9', 'Round': 8, 'Results_raw': {'train_loss': 15.856597, 'val_loss': 17.324334, 'test_loss': 14.145208}}
|
|
2024-11-13 13:04:36,106 (server:615) INFO: {'Role': 'Server #', 'Round': 7, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.965843), 'test_loss': np.float64(59719.767508), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(18.56487), 'val_loss': np.float64(65348.341504)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.965843), 'test_loss': np.float64(59719.767508), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(18.56487), 'val_loss': np.float64(65348.341504)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(8.192012), 'test_avg_loss_bottom_decile': np.float64(9.101307), 'test_avg_loss_top_decile': np.float64(32.282265), 'test_avg_loss_min': np.float64(8.836013), 'test_avg_loss_max': np.float64(32.282265), 'test_avg_loss_bottom10%': np.float64(8.836013), 'test_avg_loss_top10%': np.float64(32.282265), 'test_avg_loss_cos1': np.float64(0.900518), 'test_avg_loss_entropy': np.float64(2.193938), 'test_loss_std': np.float64(28835.88143), 'test_loss_bottom_decile': np.float64(32036.599548), 'test_loss_top_decile': np.float64(113633.571289), 'test_loss_min': np.float64(31102.764557), 'test_loss_max': np.float64(113633.571289), 'test_loss_bottom10%': np.float64(31102.764557), 'test_loss_top10%': np.float64(113633.571289), 'test_loss_cos1': np.float64(0.900518), 'test_loss_entropy': np.float64(2.193938), 'val_avg_loss_std': np.float64(8.916513), 'val_avg_loss_bottom_decile': np.float64(9.562545), 'val_avg_loss_top_decile': np.float64(34.887651), 'val_avg_loss_min': np.float64(9.04735), 'val_avg_loss_max': np.float64(34.887651), 'val_avg_loss_bottom10%': np.float64(9.04735), 'val_avg_loss_top10%': np.float64(34.887651), 'val_avg_loss_cos1': np.float64(0.901421), 'val_avg_loss_entropy': np.float64(2.193212), 'val_loss_std': np.float64(31386.124162), 'val_loss_bottom_decile': np.float64(33660.159973), 'val_loss_top_decile': np.float64(122804.531372), 'val_loss_min': np.float64(31846.670258), 'val_loss_max': np.float64(122804.531372), 'val_loss_bottom10%': np.float64(31846.670258), 'val_loss_top10%': np.float64(122804.531372), 'val_loss_cos1': np.float64(0.901421), 'val_loss_entropy': np.float64(2.193212)}}
|
|
2024-11-13 13:04:36,140 (server:353) INFO: Server: Starting evaluation at the end of round 8.
|
|
2024-11-13 13:04:36,141 (server:359) INFO: ----------- Starting a new training round (Round #9) -------------
|
|
2024-11-13 13:06:46,446 (client:354) INFO: {'Role': 'Client #2', 'Round': 9, 'Results_raw': {'train_loss': 12.525942, 'val_loss': 12.103621, 'test_loss': 11.193911}}
|
|
2024-11-13 13:07:17,791 (client:354) INFO: {'Role': 'Client #9', 'Round': 9, 'Results_raw': {'train_loss': 15.74344, 'val_loss': 17.570427, 'test_loss': 14.209919}}
|
|
2024-11-13 13:07:49,228 (client:354) INFO: {'Role': 'Client #8', 'Round': 9, 'Results_raw': {'train_loss': 8.389645, 'val_loss': 16.206283, 'test_loss': 8.642534}}
|
|
2024-11-13 13:08:20,726 (client:354) INFO: {'Role': 'Client #5', 'Round': 9, 'Results_raw': {'train_loss': 6.869912, 'val_loss': 6.693667, 'test_loss': 6.541222}}
|
|
2024-11-13 13:08:52,134 (client:354) INFO: {'Role': 'Client #1', 'Round': 9, 'Results_raw': {'train_loss': 9.629425, 'val_loss': 8.644842, 'test_loss': 8.987335}}
|
|
2024-11-13 13:09:24,098 (client:354) INFO: {'Role': 'Client #4', 'Round': 9, 'Results_raw': {'train_loss': 8.184011, 'val_loss': 7.154733, 'test_loss': 7.094006}}
|
|
2024-11-13 13:09:56,408 (client:354) INFO: {'Role': 'Client #3', 'Round': 9, 'Results_raw': {'train_loss': 9.83873, 'val_loss': 8.931303, 'test_loss': 9.396786}}
|
|
2024-11-13 13:10:29,617 (client:354) INFO: {'Role': 'Client #6', 'Round': 9, 'Results_raw': {'train_loss': 10.808561, 'val_loss': 9.463777, 'test_loss': 9.594813}}
|
|
2024-11-13 13:11:02,756 (client:354) INFO: {'Role': 'Client #10', 'Round': 9, 'Results_raw': {'train_loss': 19.747171, 'val_loss': 16.894185, 'test_loss': 16.091703}}
|
|
2024-11-13 13:11:37,949 (client:354) INFO: {'Role': 'Client #7', 'Round': 9, 'Results_raw': {'train_loss': 12.914084, 'val_loss': 11.988265, 'test_loss': 11.161347}}
|
|
2024-11-13 13:11:37,953 (server:615) INFO: {'Role': 'Server #', 'Round': 8, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(17.513337), 'test_loss': np.float64(61646.947543), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(19.1085), 'val_loss': np.float64(67261.918317)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(17.513337), 'test_loss': np.float64(61646.947543), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(19.1085), 'val_loss': np.float64(67261.918317)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(8.876165), 'test_avg_loss_bottom_decile': np.float64(9.090877), 'test_avg_loss_top_decile': np.float64(34.8764), 'test_avg_loss_min': np.float64(8.909362), 'test_avg_loss_max': np.float64(34.8764), 'test_avg_loss_bottom10%': np.float64(8.909362), 'test_avg_loss_top10%': np.float64(34.8764), 'test_avg_loss_cos1': np.float64(0.891979), 'test_avg_loss_entropy': np.float64(2.183631), 'test_loss_std': np.float64(31244.099967), 'test_loss_bottom_decile': np.float64(31999.887848), 'test_loss_top_decile': np.float64(122764.929138), 'test_loss_min': np.float64(31360.954651), 'test_loss_max': np.float64(122764.929138), 'test_loss_bottom10%': np.float64(31360.954651), 'test_loss_top10%': np.float64(122764.929138), 'test_loss_cos1': np.float64(0.891979), 'test_loss_entropy': np.float64(2.183631), 'val_avg_loss_std': np.float64(9.593108), 'val_avg_loss_bottom_decile': np.float64(9.534218), 'val_avg_loss_top_decile': np.float64(36.217646), 'val_avg_loss_min': np.float64(9.103478), 'val_avg_loss_max': np.float64(36.217646), 'val_avg_loss_bottom10%': np.float64(9.103478), 'val_avg_loss_top10%': np.float64(36.217646), 'val_avg_loss_cos1': np.float64(0.893699), 'val_avg_loss_entropy': np.float64(2.183697), 'val_loss_std': np.float64(33767.740453), 'val_loss_bottom_decile': np.float64(33560.446564), 'val_loss_top_decile': np.float64(127486.114807), 'val_loss_min': np.float64(32044.24231), 'val_loss_max': np.float64(127486.114807), 'val_loss_bottom10%': np.float64(32044.24231), 'val_loss_top10%': np.float64(127486.114807), 'val_loss_cos1': np.float64(0.893699), 'val_loss_entropy': np.float64(2.183697)}}
|
|
2024-11-13 13:11:37,987 (server:353) INFO: Server: Starting evaluation at the end of round 9.
|
|
2024-11-13 13:11:37,987 (server:359) INFO: ----------- Starting a new training round (Round #10) -------------
|
|
2024-11-13 13:13:10,739 (client:354) INFO: {'Role': 'Client #6', 'Round': 10, 'Results_raw': {'train_loss': 10.351503, 'val_loss': 10.120272, 'test_loss': 10.007479}}
|
|
2024-11-13 13:13:44,428 (client:354) INFO: {'Role': 'Client #10', 'Round': 10, 'Results_raw': {'train_loss': 17.880697, 'val_loss': 19.465157, 'test_loss': 18.657847}}
|
|
2024-11-13 13:14:18,331 (client:354) INFO: {'Role': 'Client #4', 'Round': 10, 'Results_raw': {'train_loss': 8.017029, 'val_loss': 6.901297, 'test_loss': 6.889529}}
|
|
2024-11-13 13:14:50,829 (client:354) INFO: {'Role': 'Client #9', 'Round': 10, 'Results_raw': {'train_loss': 15.245442, 'val_loss': 16.8335, 'test_loss': 13.439969}}
|
|
2024-11-13 13:15:24,544 (client:354) INFO: {'Role': 'Client #3', 'Round': 10, 'Results_raw': {'train_loss': 9.714545, 'val_loss': 8.986426, 'test_loss': 9.399783}}
|
|
2024-11-13 13:15:58,880 (client:354) INFO: {'Role': 'Client #1', 'Round': 10, 'Results_raw': {'train_loss': 9.483568, 'val_loss': 8.431666, 'test_loss': 8.787958}}
|
|
2024-11-13 13:16:33,473 (client:354) INFO: {'Role': 'Client #5', 'Round': 10, 'Results_raw': {'train_loss': 6.747626, 'val_loss': 6.522574, 'test_loss': 6.431973}}
|
|
2024-11-13 13:17:08,834 (client:354) INFO: {'Role': 'Client #8', 'Round': 10, 'Results_raw': {'train_loss': 8.4416, 'val_loss': 15.24646, 'test_loss': 8.258903}}
|
|
2024-11-13 13:17:43,070 (client:354) INFO: {'Role': 'Client #2', 'Round': 10, 'Results_raw': {'train_loss': 12.316539, 'val_loss': 11.555305, 'test_loss': 10.750855}}
|
|
2024-11-13 13:18:16,651 (client:354) INFO: {'Role': 'Client #7', 'Round': 10, 'Results_raw': {'train_loss': 12.820732, 'val_loss': 11.687469, 'test_loss': 10.795376}}
|
|
2024-11-13 13:18:16,654 (server:615) INFO: {'Role': 'Server #', 'Round': 9, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(17.559453), 'test_loss': np.float64(61809.273505), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(19.242115), 'val_loss': np.float64(67732.243668)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(17.559453), 'test_loss': np.float64(61809.273505), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(19.242115), 'val_loss': np.float64(67732.243668)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(9.032341), 'test_avg_loss_bottom_decile': np.float64(9.009301), 'test_avg_loss_top_decile': np.float64(34.515104), 'test_avg_loss_min': np.float64(8.814314), 'test_avg_loss_max': np.float64(34.515104), 'test_avg_loss_bottom10%': np.float64(8.814314), 'test_avg_loss_top10%': np.float64(34.515104), 'test_avg_loss_cos1': np.float64(0.889251), 'test_avg_loss_entropy': np.float64(2.179674), 'test_loss_std': np.float64(31793.840212), 'test_loss_bottom_decile': np.float64(31712.73941), 'test_loss_top_decile': np.float64(121493.164856), 'test_loss_min': np.float64(31026.384308), 'test_loss_max': np.float64(121493.164856), 'test_loss_bottom10%': np.float64(31026.384308), 'test_loss_top10%': np.float64(121493.164856), 'test_loss_cos1': np.float64(0.889251), 'test_loss_entropy': np.float64(2.179674), 'val_avg_loss_std': np.float64(9.81827), 'val_avg_loss_bottom_decile': np.float64(9.488082), 'val_avg_loss_top_decile': np.float64(37.105139), 'val_avg_loss_min': np.float64(8.995147), 'val_avg_loss_max': np.float64(37.105139), 'val_avg_loss_bottom10%': np.float64(8.995147), 'val_avg_loss_top10%': np.float64(37.105139), 'val_avg_loss_cos1': np.float64(0.890746), 'val_avg_loss_entropy': np.float64(2.179541), 'val_loss_std': np.float64(34560.309162), 'val_loss_bottom_decile': np.float64(33398.048706), 'val_loss_top_decile': np.float64(130610.088989), 'val_loss_min': np.float64(31662.917328), 'val_loss_max': np.float64(130610.088989), 'val_loss_bottom10%': np.float64(31662.917328), 'val_loss_top10%': np.float64(130610.088989), 'val_loss_cos1': np.float64(0.890746), 'val_loss_entropy': np.float64(2.179541)}}
|
|
2024-11-13 13:18:16,687 (server:353) INFO: Server: Starting evaluation at the end of round 10.
|
|
2024-11-13 13:18:16,688 (server:359) INFO: ----------- Starting a new training round (Round #11) -------------
|
|
2024-11-13 13:19:46,023 (client:354) INFO: {'Role': 'Client #4', 'Round': 11, 'Results_raw': {'train_loss': 7.958522, 'val_loss': 7.106068, 'test_loss': 7.07359}}
|
|
2024-11-13 13:20:19,406 (client:354) INFO: {'Role': 'Client #9', 'Round': 11, 'Results_raw': {'train_loss': 15.1085, 'val_loss': 17.168103, 'test_loss': 13.845894}}
|
|
2024-11-13 13:20:55,893 (client:354) INFO: {'Role': 'Client #7', 'Round': 11, 'Results_raw': {'train_loss': 12.902291, 'val_loss': 11.727988, 'test_loss': 10.893205}}
|
|
2024-11-13 13:21:30,094 (client:354) INFO: {'Role': 'Client #5', 'Round': 11, 'Results_raw': {'train_loss': 6.732408, 'val_loss': 6.442787, 'test_loss': 6.421986}}
|
|
2024-11-13 13:22:03,376 (client:354) INFO: {'Role': 'Client #8', 'Round': 11, 'Results_raw': {'train_loss': 8.286952, 'val_loss': 15.095767, 'test_loss': 8.179237}}
|
|
2024-11-13 13:22:37,043 (client:354) INFO: {'Role': 'Client #10', 'Round': 11, 'Results_raw': {'train_loss': 17.615987, 'val_loss': 16.42587, 'test_loss': 15.825598}}
|
|
2024-11-13 13:23:09,717 (client:354) INFO: {'Role': 'Client #1', 'Round': 11, 'Results_raw': {'train_loss': 9.386197, 'val_loss': 8.492703, 'test_loss': 8.86585}}
|
|
2024-11-13 13:23:41,208 (client:354) INFO: {'Role': 'Client #6', 'Round': 11, 'Results_raw': {'train_loss': 10.340995, 'val_loss': 9.495864, 'test_loss': 9.444946}}
|
|
2024-11-13 13:24:12,612 (client:354) INFO: {'Role': 'Client #3', 'Round': 11, 'Results_raw': {'train_loss': 9.681408, 'val_loss': 8.94808, 'test_loss': 9.354983}}
|
|
2024-11-13 13:24:44,272 (client:354) INFO: {'Role': 'Client #2', 'Round': 11, 'Results_raw': {'train_loss': 12.89376, 'val_loss': 12.570182, 'test_loss': 11.950895}}
|
|
2024-11-13 13:24:44,275 (server:615) INFO: {'Role': 'Server #', 'Round': 10, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(17.055898), 'test_loss': np.float64(60036.762546), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(18.681424), 'val_loss': np.float64(65758.613617)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(17.055898), 'test_loss': np.float64(60036.762546), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(18.681424), 'val_loss': np.float64(65758.613617)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(8.474787), 'test_avg_loss_bottom_decile': np.float64(8.912069), 'test_avg_loss_top_decile': np.float64(32.565543), 'test_avg_loss_min': np.float64(8.825782), 'test_avg_loss_max': np.float64(32.565543), 'test_avg_loss_bottom10%': np.float64(8.825782), 'test_avg_loss_top10%': np.float64(32.565543), 'test_avg_loss_cos1': np.float64(0.895541), 'test_avg_loss_entropy': np.float64(2.187817), 'test_loss_std': np.float64(29831.249427), 'test_loss_bottom_decile': np.float64(31370.481567), 'test_loss_top_decile': np.float64(114630.711548), 'test_loss_min': np.float64(31066.751892), 'test_loss_max': np.float64(114630.711548), 'test_loss_bottom10%': np.float64(31066.751892), 'test_loss_top10%': np.float64(114630.711548), 'test_loss_cos1': np.float64(0.895541), 'test_loss_entropy': np.float64(2.187817), 'val_avg_loss_std': np.float64(9.249549), 'val_avg_loss_bottom_decile': np.float64(9.333148), 'val_avg_loss_top_decile': np.float64(36.208037), 'val_avg_loss_min': np.float64(9.01093), 'val_avg_loss_max': np.float64(36.208037), 'val_avg_loss_bottom10%': np.float64(9.01093), 'val_avg_loss_top10%': np.float64(36.208037), 'val_avg_loss_cos1': np.float64(0.89617), 'val_avg_loss_entropy': np.float64(2.18674), 'val_loss_std': np.float64(32558.411843), 'val_loss_bottom_decile': np.float64(32852.681824), 'val_loss_top_decile': np.float64(127452.291687), 'val_loss_min': np.float64(31718.473053), 'val_loss_max': np.float64(127452.291687), 'val_loss_bottom10%': np.float64(31718.473053), 'val_loss_top10%': np.float64(127452.291687), 'val_loss_cos1': np.float64(0.89617), 'val_loss_entropy': np.float64(2.18674)}}
|
|
2024-11-13 13:24:44,306 (server:353) INFO: Server: Starting evaluation at the end of round 11.
|
|
2024-11-13 13:24:44,307 (server:359) INFO: ----------- Starting a new training round (Round #12) -------------
|
|
2024-11-13 13:26:24,232 (client:354) INFO: {'Role': 'Client #9', 'Round': 12, 'Results_raw': {'train_loss': 15.551044, 'val_loss': 16.378783, 'test_loss': 13.190151}}
|
|
2024-11-13 13:26:56,483 (client:354) INFO: {'Role': 'Client #2', 'Round': 12, 'Results_raw': {'train_loss': 11.979209, 'val_loss': 11.937206, 'test_loss': 11.183255}}
|
|
2024-11-13 13:27:28,349 (client:354) INFO: {'Role': 'Client #10', 'Round': 12, 'Results_raw': {'train_loss': 18.8395, 'val_loss': 17.073027, 'test_loss': 16.14393}}
|
|
2024-11-13 13:27:59,951 (client:354) INFO: {'Role': 'Client #7', 'Round': 12, 'Results_raw': {'train_loss': 12.822219, 'val_loss': 11.769252, 'test_loss': 10.916748}}
|
|
2024-11-13 13:28:31,466 (client:354) INFO: {'Role': 'Client #3', 'Round': 12, 'Results_raw': {'train_loss': 9.567347, 'val_loss': 8.920262, 'test_loss': 9.39694}}
|
|
2024-11-13 13:29:03,267 (client:354) INFO: {'Role': 'Client #5', 'Round': 12, 'Results_raw': {'train_loss': 6.65877, 'val_loss': 6.47235, 'test_loss': 6.189583}}
|
|
2024-11-13 13:29:34,649 (client:354) INFO: {'Role': 'Client #1', 'Round': 12, 'Results_raw': {'train_loss': 9.426573, 'val_loss': 8.547455, 'test_loss': 8.858365}}
|
|
2024-11-13 13:30:06,241 (client:354) INFO: {'Role': 'Client #6', 'Round': 12, 'Results_raw': {'train_loss': 10.093835, 'val_loss': 9.617583, 'test_loss': 9.505684}}
|
|
2024-11-13 13:30:38,053 (client:354) INFO: {'Role': 'Client #4', 'Round': 12, 'Results_raw': {'train_loss': 7.900791, 'val_loss': 7.102919, 'test_loss': 7.019229}}
|
|
2024-11-13 13:31:09,663 (client:354) INFO: {'Role': 'Client #8', 'Round': 12, 'Results_raw': {'train_loss': 8.301343, 'val_loss': 15.764237, 'test_loss': 8.359019}}
|
|
2024-11-13 13:31:09,667 (server:615) INFO: {'Role': 'Server #', 'Round': 11, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.978566), 'test_loss': np.float64(59764.550632), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(18.599172), 'val_loss': np.float64(65469.087036)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.978566), 'test_loss': np.float64(59764.550632), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(18.599172), 'val_loss': np.float64(65469.087036)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(8.48236), 'test_avg_loss_bottom_decile': np.float64(8.803158), 'test_avg_loss_top_decile': np.float64(33.130614), 'test_avg_loss_min': np.float64(8.688693), 'test_avg_loss_max': np.float64(33.130614), 'test_avg_loss_bottom10%': np.float64(8.688693), 'test_avg_loss_top10%': np.float64(33.130614), 'test_avg_loss_cos1': np.float64(0.894573), 'test_avg_loss_entropy': np.float64(2.186711), 'test_loss_std': np.float64(29857.906141), 'test_loss_bottom_decile': np.float64(30987.115448), 'test_loss_top_decile': np.float64(116619.759766), 'test_loss_min': np.float64(30584.198883), 'test_loss_max': np.float64(116619.759766), 'test_loss_bottom10%': np.float64(30584.198883), 'test_loss_top10%': np.float64(116619.759766), 'test_loss_cos1': np.float64(0.894573), 'test_loss_entropy': np.float64(2.186711), 'val_avg_loss_std': np.float64(9.226276), 'val_avg_loss_bottom_decile': np.float64(9.204087), 'val_avg_loss_top_decile': np.float64(35.380232), 'val_avg_loss_min': np.float64(8.872019), 'val_avg_loss_max': np.float64(35.380232), 'val_avg_loss_bottom10%': np.float64(8.872019), 'val_avg_loss_top10%': np.float64(35.380232), 'val_avg_loss_cos1': np.float64(0.895835), 'val_avg_loss_entropy': np.float64(2.186095), 'val_loss_std': np.float64(32476.492925), 'val_loss_bottom_decile': np.float64(32398.386993), 'val_loss_top_decile': np.float64(124538.414978), 'val_loss_min': np.float64(31229.505493), 'val_loss_max': np.float64(124538.414978), 'val_loss_bottom10%': np.float64(31229.505493), 'val_loss_top10%': np.float64(124538.414978), 'val_loss_cos1': np.float64(0.895835), 'val_loss_entropy': np.float64(2.186095)}}
|
|
2024-11-13 13:31:09,701 (server:353) INFO: Server: Starting evaluation at the end of round 12.
|
|
2024-11-13 13:31:09,701 (server:359) INFO: ----------- Starting a new training round (Round #13) -------------
|
|
2024-11-13 13:32:36,977 (client:354) INFO: {'Role': 'Client #10', 'Round': 13, 'Results_raw': {'train_loss': 17.096842, 'val_loss': 15.905669, 'test_loss': 15.291621}}
|
|
2024-11-13 13:33:08,022 (client:354) INFO: {'Role': 'Client #5', 'Round': 13, 'Results_raw': {'train_loss': 6.566139, 'val_loss': 6.522965, 'test_loss': 6.352309}}
|
|
2024-11-13 13:33:39,053 (client:354) INFO: {'Role': 'Client #7', 'Round': 13, 'Results_raw': {'train_loss': 12.514339, 'val_loss': 11.449629, 'test_loss': 10.577688}}
|
|
2024-11-13 13:34:10,087 (client:354) INFO: {'Role': 'Client #8', 'Round': 13, 'Results_raw': {'train_loss': 8.234365, 'val_loss': 16.786284, 'test_loss': 8.432843}}
|
|
2024-11-13 13:34:41,412 (client:354) INFO: {'Role': 'Client #1', 'Round': 13, 'Results_raw': {'train_loss': 9.325908, 'val_loss': 8.463017, 'test_loss': 8.811999}}
|
|
2024-11-13 13:35:13,062 (client:354) INFO: {'Role': 'Client #9', 'Round': 13, 'Results_raw': {'train_loss': 14.629133, 'val_loss': 16.051464, 'test_loss': 12.736055}}
|
|
2024-11-13 13:35:44,780 (client:354) INFO: {'Role': 'Client #6', 'Round': 13, 'Results_raw': {'train_loss': 10.162932, 'val_loss': 9.968169, 'test_loss': 9.818562}}
|
|
2024-11-13 13:36:16,526 (client:354) INFO: {'Role': 'Client #3', 'Round': 13, 'Results_raw': {'train_loss': 9.507018, 'val_loss': 8.980003, 'test_loss': 9.439348}}
|
|
2024-11-13 13:36:48,595 (client:354) INFO: {'Role': 'Client #2', 'Round': 13, 'Results_raw': {'train_loss': 12.059659, 'val_loss': 11.474488, 'test_loss': 10.732812}}
|
|
2024-11-13 13:37:19,982 (client:354) INFO: {'Role': 'Client #4', 'Round': 13, 'Results_raw': {'train_loss': 7.939238, 'val_loss': 6.949189, 'test_loss': 6.991839}}
|
|
2024-11-13 13:37:19,985 (server:615) INFO: {'Role': 'Server #', 'Round': 12, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(17.282425), 'test_loss': np.float64(60834.136981), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(18.901561), 'val_loss': np.float64(66533.494937)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(17.282425), 'test_loss': np.float64(60834.136981), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(18.901561), 'val_loss': np.float64(66533.494937)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(8.844486), 'test_avg_loss_bottom_decile': np.float64(8.931207), 'test_avg_loss_top_decile': np.float64(33.723188), 'test_avg_loss_min': np.float64(8.76562), 'test_avg_loss_max': np.float64(33.723188), 'test_avg_loss_bottom10%': np.float64(8.76562), 'test_avg_loss_top10%': np.float64(33.723188), 'test_avg_loss_cos1': np.float64(0.8902), 'test_avg_loss_entropy': np.float64(2.181371), 'test_loss_std': np.float64(31132.590553), 'test_loss_bottom_decile': np.float64(31437.848816), 'test_loss_top_decile': np.float64(118705.62146), 'test_loss_min': np.float64(30854.983612), 'test_loss_max': np.float64(118705.62146), 'test_loss_bottom10%': np.float64(30854.983612), 'test_loss_top10%': np.float64(118705.62146), 'test_loss_cos1': np.float64(0.8902), 'test_loss_entropy': np.float64(2.181371), 'val_avg_loss_std': np.float64(9.606344), 'val_avg_loss_bottom_decile': np.float64(9.365228), 'val_avg_loss_top_decile': np.float64(36.901144), 'val_avg_loss_min': np.float64(8.947647), 'val_avg_loss_max': np.float64(36.901144), 'val_avg_loss_bottom10%': np.float64(8.947647), 'val_avg_loss_top10%': np.float64(36.901144), 'val_avg_loss_cos1': np.float64(0.891473), 'val_avg_loss_entropy': np.float64(2.181017), 'val_loss_std': np.float64(33814.3314), 'val_loss_bottom_decile': np.float64(32965.603638), 'val_loss_top_decile': np.float64(129892.025391), 'val_loss_min': np.float64(31495.718018), 'val_loss_max': np.float64(129892.025391), 'val_loss_bottom10%': np.float64(31495.718018), 'val_loss_top10%': np.float64(129892.025391), 'val_loss_cos1': np.float64(0.891473), 'val_loss_entropy': np.float64(2.181017)}}
|
|
2024-11-13 13:37:20,016 (server:353) INFO: Server: Starting evaluation at the end of round 13.
|
|
2024-11-13 13:37:20,017 (server:359) INFO: ----------- Starting a new training round (Round #14) -------------
|
|
2024-11-13 13:38:54,970 (client:354) INFO: {'Role': 'Client #9', 'Round': 14, 'Results_raw': {'train_loss': 14.761739, 'val_loss': 16.813473, 'test_loss': 13.510155}}
|
|
2024-11-13 13:39:55,534 (client:354) INFO: {'Role': 'Client #4', 'Round': 14, 'Results_raw': {'train_loss': 7.850667, 'val_loss': 6.91111, 'test_loss': 6.899488}}
|
|
2024-11-13 13:40:56,098 (client:354) INFO: {'Role': 'Client #8', 'Round': 14, 'Results_raw': {'train_loss': 8.161234, 'val_loss': 16.169449, 'test_loss': 8.215305}}
|
|
2024-11-13 13:41:58,274 (client:354) INFO: {'Role': 'Client #6', 'Round': 14, 'Results_raw': {'train_loss': 9.825337, 'val_loss': 9.514659, 'test_loss': 9.479626}}
|
|
2024-11-13 13:43:01,225 (client:354) INFO: {'Role': 'Client #7', 'Round': 14, 'Results_raw': {'train_loss': 12.255893, 'val_loss': 11.592986, 'test_loss': 10.809279}}
|
|
2024-11-13 13:44:05,375 (client:354) INFO: {'Role': 'Client #5', 'Round': 14, 'Results_raw': {'train_loss': 6.538667, 'val_loss': 6.543675, 'test_loss': 6.387964}}
|
|
2024-11-13 13:45:09,876 (client:354) INFO: {'Role': 'Client #3', 'Round': 14, 'Results_raw': {'train_loss': 9.483314, 'val_loss': 8.87563, 'test_loss': 9.355579}}
|
|
2024-11-13 13:46:14,034 (client:354) INFO: {'Role': 'Client #10', 'Round': 14, 'Results_raw': {'train_loss': 17.707403, 'val_loss': 16.116933, 'test_loss': 15.345731}}
|
|
2024-11-13 13:47:17,545 (client:354) INFO: {'Role': 'Client #1', 'Round': 14, 'Results_raw': {'train_loss': 9.334867, 'val_loss': 8.38755, 'test_loss': 8.780623}}
|
|
2024-11-13 13:48:20,419 (client:354) INFO: {'Role': 'Client #2', 'Round': 14, 'Results_raw': {'train_loss': 12.372472, 'val_loss': 11.981764, 'test_loss': 11.234413}}
|
|
2024-11-13 13:48:20,422 (server:615) INFO: {'Role': 'Server #', 'Round': 13, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(17.460818), 'test_loss': np.float64(61462.080786), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(19.085714), 'val_loss': np.float64(67181.713162)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(17.460818), 'test_loss': np.float64(61462.080786), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(19.085714), 'val_loss': np.float64(67181.713162)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(9.099721), 'test_avg_loss_bottom_decile': np.float64(8.797792), 'test_avg_loss_top_decile': np.float64(34.692361), 'test_avg_loss_min': np.float64(8.645883), 'test_avg_loss_max': np.float64(34.692361), 'test_avg_loss_bottom10%': np.float64(8.645883), 'test_avg_loss_top10%': np.float64(34.692361), 'test_avg_loss_cos1': np.float64(0.886799), 'test_avg_loss_entropy': np.float64(2.176496), 'test_loss_std': np.float64(32031.018709), 'test_loss_bottom_decile': np.float64(30968.22757), 'test_loss_top_decile': np.float64(122117.110046), 'test_loss_min': np.float64(30433.506561), 'test_loss_max': np.float64(122117.110046), 'test_loss_bottom10%': np.float64(30433.506561), 'test_loss_top10%': np.float64(122117.110046), 'test_loss_cos1': np.float64(0.886799), 'test_loss_entropy': np.float64(2.176496), 'val_avg_loss_std': np.float64(9.80255), 'val_avg_loss_bottom_decile': np.float64(9.208626), 'val_avg_loss_top_decile': np.float64(37.024808), 'val_avg_loss_min': np.float64(8.811485), 'val_avg_loss_max': np.float64(37.024808), 'val_avg_loss_bottom10%': np.float64(8.811485), 'val_avg_loss_top10%': np.float64(37.024808), 'val_avg_loss_cos1': np.float64(0.889533), 'val_avg_loss_entropy': np.float64(2.177678), 'val_loss_std': np.float64(34504.977716), 'val_loss_bottom_decile': np.float64(32414.364655), 'val_loss_top_decile': np.float64(130327.324463), 'val_loss_min': np.float64(31016.426422), 'val_loss_max': np.float64(130327.324463), 'val_loss_bottom10%': np.float64(31016.426422), 'val_loss_top10%': np.float64(130327.324463), 'val_loss_cos1': np.float64(0.889533), 'val_loss_entropy': np.float64(2.177678)}}
|
|
2024-11-13 13:48:20,464 (server:353) INFO: Server: Starting evaluation at the end of round 14.
|
|
2024-11-13 13:48:20,466 (server:359) INFO: ----------- Starting a new training round (Round #15) -------------
|
|
2024-11-13 13:51:38,173 (client:354) INFO: {'Role': 'Client #7', 'Round': 15, 'Results_raw': {'train_loss': 12.457159, 'val_loss': 11.46481, 'test_loss': 10.640413}}
|
|
2024-11-13 13:52:40,394 (client:354) INFO: {'Role': 'Client #3', 'Round': 15, 'Results_raw': {'train_loss': 9.506425, 'val_loss': 8.858363, 'test_loss': 9.326106}}
|
|
2024-11-13 13:53:42,270 (client:354) INFO: {'Role': 'Client #4', 'Round': 15, 'Results_raw': {'train_loss': 7.889191, 'val_loss': 6.991324, 'test_loss': 6.980906}}
|
|
2024-11-13 13:54:42,717 (client:354) INFO: {'Role': 'Client #5', 'Round': 15, 'Results_raw': {'train_loss': 6.446141, 'val_loss': 6.41032, 'test_loss': 6.320064}}
|
|
2024-11-13 13:55:43,751 (client:354) INFO: {'Role': 'Client #9', 'Round': 15, 'Results_raw': {'train_loss': 14.217459, 'val_loss': 15.822074, 'test_loss': 12.489953}}
|
|
2024-11-13 13:56:47,391 (client:354) INFO: {'Role': 'Client #2', 'Round': 15, 'Results_raw': {'train_loss': 11.949058, 'val_loss': 11.6894, 'test_loss': 10.746527}}
|
|
2024-11-13 13:57:50,247 (client:354) INFO: {'Role': 'Client #6', 'Round': 15, 'Results_raw': {'train_loss': 9.806999, 'val_loss': 9.596769, 'test_loss': 9.556778}}
|
|
2024-11-13 13:58:50,812 (client:354) INFO: {'Role': 'Client #8', 'Round': 15, 'Results_raw': {'train_loss': 8.060857, 'val_loss': 15.182861, 'test_loss': 8.339282}}
|
|
2024-11-13 13:59:51,819 (client:354) INFO: {'Role': 'Client #10', 'Round': 15, 'Results_raw': {'train_loss': 18.372237, 'val_loss': 16.638446, 'test_loss': 15.99996}}
|
|
2024-11-13 14:00:54,251 (client:354) INFO: {'Role': 'Client #1', 'Round': 15, 'Results_raw': {'train_loss': 9.331001, 'val_loss': 8.478948, 'test_loss': 8.920371}}
|
|
2024-11-13 14:00:54,255 (server:615) INFO: {'Role': 'Server #', 'Round': 14, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.95084), 'test_loss': np.float64(59666.955817), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(18.531166), 'val_loss': np.float64(65229.703464)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.95084), 'test_loss': np.float64(59666.955817), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(18.531166), 'val_loss': np.float64(65229.703464)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(8.498174), 'test_avg_loss_bottom_decile': np.float64(8.752238), 'test_avg_loss_top_decile': np.float64(32.719452), 'test_avg_loss_min': np.float64(8.605916), 'test_avg_loss_max': np.float64(32.719452), 'test_avg_loss_bottom10%': np.float64(8.605916), 'test_avg_loss_top10%': np.float64(32.719452), 'test_avg_loss_cos1': np.float64(0.893947), 'test_avg_loss_entropy': np.float64(2.185475), 'test_loss_std': np.float64(29913.574189), 'test_loss_bottom_decile': np.float64(30807.878387), 'test_loss_top_decile': np.float64(115172.470764), 'test_loss_min': np.float64(30292.823822), 'test_loss_max': np.float64(115172.470764), 'test_loss_bottom10%': np.float64(30292.823822), 'test_loss_top10%': np.float64(115172.470764), 'test_loss_cos1': np.float64(0.893947), 'test_loss_entropy': np.float64(2.185475), 'val_avg_loss_std': np.float64(9.169555), 'val_avg_loss_bottom_decile': np.float64(9.166066), 'val_avg_loss_top_decile': np.float64(35.554757), 'val_avg_loss_min': np.float64(8.780934), 'val_avg_loss_max': np.float64(35.554757), 'val_avg_loss_bottom10%': np.float64(8.780934), 'val_avg_loss_top10%': np.float64(35.554757), 'val_avg_loss_cos1': np.float64(0.896277), 'val_avg_loss_entropy': np.float64(2.18615), 'val_loss_std': np.float64(32276.8336), 'val_loss_bottom_decile': np.float64(32264.553833), 'val_loss_top_decile': np.float64(125152.745728), 'val_loss_min': np.float64(30908.8862), 'val_loss_max': np.float64(125152.745728), 'val_loss_bottom10%': np.float64(30908.8862), 'val_loss_top10%': np.float64(125152.745728), 'val_loss_cos1': np.float64(0.896277), 'val_loss_entropy': np.float64(2.18615)}}
|
|
2024-11-13 14:00:54,291 (server:353) INFO: Server: Starting evaluation at the end of round 15.
|
|
2024-11-13 14:00:54,291 (server:359) INFO: ----------- Starting a new training round (Round #16) -------------
|
|
2024-11-13 14:04:07,340 (client:354) INFO: {'Role': 'Client #2', 'Round': 16, 'Results_raw': {'train_loss': 11.971199, 'val_loss': 11.842932, 'test_loss': 10.888008}}
|
|
2024-11-13 14:05:06,997 (client:354) INFO: {'Role': 'Client #9', 'Round': 16, 'Results_raw': {'train_loss': 14.340613, 'val_loss': 15.483268, 'test_loss': 12.305411}}
|
|
2024-11-13 14:06:09,888 (client:354) INFO: {'Role': 'Client #5', 'Round': 16, 'Results_raw': {'train_loss': 6.436503, 'val_loss': 6.27308, 'test_loss': 6.130719}}
|
|
2024-11-13 14:07:12,438 (client:354) INFO: {'Role': 'Client #8', 'Round': 16, 'Results_raw': {'train_loss': 8.007172, 'val_loss': 16.383841, 'test_loss': 8.091962}}
|
|
2024-11-13 14:08:15,393 (client:354) INFO: {'Role': 'Client #6', 'Round': 16, 'Results_raw': {'train_loss': 9.770893, 'val_loss': 9.230331, 'test_loss': 9.190709}}
|
|
2024-11-13 14:09:18,240 (client:354) INFO: {'Role': 'Client #10', 'Round': 16, 'Results_raw': {'train_loss': 18.29967, 'val_loss': 16.114535, 'test_loss': 15.71456}}
|
|
2024-11-13 14:10:16,694 (client:354) INFO: {'Role': 'Client #4', 'Round': 16, 'Results_raw': {'train_loss': 7.751984, 'val_loss': 6.882247, 'test_loss': 6.907168}}
|
|
2024-11-13 14:11:16,482 (client:354) INFO: {'Role': 'Client #3', 'Round': 16, 'Results_raw': {'train_loss': 9.437164, 'val_loss': 8.905833, 'test_loss': 9.357628}}
|
|
2024-11-13 14:12:17,741 (client:354) INFO: {'Role': 'Client #1', 'Round': 16, 'Results_raw': {'train_loss': 9.198743, 'val_loss': 8.278701, 'test_loss': 8.653906}}
|
|
2024-11-13 14:13:20,216 (client:354) INFO: {'Role': 'Client #7', 'Round': 16, 'Results_raw': {'train_loss': 12.361143, 'val_loss': 11.355048, 'test_loss': 10.543837}}
|
|
2024-11-13 14:13:20,220 (server:615) INFO: {'Role': 'Server #', 'Round': 15, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(17.105302), 'test_loss': np.float64(60210.661777), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(18.696271), 'val_loss': np.float64(65810.875217)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(17.105302), 'test_loss': np.float64(60210.661777), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(18.696271), 'val_loss': np.float64(65810.875217)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(8.694403), 'test_avg_loss_bottom_decile': np.float64(8.892721), 'test_avg_loss_top_decile': np.float64(33.284071), 'test_avg_loss_min': np.float64(8.679802), 'test_avg_loss_max': np.float64(33.284071), 'test_avg_loss_bottom10%': np.float64(8.679802), 'test_avg_loss_top10%': np.float64(33.284071), 'test_avg_loss_cos1': np.float64(0.891453), 'test_avg_loss_entropy': np.float64(2.183074), 'test_loss_std': np.float64(30604.297573), 'test_loss_bottom_decile': np.float64(31302.377838), 'test_loss_top_decile': np.float64(117159.931641), 'test_loss_min': np.float64(30552.903351), 'test_loss_max': np.float64(117159.931641), 'test_loss_bottom10%': np.float64(30552.903351), 'test_loss_top10%': np.float64(117159.931641), 'test_loss_cos1': np.float64(0.891453), 'test_loss_entropy': np.float64(2.183074), 'val_avg_loss_std': np.float64(9.394735), 'val_avg_loss_bottom_decile': np.float64(9.312655), 'val_avg_loss_top_decile': np.float64(36.394391), 'val_avg_loss_min': np.float64(8.862064), 'val_avg_loss_max': np.float64(36.394391), 'val_avg_loss_bottom10%': np.float64(8.862064), 'val_avg_loss_top10%': np.float64(36.394391), 'val_avg_loss_cos1': np.float64(0.893535), 'val_avg_loss_entropy': np.float64(2.18351), 'val_loss_std': np.float64(33069.468754), 'val_loss_bottom_decile': np.float64(32780.545654), 'val_loss_top_decile': np.float64(128108.257263), 'val_loss_min': np.float64(31194.464539), 'val_loss_max': np.float64(128108.257263), 'val_loss_bottom10%': np.float64(31194.464539), 'val_loss_top10%': np.float64(128108.257263), 'val_loss_cos1': np.float64(0.893535), 'val_loss_entropy': np.float64(2.18351)}}
|
|
2024-11-13 14:13:20,261 (server:353) INFO: Server: Starting evaluation at the end of round 16.
|
|
2024-11-13 14:13:20,262 (server:359) INFO: ----------- Starting a new training round (Round #17) -------------
|
|
2024-11-13 14:16:38,198 (client:354) INFO: {'Role': 'Client #10', 'Round': 17, 'Results_raw': {'train_loss': 17.187188, 'val_loss': 17.169304, 'test_loss': 16.248594}}
|
|
2024-11-13 14:17:39,030 (client:354) INFO: {'Role': 'Client #5', 'Round': 17, 'Results_raw': {'train_loss': 6.43731, 'val_loss': 6.312496, 'test_loss': 6.302172}}
|
|
2024-11-13 14:18:37,918 (client:354) INFO: {'Role': 'Client #3', 'Round': 17, 'Results_raw': {'train_loss': 9.343231, 'val_loss': 8.891419, 'test_loss': 9.355118}}
|
|
2024-11-13 14:19:38,742 (client:354) INFO: {'Role': 'Client #7', 'Round': 17, 'Results_raw': {'train_loss': 12.171521, 'val_loss': 11.357978, 'test_loss': 10.509802}}
|
|
2024-11-13 14:20:41,021 (client:354) INFO: {'Role': 'Client #2', 'Round': 17, 'Results_raw': {'train_loss': 11.924221, 'val_loss': 11.455994, 'test_loss': 10.570448}}
|
|
2024-11-13 14:21:42,969 (client:354) INFO: {'Role': 'Client #4', 'Round': 17, 'Results_raw': {'train_loss': 7.730288, 'val_loss': 6.948241, 'test_loss': 6.946596}}
|
|
2024-11-13 14:22:44,920 (client:354) INFO: {'Role': 'Client #8', 'Round': 17, 'Results_raw': {'train_loss': 7.992001, 'val_loss': 15.618191, 'test_loss': 8.217604}}
|
|
2024-11-13 14:23:42,459 (client:354) INFO: {'Role': 'Client #9', 'Round': 17, 'Results_raw': {'train_loss': 14.998107, 'val_loss': 16.211822, 'test_loss': 12.789305}}
|
|
2024-11-13 14:24:30,086 (client:354) INFO: {'Role': 'Client #6', 'Round': 17, 'Results_raw': {'train_loss': 9.64042, 'val_loss': 9.351718, 'test_loss': 9.307921}}
|
|
2024-11-13 14:25:18,613 (client:354) INFO: {'Role': 'Client #1', 'Round': 17, 'Results_raw': {'train_loss': 9.226212, 'val_loss': 8.321399, 'test_loss': 8.694515}}
|
|
2024-11-13 14:25:18,617 (server:615) INFO: {'Role': 'Server #', 'Round': 16, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(17.0929), 'test_loss': np.float64(60167.007452), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(18.702164), 'val_loss': np.float64(65831.618216)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(17.0929), 'test_loss': np.float64(60167.007452), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(18.702164), 'val_loss': np.float64(65831.618216)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(8.802964), 'test_avg_loss_bottom_decile': np.float64(8.725305), 'test_avg_loss_top_decile': np.float64(33.587757), 'test_avg_loss_min': np.float64(8.649861), 'test_avg_loss_max': np.float64(33.587757), 'test_avg_loss_bottom10%': np.float64(8.649861), 'test_avg_loss_top10%': np.float64(33.587757), 'test_avg_loss_cos1': np.float64(0.889027), 'test_avg_loss_entropy': np.float64(2.179935), 'test_loss_std': np.float64(30986.432489), 'test_loss_bottom_decile': np.float64(30713.074371), 'test_loss_top_decile': np.float64(118228.905212), 'test_loss_min': np.float64(30447.509186), 'test_loss_max': np.float64(118228.905212), 'test_loss_bottom10%': np.float64(30447.509186), 'test_loss_top10%': np.float64(118228.905212), 'test_loss_cos1': np.float64(0.889027), 'test_loss_entropy': np.float64(2.179935), 'val_avg_loss_std': np.float64(9.488441), 'val_avg_loss_bottom_decile': np.float64(9.169772), 'val_avg_loss_top_decile': np.float64(36.521427), 'val_avg_loss_min': np.float64(8.828745), 'val_avg_loss_max': np.float64(36.521427), 'val_avg_loss_bottom10%': np.float64(8.828745), 'val_avg_loss_top10%': np.float64(36.521427), 'val_avg_loss_cos1': np.float64(0.891792), 'val_avg_loss_entropy': np.float64(2.181141), 'val_loss_std': np.float64(33399.313267), 'val_loss_bottom_decile': np.float64(32277.598663), 'val_loss_top_decile': np.float64(128555.424744), 'val_loss_min': np.float64(31077.181793), 'val_loss_max': np.float64(128555.424744), 'val_loss_bottom10%': np.float64(31077.181793), 'val_loss_top10%': np.float64(128555.424744), 'val_loss_cos1': np.float64(0.891792), 'val_loss_entropy': np.float64(2.181141)}}
|
|
2024-11-13 14:25:18,657 (server:353) INFO: Server: Starting evaluation at the end of round 17.
|
|
2024-11-13 14:25:18,657 (server:359) INFO: ----------- Starting a new training round (Round #18) -------------
|
|
2024-11-13 14:27:33,344 (client:354) INFO: {'Role': 'Client #3', 'Round': 18, 'Results_raw': {'train_loss': 9.374504, 'val_loss': 8.813522, 'test_loss': 9.277867}}
|
|
2024-11-13 14:28:22,477 (client:354) INFO: {'Role': 'Client #5', 'Round': 18, 'Results_raw': {'train_loss': 6.379247, 'val_loss': 6.337491, 'test_loss': 6.08709}}
|
|
2024-11-13 14:29:09,839 (client:354) INFO: {'Role': 'Client #7', 'Round': 18, 'Results_raw': {'train_loss': 11.951051, 'val_loss': 11.359471, 'test_loss': 10.463708}}
|
|
2024-11-13 14:29:57,670 (client:354) INFO: {'Role': 'Client #9', 'Round': 18, 'Results_raw': {'train_loss': 15.095971, 'val_loss': 15.831142, 'test_loss': 12.394991}}
|
|
2024-11-13 14:30:41,218 (client:354) INFO: {'Role': 'Client #10', 'Round': 18, 'Results_raw': {'train_loss': 17.905411, 'val_loss': 16.137648, 'test_loss': 15.679186}}
|
|
2024-11-13 14:31:20,512 (client:354) INFO: {'Role': 'Client #1', 'Round': 18, 'Results_raw': {'train_loss': 9.169103, 'val_loss': 8.411161, 'test_loss': 8.800432}}
|
|
2024-11-13 14:31:58,773 (client:354) INFO: {'Role': 'Client #4', 'Round': 18, 'Results_raw': {'train_loss': 7.749408, 'val_loss': 6.932917, 'test_loss': 6.974452}}
|
|
2024-11-13 14:32:37,390 (client:354) INFO: {'Role': 'Client #8', 'Round': 18, 'Results_raw': {'train_loss': 7.984848, 'val_loss': 14.380704, 'test_loss': 8.205664}}
|
|
2024-11-13 14:33:15,617 (client:354) INFO: {'Role': 'Client #2', 'Round': 18, 'Results_raw': {'train_loss': 11.4799, 'val_loss': 11.067674, 'test_loss': 10.234107}}
|
|
2024-11-13 14:33:54,609 (client:354) INFO: {'Role': 'Client #6', 'Round': 18, 'Results_raw': {'train_loss': 9.792362, 'val_loss': 9.735672, 'test_loss': 9.627817}}
|
|
2024-11-13 14:33:54,613 (server:615) INFO: {'Role': 'Server #', 'Round': 17, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(17.115498), 'test_loss': np.float64(60246.553162), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(18.697357), 'val_loss': np.float64(65814.695898)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(17.115498), 'test_loss': np.float64(60246.553162), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(18.697357), 'val_loss': np.float64(65814.695898)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(8.723715), 'test_avg_loss_bottom_decile': np.float64(8.715518), 'test_avg_loss_top_decile': np.float64(33.219078), 'test_avg_loss_min': np.float64(8.603796), 'test_avg_loss_max': np.float64(33.219078), 'test_avg_loss_bottom10%': np.float64(8.603796), 'test_avg_loss_top10%': np.float64(33.219078), 'test_avg_loss_cos1': np.float64(0.890945), 'test_avg_loss_entropy': np.float64(2.181518), 'test_loss_std': np.float64(30707.476831), 'test_loss_bottom_decile': np.float64(30678.622437), 'test_loss_top_decile': np.float64(116931.153076), 'test_loss_min': np.float64(30285.361786), 'test_loss_max': np.float64(116931.153076), 'test_loss_bottom10%': np.float64(30285.361786), 'test_loss_top10%': np.float64(116931.153076), 'test_loss_cos1': np.float64(0.890945), 'test_loss_entropy': np.float64(2.181518), 'val_avg_loss_std': np.float64(9.384003), 'val_avg_loss_bottom_decile': np.float64(9.146548), 'val_avg_loss_top_decile': np.float64(36.218152), 'val_avg_loss_min': np.float64(8.776471), 'val_avg_loss_max': np.float64(36.218152), 'val_avg_loss_bottom10%': np.float64(8.776471), 'val_avg_loss_top10%': np.float64(36.218152), 'val_avg_loss_cos1': np.float64(0.893751), 'val_avg_loss_entropy': np.float64(2.182884), 'val_loss_std': np.float64(33031.691648), 'val_loss_bottom_decile': np.float64(32195.848328), 'val_loss_top_decile': np.float64(127487.896362), 'val_loss_min': np.float64(30893.176666), 'val_loss_max': np.float64(127487.896362), 'val_loss_bottom10%': np.float64(30893.176666), 'val_loss_top10%': np.float64(127487.896362), 'val_loss_cos1': np.float64(0.893751), 'val_loss_entropy': np.float64(2.182884)}}
|
|
2024-11-13 14:33:54,661 (server:353) INFO: Server: Starting evaluation at the end of round 18.
|
|
2024-11-13 14:33:54,662 (server:359) INFO: ----------- Starting a new training round (Round #19) -------------
|
|
2024-11-13 14:35:34,787 (client:354) INFO: {'Role': 'Client #3', 'Round': 19, 'Results_raw': {'train_loss': 9.359419, 'val_loss': 8.842983, 'test_loss': 9.309401}}
|
|
2024-11-13 14:36:11,986 (client:354) INFO: {'Role': 'Client #7', 'Round': 19, 'Results_raw': {'train_loss': 11.993192, 'val_loss': 11.732352, 'test_loss': 10.782228}}
|
|
2024-11-13 14:36:48,638 (client:354) INFO: {'Role': 'Client #2', 'Round': 19, 'Results_raw': {'train_loss': 11.729029, 'val_loss': 11.637134, 'test_loss': 10.687955}}
|
|
2024-11-13 14:37:26,540 (client:354) INFO: {'Role': 'Client #4', 'Round': 19, 'Results_raw': {'train_loss': 7.685938, 'val_loss': 6.750124, 'test_loss': 6.825744}}
|
|
2024-11-13 14:38:07,326 (client:354) INFO: {'Role': 'Client #5', 'Round': 19, 'Results_raw': {'train_loss': 6.345507, 'val_loss': 6.179165, 'test_loss': 6.029257}}
|
|
2024-11-13 14:38:46,900 (client:354) INFO: {'Role': 'Client #9', 'Round': 19, 'Results_raw': {'train_loss': 14.886558, 'val_loss': 16.161938, 'test_loss': 12.662605}}
|
|
2024-11-13 14:39:26,459 (client:354) INFO: {'Role': 'Client #10', 'Round': 19, 'Results_raw': {'train_loss': 17.656363, 'val_loss': 17.082114, 'test_loss': 16.481688}}
|
|
2024-11-13 14:40:03,477 (client:354) INFO: {'Role': 'Client #1', 'Round': 19, 'Results_raw': {'train_loss': 9.114698, 'val_loss': 8.352503, 'test_loss': 8.771041}}
|
|
2024-11-13 14:40:43,280 (client:354) INFO: {'Role': 'Client #8', 'Round': 19, 'Results_raw': {'train_loss': 7.99112, 'val_loss': 14.819432, 'test_loss': 8.256619}}
|
|
2024-11-13 14:41:22,793 (client:354) INFO: {'Role': 'Client #6', 'Round': 19, 'Results_raw': {'train_loss': 9.690298, 'val_loss': 9.361991, 'test_loss': 9.315871}}
|
|
2024-11-13 14:41:22,805 (server:615) INFO: {'Role': 'Server #', 'Round': 18, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(17.198361), 'test_loss': np.float64(60538.229248), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(18.755924), 'val_loss': np.float64(66020.852792)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(17.198361), 'test_loss': np.float64(60538.229248), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(18.755924), 'val_loss': np.float64(66020.852792)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(8.916023), 'test_avg_loss_bottom_decile': np.float64(8.7638), 'test_avg_loss_top_decile': np.float64(34.178589), 'test_avg_loss_min': np.float64(8.684777), 'test_avg_loss_max': np.float64(34.178589), 'test_avg_loss_bottom10%': np.float64(8.684777), 'test_avg_loss_top10%': np.float64(34.178589), 'test_avg_loss_cos1': np.float64(0.887789), 'test_avg_loss_entropy': np.float64(2.178529), 'test_loss_std': np.float64(31384.400438), 'test_loss_bottom_decile': np.float64(30848.577026), 'test_loss_top_decile': np.float64(120308.631714), 'test_loss_min': np.float64(30570.41626), 'test_loss_max': np.float64(120308.631714), 'test_loss_bottom10%': np.float64(30570.41626), 'test_loss_top10%': np.float64(120308.631714), 'test_loss_cos1': np.float64(0.887789), 'test_loss_entropy': np.float64(2.178529), 'val_avg_loss_std': np.float64(9.580334), 'val_avg_loss_bottom_decile': np.float64(9.1781), 'val_avg_loss_top_decile': np.float64(36.449326), 'val_avg_loss_min': np.float64(8.86239), 'val_avg_loss_max': np.float64(36.449326), 'val_avg_loss_bottom10%': np.float64(8.86239), 'val_avg_loss_top10%': np.float64(36.449326), 'val_avg_loss_cos1': np.float64(0.890551), 'val_avg_loss_entropy': np.float64(2.179719), 'val_loss_std': np.float64(33722.775432), 'val_loss_bottom_decile': np.float64(32306.912506), 'val_loss_top_decile': np.float64(128301.628845), 'val_loss_min': np.float64(31195.611816), 'val_loss_max': np.float64(128301.628845), 'val_loss_bottom10%': np.float64(31195.611816), 'val_loss_top10%': np.float64(128301.628845), 'val_loss_cos1': np.float64(0.890551), 'val_loss_entropy': np.float64(2.179719)}}
|
|
2024-11-13 14:41:22,847 (server:353) INFO: Server: Starting evaluation at the end of round 19.
|
|
2024-11-13 14:41:22,848 (server:359) INFO: ----------- Starting a new training round (Round #20) -------------
|
|
2024-11-13 14:43:00,197 (client:354) INFO: {'Role': 'Client #3', 'Round': 20, 'Results_raw': {'train_loss': 9.285226, 'val_loss': 8.737754, 'test_loss': 9.225828}}
|
|
2024-11-13 14:43:35,960 (client:354) INFO: {'Role': 'Client #4', 'Round': 20, 'Results_raw': {'train_loss': 7.690399, 'val_loss': 6.710826, 'test_loss': 6.756256}}
|
|
2024-11-13 14:44:13,834 (client:354) INFO: {'Role': 'Client #1', 'Round': 20, 'Results_raw': {'train_loss': 9.083001, 'val_loss': 8.231638, 'test_loss': 8.599895}}
|
|
2024-11-13 14:44:49,285 (client:354) INFO: {'Role': 'Client #5', 'Round': 20, 'Results_raw': {'train_loss': 6.366716, 'val_loss': 6.152573, 'test_loss': 6.110718}}
|
|
2024-11-13 14:45:22,536 (client:354) INFO: {'Role': 'Client #9', 'Round': 20, 'Results_raw': {'train_loss': 13.900804, 'val_loss': 16.513006, 'test_loss': 13.234153}}
|
|
2024-11-13 14:45:56,796 (client:354) INFO: {'Role': 'Client #8', 'Round': 20, 'Results_raw': {'train_loss': 7.916777, 'val_loss': 15.051135, 'test_loss': 8.158095}}
|
|
2024-11-13 14:46:30,108 (client:354) INFO: {'Role': 'Client #7', 'Round': 20, 'Results_raw': {'train_loss': 11.800864, 'val_loss': 11.190437, 'test_loss': 10.380246}}
|
|
2024-11-13 14:47:02,681 (client:354) INFO: {'Role': 'Client #6', 'Round': 20, 'Results_raw': {'train_loss': 9.660907, 'val_loss': 9.10227, 'test_loss': 9.08266}}
|
|
2024-11-13 14:47:36,273 (client:354) INFO: {'Role': 'Client #2', 'Round': 20, 'Results_raw': {'train_loss': 11.578782, 'val_loss': 11.424475, 'test_loss': 10.499986}}
|
|
2024-11-13 14:48:11,578 (client:354) INFO: {'Role': 'Client #10', 'Round': 20, 'Results_raw': {'train_loss': 16.855713, 'val_loss': 16.118319, 'test_loss': 15.57333}}
|
|
2024-11-13 14:48:11,581 (server:615) INFO: {'Role': 'Server #', 'Round': 19, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(17.155179), 'test_loss': np.float64(60386.228525), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(18.716088), 'val_loss': np.float64(65880.630438)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(17.155179), 'test_loss': np.float64(60386.228525), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(18.716088), 'val_loss': np.float64(65880.630438)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(8.943628), 'test_avg_loss_bottom_decile': np.float64(8.70014), 'test_avg_loss_top_decile': np.float64(34.203002), 'test_avg_loss_min': np.float64(8.624678), 'test_avg_loss_max': np.float64(34.203002), 'test_avg_loss_bottom10%': np.float64(8.624678), 'test_avg_loss_top10%': np.float64(34.203002), 'test_avg_loss_cos1': np.float64(0.886731), 'test_avg_loss_entropy': np.float64(2.177189), 'test_loss_std': np.float64(31481.571461), 'test_loss_bottom_decile': np.float64(30624.493683), 'test_loss_top_decile': np.float64(120394.567139), 'test_loss_min': np.float64(30358.865448), 'test_loss_max': np.float64(120394.567139), 'test_loss_bottom10%': np.float64(30358.865448), 'test_loss_top10%': np.float64(120394.567139), 'test_loss_cos1': np.float64(0.886731), 'test_loss_entropy': np.float64(2.177189), 'val_avg_loss_std': np.float64(9.611331), 'val_avg_loss_bottom_decile': np.float64(9.11146), 'val_avg_loss_top_decile': np.float64(36.509708), 'val_avg_loss_min': np.float64(8.803046), 'val_avg_loss_max': np.float64(36.509708), 'val_avg_loss_bottom10%': np.float64(8.803046), 'val_avg_loss_top10%': np.float64(36.509708), 'val_avg_loss_cos1': np.float64(0.88956), 'val_avg_loss_entropy': np.float64(2.178478), 'val_loss_std': np.float64(33831.885421), 'val_loss_bottom_decile': np.float64(32072.338257), 'val_loss_top_decile': np.float64(128514.171814), 'val_loss_min': np.float64(30986.720886), 'val_loss_max': np.float64(128514.171814), 'val_loss_bottom10%': np.float64(30986.720886), 'val_loss_top10%': np.float64(128514.171814), 'val_loss_cos1': np.float64(0.88956), 'val_loss_entropy': np.float64(2.178478)}}
|
|
2024-11-13 14:48:11,611 (server:353) INFO: Server: Starting evaluation at the end of round 20.
|
|
2024-11-13 14:48:11,611 (server:359) INFO: ----------- Starting a new training round (Round #21) -------------
|
|
2024-11-13 14:49:43,821 (client:354) INFO: {'Role': 'Client #5', 'Round': 21, 'Results_raw': {'train_loss': 6.296818, 'val_loss': 6.228672, 'test_loss': 6.204889}}
|
|
2024-11-13 14:50:17,737 (client:354) INFO: {'Role': 'Client #3', 'Round': 21, 'Results_raw': {'train_loss': 9.255912, 'val_loss': 8.746986, 'test_loss': 9.251735}}
|
|
2024-11-13 14:50:51,618 (client:354) INFO: {'Role': 'Client #6', 'Round': 21, 'Results_raw': {'train_loss': 9.549366, 'val_loss': 9.623344, 'test_loss': 9.557464}}
|
|
2024-11-13 14:51:26,441 (client:354) INFO: {'Role': 'Client #9', 'Round': 21, 'Results_raw': {'train_loss': 14.111804, 'val_loss': 15.689106, 'test_loss': 12.22077}}
|
|
2024-11-13 14:52:00,107 (client:354) INFO: {'Role': 'Client #4', 'Round': 21, 'Results_raw': {'train_loss': 7.671685, 'val_loss': 6.727642, 'test_loss': 6.720358}}
|
|
2024-11-13 14:52:34,030 (client:354) INFO: {'Role': 'Client #1', 'Round': 21, 'Results_raw': {'train_loss': 9.094577, 'val_loss': 8.277124, 'test_loss': 8.60747}}
|
|
2024-11-13 14:53:08,683 (client:354) INFO: {'Role': 'Client #7', 'Round': 21, 'Results_raw': {'train_loss': 11.745849, 'val_loss': 11.453294, 'test_loss': 10.70871}}
|
|
2024-11-13 14:53:43,064 (client:354) INFO: {'Role': 'Client #2', 'Round': 21, 'Results_raw': {'train_loss': 11.693197, 'val_loss': 11.123973, 'test_loss': 10.302778}}
|
|
2024-11-13 14:54:17,283 (client:354) INFO: {'Role': 'Client #10', 'Round': 21, 'Results_raw': {'train_loss': 16.697224, 'val_loss': 16.285577, 'test_loss': 15.922381}}
|
|
2024-11-13 14:54:51,377 (client:354) INFO: {'Role': 'Client #8', 'Round': 21, 'Results_raw': {'train_loss': 7.873046, 'val_loss': 14.880292, 'test_loss': 8.095128}}
|
|
2024-11-13 14:54:51,380 (server:615) INFO: {'Role': 'Server #', 'Round': 20, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.887318), 'test_loss': np.float64(59443.358176), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(18.397752), 'val_loss': np.float64(64760.088181)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.887318), 'test_loss': np.float64(59443.358176), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(18.397752), 'val_loss': np.float64(64760.088181)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(8.607341), 'test_avg_loss_bottom_decile': np.float64(8.71319), 'test_avg_loss_top_decile': np.float64(33.805945), 'test_avg_loss_min': np.float64(8.559161), 'test_avg_loss_max': np.float64(33.805945), 'test_avg_loss_bottom10%': np.float64(8.559161), 'test_avg_loss_top10%': np.float64(33.805945), 'test_avg_loss_cos1': np.float64(0.890946), 'test_avg_loss_entropy': np.float64(2.182736), 'test_loss_std': np.float64(30297.839823), 'test_loss_bottom_decile': np.float64(30670.429321), 'test_loss_top_decile': np.float64(118996.926453), 'test_loss_min': np.float64(30128.248383), 'test_loss_max': np.float64(118996.926453), 'test_loss_bottom10%': np.float64(30128.248383), 'test_loss_top10%': np.float64(118996.926453), 'test_loss_cos1': np.float64(0.890946), 'test_loss_entropy': np.float64(2.182736), 'val_avg_loss_std': np.float64(9.227641), 'val_avg_loss_bottom_decile': np.float64(9.127756), 'val_avg_loss_top_decile': np.float64(34.985744), 'val_avg_loss_min': np.float64(8.730938), 'val_avg_loss_max': np.float64(34.985744), 'val_avg_loss_bottom10%': np.float64(8.730938), 'val_avg_loss_top10%': np.float64(34.985744), 'val_avg_loss_cos1': np.float64(0.893867), 'val_avg_loss_entropy': np.float64(2.183898), 'val_loss_std': np.float64(32481.296764), 'val_loss_bottom_decile': np.float64(32129.69989), 'val_loss_top_decile': np.float64(123149.820129), 'val_loss_min': np.float64(30732.902649), 'val_loss_max': np.float64(123149.820129), 'val_loss_bottom10%': np.float64(30732.902649), 'val_loss_top10%': np.float64(123149.820129), 'val_loss_cos1': np.float64(0.893867), 'val_loss_entropy': np.float64(2.183898)}}
|
|
2024-11-13 14:54:51,419 (server:353) INFO: Server: Starting evaluation at the end of round 21.
|
|
2024-11-13 14:54:51,419 (server:359) INFO: ----------- Starting a new training round (Round #22) -------------
|
|
2024-11-13 14:56:24,332 (client:354) INFO: {'Role': 'Client #4', 'Round': 22, 'Results_raw': {'train_loss': 7.651044, 'val_loss': 6.783534, 'test_loss': 6.847526}}
|
|
2024-11-13 14:56:57,044 (client:354) INFO: {'Role': 'Client #8', 'Round': 22, 'Results_raw': {'train_loss': 7.826954, 'val_loss': 13.668605, 'test_loss': 8.085353}}
|
|
2024-11-13 14:57:29,704 (client:354) INFO: {'Role': 'Client #2', 'Round': 22, 'Results_raw': {'train_loss': 11.581394, 'val_loss': 11.497665, 'test_loss': 10.57383}}
|
|
2024-11-13 14:58:02,382 (client:354) INFO: {'Role': 'Client #6', 'Round': 22, 'Results_raw': {'train_loss': 9.660317, 'val_loss': 9.123472, 'test_loss': 9.055727}}
|
|
2024-11-13 14:58:35,151 (client:354) INFO: {'Role': 'Client #3', 'Round': 22, 'Results_raw': {'train_loss': 9.26503, 'val_loss': 8.774005, 'test_loss': 9.233565}}
|
|
2024-11-13 14:59:07,566 (client:354) INFO: {'Role': 'Client #10', 'Round': 22, 'Results_raw': {'train_loss': 16.46107, 'val_loss': 16.403265, 'test_loss': 15.877553}}
|
|
2024-11-13 14:59:40,411 (client:354) INFO: {'Role': 'Client #1', 'Round': 22, 'Results_raw': {'train_loss': 9.051702, 'val_loss': 8.372028, 'test_loss': 8.737189}}
|
|
2024-11-13 15:00:13,094 (client:354) INFO: {'Role': 'Client #9', 'Round': 22, 'Results_raw': {'train_loss': 14.611553, 'val_loss': 15.501227, 'test_loss': 11.901562}}
|
|
2024-11-13 15:00:45,786 (client:354) INFO: {'Role': 'Client #7', 'Round': 22, 'Results_raw': {'train_loss': 11.751997, 'val_loss': 11.404784, 'test_loss': 10.564884}}
|
|
2024-11-13 15:01:18,903 (client:354) INFO: {'Role': 'Client #5', 'Round': 22, 'Results_raw': {'train_loss': 6.257017, 'val_loss': 6.49215, 'test_loss': 6.491875}}
|
|
2024-11-13 15:01:18,913 (server:615) INFO: {'Role': 'Server #', 'Round': 21, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.896736), 'test_loss': np.float64(59476.51149), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(18.404477), 'val_loss': np.float64(64783.757971)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.896736), 'test_loss': np.float64(59476.51149), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(18.404477), 'val_loss': np.float64(64783.757971)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(8.635921), 'test_avg_loss_bottom_decile': np.float64(8.700432), 'test_avg_loss_top_decile': np.float64(33.673415), 'test_avg_loss_min': np.float64(8.603063), 'test_avg_loss_max': np.float64(33.673415), 'test_avg_loss_bottom10%': np.float64(8.603063), 'test_avg_loss_top10%': np.float64(33.673415), 'test_avg_loss_cos1': np.float64(0.890439), 'test_avg_loss_entropy': np.float64(2.182045), 'test_loss_std': np.float64(30398.443639), 'test_loss_bottom_decile': np.float64(30625.52179), 'test_loss_top_decile': np.float64(118530.420959), 'test_loss_min': np.float64(30282.780487), 'test_loss_max': np.float64(118530.420959), 'test_loss_bottom10%': np.float64(30282.780487), 'test_loss_top10%': np.float64(118530.420959), 'test_loss_cos1': np.float64(0.890439), 'test_loss_entropy': np.float64(2.182045), 'val_avg_loss_std': np.float64(9.259459), 'val_avg_loss_bottom_decile': np.float64(9.091071), 'val_avg_loss_top_decile': np.float64(35.292823), 'val_avg_loss_min': np.float64(8.78143), 'val_avg_loss_max': np.float64(35.292823), 'val_avg_loss_bottom10%': np.float64(8.78143), 'val_avg_loss_top10%': np.float64(35.292823), 'val_avg_loss_cos1': np.float64(0.893313), 'val_avg_loss_entropy': np.float64(2.183256), 'val_loss_std': np.float64(32593.295281), 'val_loss_bottom_decile': np.float64(32000.570892), 'val_loss_top_decile': np.float64(124230.737366), 'val_loss_min': np.float64(30910.634491), 'val_loss_max': np.float64(124230.737366), 'val_loss_bottom10%': np.float64(30910.634491), 'val_loss_top10%': np.float64(124230.737366), 'val_loss_cos1': np.float64(0.893313), 'val_loss_entropy': np.float64(2.183256)}}
|
|
2024-11-13 15:01:18,943 (server:353) INFO: Server: Starting evaluation at the end of round 22.
|
|
2024-11-13 15:01:18,943 (server:359) INFO: ----------- Starting a new training round (Round #23) -------------
|
|
2024-11-13 15:02:49,641 (client:354) INFO: {'Role': 'Client #5', 'Round': 23, 'Results_raw': {'train_loss': 6.254685, 'val_loss': 6.128396, 'test_loss': 6.041757}}
|
|
2024-11-13 15:03:22,306 (client:354) INFO: {'Role': 'Client #6', 'Round': 23, 'Results_raw': {'train_loss': 9.461014, 'val_loss': 9.138559, 'test_loss': 9.109187}}
|
|
2024-11-13 15:03:54,424 (client:354) INFO: {'Role': 'Client #9', 'Round': 23, 'Results_raw': {'train_loss': 13.797371, 'val_loss': 15.773308, 'test_loss': 12.261055}}
|
|
2024-11-13 15:04:28,664 (client:354) INFO: {'Role': 'Client #1', 'Round': 23, 'Results_raw': {'train_loss': 9.014775, 'val_loss': 8.353353, 'test_loss': 8.745228}}
|
|
2024-11-13 15:05:02,623 (client:354) INFO: {'Role': 'Client #8', 'Round': 23, 'Results_raw': {'train_loss': 7.835448, 'val_loss': 15.401214, 'test_loss': 8.158025}}
|
|
2024-11-13 15:05:40,173 (client:354) INFO: {'Role': 'Client #3', 'Round': 23, 'Results_raw': {'train_loss': 9.187688, 'val_loss': 8.716248, 'test_loss': 9.221964}}
|
|
2024-11-13 15:06:26,070 (client:354) INFO: {'Role': 'Client #4', 'Round': 23, 'Results_raw': {'train_loss': 7.616271, 'val_loss': 6.731382, 'test_loss': 6.733328}}
|
|
2024-11-13 15:07:25,119 (client:354) INFO: {'Role': 'Client #7', 'Round': 23, 'Results_raw': {'train_loss': 11.627889, 'val_loss': 11.173643, 'test_loss': 10.31825}}
|
|
2024-11-13 15:08:29,751 (client:354) INFO: {'Role': 'Client #10', 'Round': 23, 'Results_raw': {'train_loss': 16.878098, 'val_loss': 16.285661, 'test_loss': 15.731599}}
|
|
2024-11-13 15:09:32,173 (client:354) INFO: {'Role': 'Client #2', 'Round': 23, 'Results_raw': {'train_loss': 11.556963, 'val_loss': 11.271453, 'test_loss': 10.32042}}
|
|
2024-11-13 15:09:32,177 (server:615) INFO: {'Role': 'Server #', 'Round': 22, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.614048), 'test_loss': np.float64(58481.449759), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(18.071341), 'val_loss': np.float64(63611.121848)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.614048), 'test_loss': np.float64(58481.449759), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(18.071341), 'val_loss': np.float64(63611.121848)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(8.268035), 'test_avg_loss_bottom_decile': np.float64(8.681413), 'test_avg_loss_top_decile': np.float64(32.496275), 'test_avg_loss_min': np.float64(8.568086), 'test_avg_loss_max': np.float64(32.496275), 'test_avg_loss_bottom10%': np.float64(8.568086), 'test_avg_loss_top10%': np.float64(32.496275), 'test_avg_loss_cos1': np.float64(0.895266), 'test_avg_loss_entropy': np.float64(2.187939), 'test_loss_std': np.float64(29103.481635), 'test_loss_bottom_decile': np.float64(30558.573547), 'test_loss_top_decile': np.float64(114386.887573), 'test_loss_min': np.float64(30159.66098), 'test_loss_max': np.float64(114386.887573), 'test_loss_bottom10%': np.float64(30159.66098), 'test_loss_top10%': np.float64(114386.887573), 'test_loss_cos1': np.float64(0.895266), 'test_loss_entropy': np.float64(2.187939), 'val_avg_loss_std': np.float64(8.861526), 'val_avg_loss_bottom_decile': np.float64(9.088182), 'val_avg_loss_top_decile': np.float64(34.396713), 'val_avg_loss_min': np.float64(8.749339), 'val_avg_loss_max': np.float64(34.396713), 'val_avg_loss_bottom10%': np.float64(8.749339), 'val_avg_loss_top10%': np.float64(34.396713), 'val_avg_loss_cos1': np.float64(0.897861), 'val_avg_loss_entropy': np.float64(2.188923), 'val_loss_std': np.float64(31192.572591), 'val_loss_bottom_decile': np.float64(31990.40033), 'val_loss_top_decile': np.float64(121076.428894), 'val_loss_min': np.float64(30797.673859), 'val_loss_max': np.float64(121076.428894), 'val_loss_bottom10%': np.float64(30797.673859), 'val_loss_top10%': np.float64(121076.428894), 'val_loss_cos1': np.float64(0.897861), 'val_loss_entropy': np.float64(2.188923)}}
|
|
2024-11-13 15:09:32,220 (server:353) INFO: Server: Starting evaluation at the end of round 23.
|
|
2024-11-13 15:09:32,220 (server:359) INFO: ----------- Starting a new training round (Round #24) -------------
|
|
2024-11-13 15:12:44,383 (client:354) INFO: {'Role': 'Client #4', 'Round': 24, 'Results_raw': {'train_loss': 7.564281, 'val_loss': 6.746011, 'test_loss': 6.792678}}
|
|
2024-11-13 15:13:46,959 (client:354) INFO: {'Role': 'Client #2', 'Round': 24, 'Results_raw': {'train_loss': 11.584315, 'val_loss': 11.250105, 'test_loss': 10.49634}}
|
|
2024-11-13 15:14:51,033 (client:354) INFO: {'Role': 'Client #10', 'Round': 24, 'Results_raw': {'train_loss': 16.634706, 'val_loss': 16.778296, 'test_loss': 16.222479}}
|
|
2024-11-13 15:15:53,725 (client:354) INFO: {'Role': 'Client #6', 'Round': 24, 'Results_raw': {'train_loss': 9.464963, 'val_loss': 9.168394, 'test_loss': 9.142184}}
|
|
2024-11-13 15:16:55,999 (client:354) INFO: {'Role': 'Client #9', 'Round': 24, 'Results_raw': {'train_loss': 14.043717, 'val_loss': 16.678989, 'test_loss': 13.062174}}
|
|
2024-11-13 15:17:59,128 (client:354) INFO: {'Role': 'Client #8', 'Round': 24, 'Results_raw': {'train_loss': 7.777682, 'val_loss': 14.484985, 'test_loss': 8.132196}}
|
|
2024-11-13 15:19:01,926 (client:354) INFO: {'Role': 'Client #3', 'Round': 24, 'Results_raw': {'train_loss': 9.200076, 'val_loss': 8.78149, 'test_loss': 9.218192}}
|
|
2024-11-13 15:20:03,634 (client:354) INFO: {'Role': 'Client #7', 'Round': 24, 'Results_raw': {'train_loss': 11.730314, 'val_loss': 11.175954, 'test_loss': 10.342353}}
|
|
2024-11-13 15:21:05,065 (client:354) INFO: {'Role': 'Client #1', 'Round': 24, 'Results_raw': {'train_loss': 9.014615, 'val_loss': 8.221831, 'test_loss': 8.624006}}
|
|
2024-11-13 15:22:08,897 (client:354) INFO: {'Role': 'Client #5', 'Round': 24, 'Results_raw': {'train_loss': 6.217664, 'val_loss': 6.096124, 'test_loss': 5.947062}}
|
|
2024-11-13 15:22:08,901 (server:615) INFO: {'Role': 'Server #', 'Round': 23, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.719838), 'test_loss': np.float64(58853.830447), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(18.186168), 'val_loss': np.float64(64015.311191)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.719838), 'test_loss': np.float64(58853.830447), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(18.186168), 'val_loss': np.float64(64015.311191)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(8.470564), 'test_avg_loss_bottom_decile': np.float64(8.622457), 'test_avg_loss_top_decile': np.float64(32.997286), 'test_avg_loss_min': np.float64(8.533236), 'test_avg_loss_max': np.float64(32.997286), 'test_avg_loss_bottom10%': np.float64(8.533236), 'test_avg_loss_top10%': np.float64(32.997286), 'test_avg_loss_cos1': np.float64(0.892053), 'test_avg_loss_entropy': np.float64(2.18386), 'test_loss_std': np.float64(29816.386373), 'test_loss_bottom_decile': np.float64(30351.047028), 'test_loss_top_decile': np.float64(116150.445984), 'test_loss_min': np.float64(30036.991241), 'test_loss_max': np.float64(116150.445984), 'test_loss_bottom10%': np.float64(30036.991241), 'test_loss_top10%': np.float64(116150.445984), 'test_loss_cos1': np.float64(0.892053), 'test_loss_entropy': np.float64(2.18386), 'val_avg_loss_std': np.float64(9.053354), 'val_avg_loss_bottom_decile': np.float64(9.037424), 'val_avg_loss_top_decile': np.float64(34.802792), 'val_avg_loss_min': np.float64(8.706047), 'val_avg_loss_max': np.float64(34.802792), 'val_avg_loss_bottom10%': np.float64(8.706047), 'val_avg_loss_top10%': np.float64(34.802792), 'val_avg_loss_cos1': np.float64(0.895208), 'val_avg_loss_entropy': np.float64(2.185524), 'val_loss_std': np.float64(31867.804642), 'val_loss_bottom_decile': np.float64(31811.731964), 'val_loss_top_decile': np.float64(122505.828308), 'val_loss_min': np.float64(30645.285797), 'val_loss_max': np.float64(122505.828308), 'val_loss_bottom10%': np.float64(30645.285797), 'val_loss_top10%': np.float64(122505.828308), 'val_loss_cos1': np.float64(0.895208), 'val_loss_entropy': np.float64(2.185524)}}
|
|
2024-11-13 15:22:08,940 (server:353) INFO: Server: Starting evaluation at the end of round 24.
|
|
2024-11-13 15:22:08,940 (server:359) INFO: ----------- Starting a new training round (Round #25) -------------
|
|
2024-11-13 15:25:14,196 (client:354) INFO: {'Role': 'Client #5', 'Round': 25, 'Results_raw': {'train_loss': 6.208561, 'val_loss': 6.201135, 'test_loss': 6.195825}}
|
|
2024-11-13 15:26:11,910 (client:354) INFO: {'Role': 'Client #2', 'Round': 25, 'Results_raw': {'train_loss': 11.309558, 'val_loss': 11.42662, 'test_loss': 10.545675}}
|
|
2024-11-13 15:27:11,002 (client:354) INFO: {'Role': 'Client #4', 'Round': 25, 'Results_raw': {'train_loss': 7.598801, 'val_loss': 6.948337, 'test_loss': 7.035796}}
|
|
2024-11-13 15:28:09,246 (client:354) INFO: {'Role': 'Client #8', 'Round': 25, 'Results_raw': {'train_loss': 7.748671, 'val_loss': 15.821351, 'test_loss': 8.255848}}
|
|
2024-11-13 15:29:07,724 (client:354) INFO: {'Role': 'Client #10', 'Round': 25, 'Results_raw': {'train_loss': 16.199433, 'val_loss': 15.483418, 'test_loss': 15.274094}}
|
|
2024-11-13 15:30:08,017 (client:354) INFO: {'Role': 'Client #3', 'Round': 25, 'Results_raw': {'train_loss': 9.228521, 'val_loss': 8.788971, 'test_loss': 9.239928}}
|
|
2024-11-13 15:31:07,053 (client:354) INFO: {'Role': 'Client #9', 'Round': 25, 'Results_raw': {'train_loss': 14.387414, 'val_loss': 15.400262, 'test_loss': 11.950355}}
|
|
2024-11-13 15:32:06,496 (client:354) INFO: {'Role': 'Client #1', 'Round': 25, 'Results_raw': {'train_loss': 8.967555, 'val_loss': 8.219883, 'test_loss': 8.640577}}
|
|
2024-11-13 15:33:04,553 (client:354) INFO: {'Role': 'Client #6', 'Round': 25, 'Results_raw': {'train_loss': 9.346916, 'val_loss': 9.022285, 'test_loss': 9.049151}}
|
|
2024-11-13 15:34:03,514 (client:354) INFO: {'Role': 'Client #7', 'Round': 25, 'Results_raw': {'train_loss': 11.567081, 'val_loss': 11.328138, 'test_loss': 10.429635}}
|
|
2024-11-13 15:34:03,519 (server:615) INFO: {'Role': 'Server #', 'Round': 24, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.405242), 'test_loss': np.float64(57746.452469), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.815067), 'val_loss': np.float64(62709.035147)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.405242), 'test_loss': np.float64(57746.452469), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.815067), 'val_loss': np.float64(62709.035147)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(8.174914), 'test_avg_loss_bottom_decile': np.float64(8.594265), 'test_avg_loss_top_decile': np.float64(32.502747), 'test_avg_loss_min': np.float64(8.458103), 'test_avg_loss_max': np.float64(32.502747), 'test_avg_loss_bottom10%': np.float64(8.458103), 'test_avg_loss_top10%': np.float64(32.502747), 'test_avg_loss_cos1': np.float64(0.895031), 'test_avg_loss_entropy': np.float64(2.187914), 'test_loss_std': np.float64(28775.697448), 'test_loss_bottom_decile': np.float64(30251.813141), 'test_loss_top_decile': np.float64(114409.670044), 'test_loss_min': np.float64(29772.521545), 'test_loss_max': np.float64(114409.670044), 'test_loss_bottom10%': np.float64(29772.521545), 'test_loss_top10%': np.float64(114409.670044), 'test_loss_cos1': np.float64(0.895031), 'test_loss_entropy': np.float64(2.187914), 'val_avg_loss_std': np.float64(8.727643), 'val_avg_loss_bottom_decile': np.float64(9.014658), 'val_avg_loss_top_decile': np.float64(33.583435), 'val_avg_loss_min': np.float64(8.623709), 'val_avg_loss_max': np.float64(33.583435), 'val_avg_loss_bottom10%': np.float64(8.623709), 'val_avg_loss_top10%': np.float64(33.583435), 'val_avg_loss_cos1': np.float64(0.898025), 'val_avg_loss_entropy': np.float64(2.189297), 'val_loss_std': np.float64(30721.303474), 'val_loss_bottom_decile': np.float64(31731.595245), 'val_loss_top_decile': np.float64(118213.691406), 'val_loss_min': np.float64(30355.45575), 'val_loss_max': np.float64(118213.691406), 'val_loss_bottom10%': np.float64(30355.45575), 'val_loss_top10%': np.float64(118213.691406), 'val_loss_cos1': np.float64(0.898025), 'val_loss_entropy': np.float64(2.189297)}}
|
|
2024-11-13 15:34:03,555 (server:353) INFO: Server: Starting evaluation at the end of round 25.
|
|
2024-11-13 15:34:03,556 (server:359) INFO: ----------- Starting a new training round (Round #26) -------------
|
|
2024-11-13 15:37:03,399 (client:354) INFO: {'Role': 'Client #8', 'Round': 26, 'Results_raw': {'train_loss': 7.747761, 'val_loss': 14.610786, 'test_loss': 7.953567}}
|
|
2024-11-13 15:38:05,499 (client:354) INFO: {'Role': 'Client #9', 'Round': 26, 'Results_raw': {'train_loss': 13.961239, 'val_loss': 15.873349, 'test_loss': 12.348451}}
|
|
2024-11-13 15:39:04,802 (client:354) INFO: {'Role': 'Client #7', 'Round': 26, 'Results_raw': {'train_loss': 11.669081, 'val_loss': 11.163263, 'test_loss': 10.274624}}
|
|
2024-11-13 15:40:01,848 (client:354) INFO: {'Role': 'Client #10', 'Round': 26, 'Results_raw': {'train_loss': 15.932834, 'val_loss': 15.596142, 'test_loss': 15.017088}}
|
|
2024-11-13 15:40:59,276 (client:354) INFO: {'Role': 'Client #2', 'Round': 26, 'Results_raw': {'train_loss': 11.289541, 'val_loss': 11.334468, 'test_loss': 10.616286}}
|
|
2024-11-13 15:41:59,225 (client:354) INFO: {'Role': 'Client #5', 'Round': 26, 'Results_raw': {'train_loss': 6.177338, 'val_loss': 6.099255, 'test_loss': 6.039796}}
|
|
2024-11-13 15:42:59,443 (client:354) INFO: {'Role': 'Client #1', 'Round': 26, 'Results_raw': {'train_loss': 8.980258, 'val_loss': 8.186532, 'test_loss': 8.636211}}
|
|
2024-11-13 15:43:58,704 (client:354) INFO: {'Role': 'Client #6', 'Round': 26, 'Results_raw': {'train_loss': 9.362703, 'val_loss': 8.937685, 'test_loss': 8.941773}}
|
|
2024-11-13 15:44:57,936 (client:354) INFO: {'Role': 'Client #4', 'Round': 26, 'Results_raw': {'train_loss': 7.528158, 'val_loss': 6.713134, 'test_loss': 6.69986}}
|
|
2024-11-13 15:45:56,140 (client:354) INFO: {'Role': 'Client #3', 'Round': 26, 'Results_raw': {'train_loss': 9.19454, 'val_loss': 8.733732, 'test_loss': 9.238823}}
|
|
2024-11-13 15:45:56,144 (server:615) INFO: {'Role': 'Server #', 'Round': 25, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(17.240379), 'test_loss': np.float64(60686.133612), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(18.705677), 'val_loss': np.float64(65843.981644)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(17.240379), 'test_loss': np.float64(60686.133612), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(18.705677), 'val_loss': np.float64(65843.981644)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(9.141346), 'test_avg_loss_bottom_decile': np.float64(8.601059), 'test_avg_loss_top_decile': np.float64(34.950073), 'test_avg_loss_min': np.float64(8.580635), 'test_avg_loss_max': np.float64(34.950073), 'test_avg_loss_bottom10%': np.float64(8.580635), 'test_avg_loss_top10%': np.float64(34.950073), 'test_avg_loss_cos1': np.float64(0.883489), 'test_avg_loss_entropy': np.float64(2.173014), 'test_loss_std': np.float64(32177.538889), 'test_loss_bottom_decile': np.float64(30275.728485), 'test_loss_top_decile': np.float64(123024.256531), 'test_loss_min': np.float64(30203.833954), 'test_loss_max': np.float64(123024.256531), 'test_loss_bottom10%': np.float64(30203.833954), 'test_loss_top10%': np.float64(123024.256531), 'test_loss_cos1': np.float64(0.883489), 'test_loss_entropy': np.float64(2.173014), 'val_avg_loss_std': np.float64(9.724743), 'val_avg_loss_bottom_decile': np.float64(9.015956), 'val_avg_loss_top_decile': np.float64(36.494984), 'val_avg_loss_min': np.float64(8.771966), 'val_avg_loss_max': np.float64(36.494984), 'val_avg_loss_bottom10%': np.float64(8.771966), 'val_avg_loss_top10%': np.float64(36.494984), 'val_avg_loss_cos1': np.float64(0.88726), 'val_avg_loss_entropy': np.float64(2.175683), 'val_loss_std': np.float64(34231.095609), 'val_loss_bottom_decile': np.float64(31736.165192), 'val_loss_top_decile': np.float64(128462.344849), 'val_loss_min': np.float64(30877.321228), 'val_loss_max': np.float64(128462.344849), 'val_loss_bottom10%': np.float64(30877.321228), 'val_loss_top10%': np.float64(128462.344849), 'val_loss_cos1': np.float64(0.88726), 'val_loss_entropy': np.float64(2.175683)}}
|
|
2024-11-13 15:45:56,181 (server:353) INFO: Server: Starting evaluation at the end of round 26.
|
|
2024-11-13 15:45:56,182 (server:359) INFO: ----------- Starting a new training round (Round #27) -------------
|
|
2024-11-13 15:48:53,994 (client:354) INFO: {'Role': 'Client #9', 'Round': 27, 'Results_raw': {'train_loss': 13.623622, 'val_loss': 16.080346, 'test_loss': 12.519407}}
|
|
2024-11-13 15:49:50,683 (client:354) INFO: {'Role': 'Client #8', 'Round': 27, 'Results_raw': {'train_loss': 7.70466, 'val_loss': 14.966824, 'test_loss': 8.052634}}
|
|
2024-11-13 15:50:47,378 (client:354) INFO: {'Role': 'Client #4', 'Round': 27, 'Results_raw': {'train_loss': 7.580532, 'val_loss': 6.707642, 'test_loss': 6.783338}}
|
|
2024-11-13 15:51:47,193 (client:354) INFO: {'Role': 'Client #1', 'Round': 27, 'Results_raw': {'train_loss': 8.946684, 'val_loss': 8.181788, 'test_loss': 8.559962}}
|
|
2024-11-13 15:52:48,405 (client:354) INFO: {'Role': 'Client #2', 'Round': 27, 'Results_raw': {'train_loss': 11.092432, 'val_loss': 11.2955, 'test_loss': 10.600309}}
|
|
2024-11-13 15:53:48,921 (client:354) INFO: {'Role': 'Client #3', 'Round': 27, 'Results_raw': {'train_loss': 9.163247, 'val_loss': 8.844565, 'test_loss': 9.286606}}
|
|
2024-11-13 15:54:48,907 (client:354) INFO: {'Role': 'Client #7', 'Round': 27, 'Results_raw': {'train_loss': 11.505233, 'val_loss': 11.177571, 'test_loss': 10.335327}}
|
|
2024-11-13 15:55:47,808 (client:354) INFO: {'Role': 'Client #10', 'Round': 27, 'Results_raw': {'train_loss': 16.118228, 'val_loss': 15.698011, 'test_loss': 15.348493}}
|
|
2024-11-13 15:56:46,017 (client:354) INFO: {'Role': 'Client #6', 'Round': 27, 'Results_raw': {'train_loss': 9.437173, 'val_loss': 8.917998, 'test_loss': 8.868031}}
|
|
2024-11-13 15:57:31,716 (client:354) INFO: {'Role': 'Client #5', 'Round': 27, 'Results_raw': {'train_loss': 6.152576, 'val_loss': 6.124441, 'test_loss': 6.128292}}
|
|
2024-11-13 15:57:31,720 (server:615) INFO: {'Role': 'Server #', 'Round': 26, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.673518), 'test_loss': np.float64(58690.783936), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(18.082726), 'val_loss': np.float64(63651.197104)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.673518), 'test_loss': np.float64(58690.783936), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(18.082726), 'val_loss': np.float64(63651.197104)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(8.497518), 'test_avg_loss_bottom_decile': np.float64(8.570169), 'test_avg_loss_top_decile': np.float64(33.391924), 'test_avg_loss_min': np.float64(8.538767), 'test_avg_loss_max': np.float64(33.391924), 'test_avg_loss_bottom10%': np.float64(8.538767), 'test_avg_loss_top10%': np.float64(33.391924), 'test_avg_loss_cos1': np.float64(0.890965), 'test_avg_loss_entropy': np.float64(2.182848), 'test_loss_std': np.float64(29911.263853), 'test_loss_bottom_decile': np.float64(30166.99472), 'test_loss_top_decile': np.float64(117539.573364), 'test_loss_min': np.float64(30056.459991), 'test_loss_max': np.float64(117539.573364), 'test_loss_bottom10%': np.float64(30056.459991), 'test_loss_top10%': np.float64(117539.573364), 'test_loss_cos1': np.float64(0.890965), 'test_loss_entropy': np.float64(2.182848), 'val_avg_loss_std': np.float64(9.037362), 'val_avg_loss_bottom_decile': np.float64(8.967194), 'val_avg_loss_top_decile': np.float64(34.353943), 'val_avg_loss_min': np.float64(8.709555), 'val_avg_loss_max': np.float64(34.353943), 'val_avg_loss_bottom10%': np.float64(8.709555), 'val_avg_loss_top10%': np.float64(34.353943), 'val_avg_loss_cos1': np.float64(0.894506), 'val_avg_loss_entropy': np.float64(2.184895), 'val_loss_std': np.float64(31811.512605), 'val_loss_bottom_decile': np.float64(31564.524567), 'val_loss_top_decile': np.float64(120925.878662), 'val_loss_min': np.float64(30657.63205), 'val_loss_max': np.float64(120925.878662), 'val_loss_bottom10%': np.float64(30657.63205), 'val_loss_top10%': np.float64(120925.878662), 'val_loss_cos1': np.float64(0.894506), 'val_loss_entropy': np.float64(2.184895)}}
|
|
2024-11-13 15:57:31,757 (server:353) INFO: Server: Starting evaluation at the end of round 27.
|
|
2024-11-13 15:57:31,758 (server:359) INFO: ----------- Starting a new training round (Round #28) -------------
|
|
2024-11-13 15:59:32,371 (client:354) INFO: {'Role': 'Client #8', 'Round': 28, 'Results_raw': {'train_loss': 7.728658, 'val_loss': 15.159105, 'test_loss': 8.061118}}
|
|
2024-11-13 16:00:17,927 (client:354) INFO: {'Role': 'Client #9', 'Round': 28, 'Results_raw': {'train_loss': 13.808992, 'val_loss': 15.427245, 'test_loss': 11.918562}}
|
|
2024-11-13 16:01:01,978 (client:354) INFO: {'Role': 'Client #3', 'Round': 28, 'Results_raw': {'train_loss': 9.180491, 'val_loss': 8.64956, 'test_loss': 9.139895}}
|
|
2024-11-13 16:01:48,135 (client:354) INFO: {'Role': 'Client #4', 'Round': 28, 'Results_raw': {'train_loss': 7.51458, 'val_loss': 6.611378, 'test_loss': 6.630803}}
|
|
2024-11-13 16:02:33,207 (client:354) INFO: {'Role': 'Client #6', 'Round': 28, 'Results_raw': {'train_loss': 9.319142, 'val_loss': 9.024742, 'test_loss': 9.047594}}
|
|
2024-11-13 16:03:17,502 (client:354) INFO: {'Role': 'Client #1', 'Round': 28, 'Results_raw': {'train_loss': 8.937695, 'val_loss': 8.190086, 'test_loss': 8.568453}}
|
|
2024-11-13 16:04:02,471 (client:354) INFO: {'Role': 'Client #2', 'Round': 28, 'Results_raw': {'train_loss': 11.412192, 'val_loss': 10.816334, 'test_loss': 10.032337}}
|
|
2024-11-13 16:04:48,193 (client:354) INFO: {'Role': 'Client #10', 'Round': 28, 'Results_raw': {'train_loss': 15.558329, 'val_loss': 15.803737, 'test_loss': 15.385491}}
|
|
2024-11-13 16:05:35,217 (client:354) INFO: {'Role': 'Client #7', 'Round': 28, 'Results_raw': {'train_loss': 11.825532, 'val_loss': 11.223063, 'test_loss': 10.365704}}
|
|
2024-11-13 16:06:21,014 (client:354) INFO: {'Role': 'Client #5', 'Round': 28, 'Results_raw': {'train_loss': 6.112692, 'val_loss': 6.163312, 'test_loss': 5.969074}}
|
|
2024-11-13 16:06:21,017 (server:615) INFO: {'Role': 'Server #', 'Round': 27, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.513736), 'test_loss': np.float64(58128.349283), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.905397), 'val_loss': np.float64(63026.996323)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.513736), 'test_loss': np.float64(58128.349283), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.905397), 'val_loss': np.float64(63026.996323)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(8.304859), 'test_avg_loss_bottom_decile': np.float64(8.560896), 'test_avg_loss_top_decile': np.float64(33.015446), 'test_avg_loss_min': np.float64(8.485429), 'test_avg_loss_max': np.float64(33.015446), 'test_avg_loss_bottom10%': np.float64(8.485429), 'test_avg_loss_top10%': np.float64(33.015446), 'test_avg_loss_cos1': np.float64(0.893386), 'test_avg_loss_entropy': np.float64(2.185722), 'test_loss_std': np.float64(29233.102362), 'test_loss_bottom_decile': np.float64(30134.354675), 'test_loss_top_decile': np.float64(116214.369934), 'test_loss_min': np.float64(29868.708588), 'test_loss_max': np.float64(116214.369934), 'test_loss_bottom10%': np.float64(29868.708588), 'test_loss_top10%': np.float64(116214.369934), 'test_loss_cos1': np.float64(0.893386), 'test_loss_entropy': np.float64(2.185722), 'val_avg_loss_std': np.float64(8.833263), 'val_avg_loss_bottom_decile': np.float64(8.98491), 'val_avg_loss_top_decile': np.float64(33.578189), 'val_avg_loss_min': np.float64(8.645276), 'val_avg_loss_max': np.float64(33.578189), 'val_avg_loss_bottom10%': np.float64(8.645276), 'val_avg_loss_top10%': np.float64(33.578189), 'val_avg_loss_cos1': np.float64(0.896807), 'val_avg_loss_entropy': np.float64(2.187654), 'val_loss_std': np.float64(31093.086766), 'val_loss_bottom_decile': np.float64(31626.882324), 'val_loss_top_decile': np.float64(118195.225342), 'val_loss_min': np.float64(30431.371063), 'val_loss_max': np.float64(118195.225342), 'val_loss_bottom10%': np.float64(30431.371063), 'val_loss_top10%': np.float64(118195.225342), 'val_loss_cos1': np.float64(0.896807), 'val_loss_entropy': np.float64(2.187654)}}
|
|
2024-11-13 16:06:21,051 (server:353) INFO: Server: Starting evaluation at the end of round 28.
|
|
2024-11-13 16:06:21,052 (server:359) INFO: ----------- Starting a new training round (Round #29) -------------
|
|
2024-11-13 16:08:11,842 (client:354) INFO: {'Role': 'Client #1', 'Round': 29, 'Results_raw': {'train_loss': 8.88242, 'val_loss': 8.144161, 'test_loss': 8.569347}}
|
|
2024-11-13 16:08:50,120 (client:354) INFO: {'Role': 'Client #5', 'Round': 29, 'Results_raw': {'train_loss': 6.093593, 'val_loss': 6.061502, 'test_loss': 5.875234}}
|
|
2024-11-13 16:09:37,826 (client:354) INFO: {'Role': 'Client #7', 'Round': 29, 'Results_raw': {'train_loss': 11.715416, 'val_loss': 11.211178, 'test_loss': 10.426667}}
|
|
2024-11-13 16:10:35,605 (client:354) INFO: {'Role': 'Client #6', 'Round': 29, 'Results_raw': {'train_loss': 9.242991, 'val_loss': 9.281599, 'test_loss': 9.258591}}
|
|
2024-11-13 16:11:36,552 (client:354) INFO: {'Role': 'Client #3', 'Round': 29, 'Results_raw': {'train_loss': 9.112825, 'val_loss': 8.65555, 'test_loss': 9.135675}}
|
|
2024-11-13 16:12:35,463 (client:354) INFO: {'Role': 'Client #4', 'Round': 29, 'Results_raw': {'train_loss': 7.470688, 'val_loss': 6.689402, 'test_loss': 6.720886}}
|
|
2024-11-13 16:13:34,974 (client:354) INFO: {'Role': 'Client #9', 'Round': 29, 'Results_raw': {'train_loss': 13.796879, 'val_loss': 16.196899, 'test_loss': 12.871875}}
|
|
2024-11-13 16:14:33,332 (client:354) INFO: {'Role': 'Client #10', 'Round': 29, 'Results_raw': {'train_loss': 16.713978, 'val_loss': 15.58606, 'test_loss': 15.252982}}
|
|
2024-11-13 16:15:32,750 (client:354) INFO: {'Role': 'Client #2', 'Round': 29, 'Results_raw': {'train_loss': 11.130194, 'val_loss': 11.160521, 'test_loss': 10.465325}}
|
|
2024-11-13 16:16:31,683 (client:354) INFO: {'Role': 'Client #8', 'Round': 29, 'Results_raw': {'train_loss': 7.690787, 'val_loss': 15.967228, 'test_loss': 8.09048}}
|
|
2024-11-13 16:16:31,687 (server:615) INFO: {'Role': 'Server #', 'Round': 28, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.682012), 'test_loss': np.float64(58720.682834), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(18.093653), 'val_loss': np.float64(63689.658249)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.682012), 'test_loss': np.float64(58720.682834), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(18.093653), 'val_loss': np.float64(63689.658249)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(8.457517), 'test_avg_loss_bottom_decile': np.float64(8.626526), 'test_avg_loss_top_decile': np.float64(32.962707), 'test_avg_loss_min': np.float64(8.535171), 'test_avg_loss_max': np.float64(32.962707), 'test_avg_loss_bottom10%': np.float64(8.535171), 'test_avg_loss_top10%': np.float64(32.962707), 'test_avg_loss_cos1': np.float64(0.891922), 'test_avg_loss_entropy': np.float64(2.183894), 'test_loss_std': np.float64(29770.460674), 'test_loss_bottom_decile': np.float64(30365.372467), 'test_loss_top_decile': np.float64(116028.728638), 'test_loss_min': np.float64(30043.803528), 'test_loss_max': np.float64(116028.728638), 'test_loss_bottom10%': np.float64(30043.803528), 'test_loss_top10%': np.float64(116028.728638), 'test_loss_cos1': np.float64(0.891922), 'test_loss_entropy': np.float64(2.183894), 'val_avg_loss_std': np.float64(9.015804), 'val_avg_loss_bottom_decile': np.float64(9.045823), 'val_avg_loss_top_decile': np.float64(34.670716), 'val_avg_loss_min': np.float64(8.708012), 'val_avg_loss_max': np.float64(34.670716), 'val_avg_loss_bottom10%': np.float64(8.708012), 'val_avg_loss_top10%': np.float64(34.670716), 'val_avg_loss_cos1': np.float64(0.89504), 'val_avg_loss_entropy': np.float64(2.185604), 'val_loss_std': np.float64(31735.629849), 'val_loss_bottom_decile': np.float64(31841.296295), 'val_loss_top_decile': np.float64(122040.918701), 'val_loss_min': np.float64(30652.201599), 'val_loss_max': np.float64(122040.918701), 'val_loss_bottom10%': np.float64(30652.201599), 'val_loss_top10%': np.float64(122040.918701), 'val_loss_cos1': np.float64(0.89504), 'val_loss_entropy': np.float64(2.185604)}}
|
|
2024-11-13 16:16:31,721 (server:353) INFO: Server: Starting evaluation at the end of round 29.
|
|
2024-11-13 16:16:31,721 (server:359) INFO: ----------- Starting a new training round (Round #30) -------------
|
|
2024-11-13 16:19:36,647 (client:354) INFO: {'Role': 'Client #7', 'Round': 30, 'Results_raw': {'train_loss': 11.571221, 'val_loss': 11.422316, 'test_loss': 10.512166}}
|
|
2024-11-13 16:20:35,285 (client:354) INFO: {'Role': 'Client #6', 'Round': 30, 'Results_raw': {'train_loss': 9.216982, 'val_loss': 9.036764, 'test_loss': 9.058466}}
|
|
2024-11-13 16:21:35,833 (client:354) INFO: {'Role': 'Client #10', 'Round': 30, 'Results_raw': {'train_loss': 15.800599, 'val_loss': 15.683133, 'test_loss': 15.424544}}
|
|
2024-11-13 16:22:36,238 (client:354) INFO: {'Role': 'Client #8', 'Round': 30, 'Results_raw': {'train_loss': 7.667053, 'val_loss': 15.09349, 'test_loss': 8.09754}}
|
|
2024-11-13 16:23:36,898 (client:354) INFO: {'Role': 'Client #3', 'Round': 30, 'Results_raw': {'train_loss': 9.086032, 'val_loss': 8.682818, 'test_loss': 9.148368}}
|
|
2024-11-13 16:24:34,930 (client:354) INFO: {'Role': 'Client #2', 'Round': 30, 'Results_raw': {'train_loss': 11.360294, 'val_loss': 11.458044, 'test_loss': 10.459906}}
|
|
2024-11-13 16:25:36,040 (client:354) INFO: {'Role': 'Client #5', 'Round': 30, 'Results_raw': {'train_loss': 6.099066, 'val_loss': 6.056733, 'test_loss': 6.015176}}
|
|
2024-11-13 16:26:36,582 (client:354) INFO: {'Role': 'Client #4', 'Round': 30, 'Results_raw': {'train_loss': 7.511151, 'val_loss': 7.12478, 'test_loss': 7.209438}}
|
|
2024-11-13 16:27:36,436 (client:354) INFO: {'Role': 'Client #9', 'Round': 30, 'Results_raw': {'train_loss': 13.237736, 'val_loss': 15.413603, 'test_loss': 11.802599}}
|
|
2024-11-13 16:28:35,773 (client:354) INFO: {'Role': 'Client #1', 'Round': 30, 'Results_raw': {'train_loss': 8.895611, 'val_loss': 8.13855, 'test_loss': 8.534337}}
|
|
2024-11-13 16:28:35,778 (server:615) INFO: {'Role': 'Server #', 'Round': 29, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.959632), 'test_loss': np.float64(59697.906116), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(18.395381), 'val_loss': np.float64(64751.740015)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.959632), 'test_loss': np.float64(59697.906116), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(18.395381), 'val_loss': np.float64(64751.740015)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(8.76629), 'test_avg_loss_bottom_decile': np.float64(8.579523), 'test_avg_loss_top_decile': np.float64(34.091482), 'test_avg_loss_min': np.float64(8.565771), 'test_avg_loss_max': np.float64(34.091482), 'test_avg_loss_bottom10%': np.float64(8.565771), 'test_avg_loss_top10%': np.float64(34.091482), 'test_avg_loss_cos1': np.float64(0.888344), 'test_avg_loss_entropy': np.float64(2.179104), 'test_loss_std': np.float64(30857.342127), 'test_loss_bottom_decile': np.float64(30199.922546), 'test_loss_top_decile': np.float64(120002.017273), 'test_loss_min': np.float64(30151.513641), 'test_loss_max': np.float64(120002.017273), 'test_loss_bottom10%': np.float64(30151.513641), 'test_loss_top10%': np.float64(120002.017273), 'test_loss_cos1': np.float64(0.888344), 'test_loss_entropy': np.float64(2.179104), 'val_avg_loss_std': np.float64(9.302698), 'val_avg_loss_bottom_decile': np.float64(9.004369), 'val_avg_loss_top_decile': np.float64(35.048058), 'val_avg_loss_min': np.float64(8.733536), 'val_avg_loss_max': np.float64(35.048058), 'val_avg_loss_bottom10%': np.float64(8.733536), 'val_avg_loss_top10%': np.float64(35.048058), 'val_avg_loss_cos1': np.float64(0.89238), 'val_avg_loss_entropy': np.float64(2.181791), 'val_loss_std': np.float64(32745.496594), 'val_loss_bottom_decile': np.float64(31695.377258), 'val_loss_top_decile': np.float64(123369.164673), 'val_loss_min': np.float64(30742.045959), 'val_loss_max': np.float64(123369.164673), 'val_loss_bottom10%': np.float64(30742.045959), 'val_loss_top10%': np.float64(123369.164673), 'val_loss_cos1': np.float64(0.89238), 'val_loss_entropy': np.float64(2.181791)}}
|
|
2024-11-13 16:28:35,815 (server:353) INFO: Server: Starting evaluation at the end of round 30.
|
|
2024-11-13 16:28:35,815 (server:359) INFO: ----------- Starting a new training round (Round #31) -------------
|
|
2024-11-13 16:31:36,412 (client:354) INFO: {'Role': 'Client #4', 'Round': 31, 'Results_raw': {'train_loss': 7.497715, 'val_loss': 6.699892, 'test_loss': 6.794443}}
|
|
2024-11-13 16:32:35,269 (client:354) INFO: {'Role': 'Client #2', 'Round': 31, 'Results_raw': {'train_loss': 11.085514, 'val_loss': 11.053814, 'test_loss': 10.294542}}
|
|
2024-11-13 16:33:34,421 (client:354) INFO: {'Role': 'Client #5', 'Round': 31, 'Results_raw': {'train_loss': 6.103826, 'val_loss': 6.090899, 'test_loss': 5.912109}}
|
|
2024-11-13 16:34:32,832 (client:354) INFO: {'Role': 'Client #10', 'Round': 31, 'Results_raw': {'train_loss': 16.174907, 'val_loss': 15.433742, 'test_loss': 15.144414}}
|
|
2024-11-13 16:35:33,185 (client:354) INFO: {'Role': 'Client #3', 'Round': 31, 'Results_raw': {'train_loss': 9.08959, 'val_loss': 8.74343, 'test_loss': 9.204622}}
|
|
2024-11-13 16:36:33,998 (client:354) INFO: {'Role': 'Client #9', 'Round': 31, 'Results_raw': {'train_loss': 13.601337, 'val_loss': 15.861343, 'test_loss': 12.132601}}
|
|
2024-11-13 16:37:33,332 (client:354) INFO: {'Role': 'Client #1', 'Round': 31, 'Results_raw': {'train_loss': 8.879463, 'val_loss': 8.24588, 'test_loss': 8.631635}}
|
|
2024-11-13 16:38:33,684 (client:354) INFO: {'Role': 'Client #6', 'Round': 31, 'Results_raw': {'train_loss': 9.233108, 'val_loss': 9.255497, 'test_loss': 9.225529}}
|
|
2024-11-13 16:39:33,328 (client:354) INFO: {'Role': 'Client #7', 'Round': 31, 'Results_raw': {'train_loss': 11.702087, 'val_loss': 11.231685, 'test_loss': 10.436683}}
|
|
2024-11-13 16:40:32,529 (client:354) INFO: {'Role': 'Client #8', 'Round': 31, 'Results_raw': {'train_loss': 7.665638, 'val_loss': 15.304727, 'test_loss': 7.941122}}
|
|
2024-11-13 16:40:32,533 (server:615) INFO: {'Role': 'Server #', 'Round': 30, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.19537), 'test_loss': np.float64(57007.703366), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.568388), 'val_loss': np.float64(61840.725079)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.19537), 'test_loss': np.float64(57007.703366), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.568388), 'val_loss': np.float64(61840.725079)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(7.976618), 'test_avg_loss_bottom_decile': np.float64(8.481409), 'test_avg_loss_top_decile': np.float64(31.876151), 'test_avg_loss_min': np.float64(8.474651), 'test_avg_loss_max': np.float64(31.876151), 'test_avg_loss_bottom10%': np.float64(8.474651), 'test_avg_loss_top10%': np.float64(31.876151), 'test_avg_loss_cos1': np.float64(0.897094), 'test_avg_loss_entropy': np.float64(2.190418), 'test_loss_std': np.float64(28077.696514), 'test_loss_bottom_decile': np.float64(29854.559509), 'test_loss_top_decile': np.float64(112204.051758), 'test_loss_min': np.float64(29830.772552), 'test_loss_max': np.float64(112204.051758), 'test_loss_bottom10%': np.float64(29830.772552), 'test_loss_top10%': np.float64(112204.051758), 'test_loss_cos1': np.float64(0.897094), 'test_loss_entropy': np.float64(2.190418), 'val_avg_loss_std': np.float64(8.503421), 'val_avg_loss_bottom_decile': np.float64(8.885054), 'val_avg_loss_top_decile': np.float64(32.924227), 'val_avg_loss_min': np.float64(8.6421), 'val_avg_loss_max': np.float64(32.924227), 'val_avg_loss_bottom10%': np.float64(8.6421), 'val_avg_loss_top10%': np.float64(32.924227), 'val_avg_loss_cos1': np.float64(0.900107), 'val_avg_loss_entropy': np.float64(2.191826), 'val_loss_std': np.float64(29932.04285), 'val_loss_bottom_decile': np.float64(31275.38916), 'val_loss_top_decile': np.float64(115893.279053), 'val_loss_min': np.float64(30420.19339), 'val_loss_max': np.float64(115893.279053), 'val_loss_bottom10%': np.float64(30420.19339), 'val_loss_top10%': np.float64(115893.279053), 'val_loss_cos1': np.float64(0.900107), 'val_loss_entropy': np.float64(2.191826)}}
|
|
2024-11-13 16:40:32,575 (server:353) INFO: Server: Starting evaluation at the end of round 31.
|
|
2024-11-13 16:40:32,576 (server:359) INFO: ----------- Starting a new training round (Round #32) -------------
|
|
2024-11-13 16:43:36,446 (client:354) INFO: {'Role': 'Client #5', 'Round': 32, 'Results_raw': {'train_loss': 6.097673, 'val_loss': 5.925765, 'test_loss': 5.936716}}
|
|
2024-11-13 16:44:39,450 (client:354) INFO: {'Role': 'Client #10', 'Round': 32, 'Results_raw': {'train_loss': 15.331825, 'val_loss': 15.232663, 'test_loss': 14.847722}}
|
|
2024-11-13 16:45:41,962 (client:354) INFO: {'Role': 'Client #3', 'Round': 32, 'Results_raw': {'train_loss': 9.128181, 'val_loss': 8.614091, 'test_loss': 9.064058}}
|
|
2024-11-13 16:46:45,562 (client:354) INFO: {'Role': 'Client #2', 'Round': 32, 'Results_raw': {'train_loss': 11.213103, 'val_loss': 11.539631, 'test_loss': 10.581737}}
|
|
2024-11-13 16:47:49,503 (client:354) INFO: {'Role': 'Client #7', 'Round': 32, 'Results_raw': {'train_loss': 11.374358, 'val_loss': 10.995223, 'test_loss': 10.212604}}
|
|
2024-11-13 16:48:53,038 (client:354) INFO: {'Role': 'Client #8', 'Round': 32, 'Results_raw': {'train_loss': 7.683023, 'val_loss': 15.157709, 'test_loss': 8.00594}}
|
|
2024-11-13 16:49:55,291 (client:354) INFO: {'Role': 'Client #9', 'Round': 32, 'Results_raw': {'train_loss': 13.61942, 'val_loss': 16.461367, 'test_loss': 13.205846}}
|
|
2024-11-13 16:50:57,569 (client:354) INFO: {'Role': 'Client #1', 'Round': 32, 'Results_raw': {'train_loss': 8.843366, 'val_loss': 8.125521, 'test_loss': 8.541859}}
|
|
2024-11-13 16:52:00,686 (client:354) INFO: {'Role': 'Client #4', 'Round': 32, 'Results_raw': {'train_loss': 7.430789, 'val_loss': 6.646213, 'test_loss': 6.753066}}
|
|
2024-11-13 16:52:55,124 (client:354) INFO: {'Role': 'Client #6', 'Round': 32, 'Results_raw': {'train_loss': 9.256926, 'val_loss': 9.38684, 'test_loss': 9.372346}}
|
|
2024-11-13 16:52:55,127 (server:615) INFO: {'Role': 'Server #', 'Round': 31, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.441331), 'test_loss': np.float64(57873.484991), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.854184), 'val_loss': np.float64(62846.728366)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.441331), 'test_loss': np.float64(57873.484991), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.854184), 'val_loss': np.float64(62846.728366)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(8.27994), 'test_avg_loss_bottom_decile': np.float64(8.47879), 'test_avg_loss_top_decile': np.float64(32.880313), 'test_avg_loss_min': np.float64(8.433715), 'test_avg_loss_max': np.float64(32.880313), 'test_avg_loss_bottom10%': np.float64(8.433715), 'test_avg_loss_top10%': np.float64(32.880313), 'test_avg_loss_cos1': np.float64(0.893136), 'test_avg_loss_entropy': np.float64(2.185349), 'test_loss_std': np.float64(29145.388327), 'test_loss_bottom_decile': np.float64(29845.340973), 'test_loss_top_decile': np.float64(115738.700439), 'test_loss_min': np.float64(29686.67691), 'test_loss_max': np.float64(115738.700439), 'test_loss_bottom10%': np.float64(29686.67691), 'test_loss_top10%': np.float64(115738.700439), 'test_loss_cos1': np.float64(0.893136), 'test_loss_entropy': np.float64(2.185349), 'val_avg_loss_std': np.float64(8.790208), 'val_avg_loss_bottom_decile': np.float64(8.888642), 'val_avg_loss_top_decile': np.float64(33.340556), 'val_avg_loss_min': np.float64(8.597065), 'val_avg_loss_max': np.float64(33.340556), 'val_avg_loss_bottom10%': np.float64(8.597065), 'val_avg_loss_top10%': np.float64(33.340556), 'val_avg_loss_cos1': np.float64(0.897162), 'val_avg_loss_entropy': np.float64(2.187743), 'val_loss_std': np.float64(30941.533726), 'val_loss_bottom_decile': np.float64(31288.018707), 'val_loss_top_decile': np.float64(117358.757446), 'val_loss_min': np.float64(30261.668732), 'val_loss_max': np.float64(117358.757446), 'val_loss_bottom10%': np.float64(30261.668732), 'val_loss_top10%': np.float64(117358.757446), 'val_loss_cos1': np.float64(0.897162), 'val_loss_entropy': np.float64(2.187743)}}
|
|
2024-11-13 16:52:55,172 (server:353) INFO: Server: Starting evaluation at the end of round 32.
|
|
2024-11-13 16:52:55,173 (server:359) INFO: ----------- Starting a new training round (Round #33) -------------
|
|
2024-11-13 16:54:43,845 (client:354) INFO: {'Role': 'Client #9', 'Round': 33, 'Results_raw': {'train_loss': 13.509552, 'val_loss': 16.258148, 'test_loss': 12.659134}}
|
|
2024-11-13 16:55:22,577 (client:354) INFO: {'Role': 'Client #8', 'Round': 33, 'Results_raw': {'train_loss': 7.651885, 'val_loss': 15.509145, 'test_loss': 8.129149}}
|
|
2024-11-13 16:56:01,740 (client:354) INFO: {'Role': 'Client #7', 'Round': 33, 'Results_raw': {'train_loss': 11.446318, 'val_loss': 10.97497, 'test_loss': 10.131911}}
|
|
2024-11-13 16:56:36,943 (client:354) INFO: {'Role': 'Client #10', 'Round': 33, 'Results_raw': {'train_loss': 15.926103, 'val_loss': 16.111263, 'test_loss': 15.606205}}
|
|
2024-11-13 16:57:12,315 (client:354) INFO: {'Role': 'Client #1', 'Round': 33, 'Results_raw': {'train_loss': 8.856002, 'val_loss': 8.09792, 'test_loss': 8.53523}}
|
|
2024-11-13 16:57:47,865 (client:354) INFO: {'Role': 'Client #5', 'Round': 33, 'Results_raw': {'train_loss': 6.022975, 'val_loss': 5.998991, 'test_loss': 5.949561}}
|
|
2024-11-13 16:58:25,849 (client:354) INFO: {'Role': 'Client #3', 'Round': 33, 'Results_raw': {'train_loss': 9.073043, 'val_loss': 8.79495, 'test_loss': 9.256633}}
|
|
2024-11-13 16:59:04,928 (client:354) INFO: {'Role': 'Client #6', 'Round': 33, 'Results_raw': {'train_loss': 9.180257, 'val_loss': 8.917255, 'test_loss': 8.915948}}
|
|
2024-11-13 16:59:45,751 (client:354) INFO: {'Role': 'Client #2', 'Round': 33, 'Results_raw': {'train_loss': 11.026876, 'val_loss': 10.977856, 'test_loss': 10.183379}}
|
|
2024-11-13 17:00:24,975 (client:354) INFO: {'Role': 'Client #4', 'Round': 33, 'Results_raw': {'train_loss': 7.443344, 'val_loss': 6.659187, 'test_loss': 6.732375}}
|
|
2024-11-13 17:00:24,978 (server:615) INFO: {'Role': 'Server #', 'Round': 32, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.469414), 'test_loss': np.float64(57972.338055), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.854818), 'val_loss': np.float64(62848.959943)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.469414), 'test_loss': np.float64(57972.338055), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.854818), 'val_loss': np.float64(62848.959943)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(8.287275), 'test_avg_loss_bottom_decile': np.float64(8.489894), 'test_avg_loss_top_decile': np.float64(32.579402), 'test_avg_loss_min': np.float64(8.461607), 'test_avg_loss_max': np.float64(32.579402), 'test_avg_loss_bottom10%': np.float64(8.461607), 'test_avg_loss_top10%': np.float64(32.579402), 'test_avg_loss_cos1': np.float64(0.893284), 'test_avg_loss_entropy': np.float64(2.185428), 'test_loss_std': np.float64(29171.208629), 'test_loss_bottom_decile': np.float64(29884.427856), 'test_loss_top_decile': np.float64(114679.496277), 'test_loss_min': np.float64(29784.857483), 'test_loss_max': np.float64(114679.496277), 'test_loss_bottom10%': np.float64(29784.857483), 'test_loss_top10%': np.float64(114679.496277), 'test_loss_cos1': np.float64(0.893284), 'test_loss_entropy': np.float64(2.185428), 'val_avg_loss_std': np.float64(8.806157), 'val_avg_loss_bottom_decile': np.float64(8.883433), 'val_avg_loss_top_decile': np.float64(33.793311), 'val_avg_loss_min': np.float64(8.646711), 'val_avg_loss_max': np.float64(33.793311), 'val_avg_loss_bottom10%': np.float64(8.646711), 'val_avg_loss_top10%': np.float64(33.793311), 'val_avg_loss_cos1': np.float64(0.89685), 'val_avg_loss_entropy': np.float64(2.187547), 'val_loss_std': np.float64(30997.672186), 'val_loss_bottom_decile': np.float64(31269.683167), 'val_loss_top_decile': np.float64(118952.456055), 'val_loss_min': np.float64(30436.423981), 'val_loss_max': np.float64(118952.456055), 'val_loss_bottom10%': np.float64(30436.423981), 'val_loss_top10%': np.float64(118952.456055), 'val_loss_cos1': np.float64(0.89685), 'val_loss_entropy': np.float64(2.187547)}}
|
|
2024-11-13 17:00:25,016 (server:353) INFO: Server: Starting evaluation at the end of round 33.
|
|
2024-11-13 17:00:25,017 (server:359) INFO: ----------- Starting a new training round (Round #34) -------------
|
|
2024-11-13 17:02:21,049 (client:354) INFO: {'Role': 'Client #4', 'Round': 34, 'Results_raw': {'train_loss': 7.452153, 'val_loss': 6.718533, 'test_loss': 6.784214}}
|
|
2024-11-13 17:03:02,949 (client:354) INFO: {'Role': 'Client #7', 'Round': 34, 'Results_raw': {'train_loss': 11.527385, 'val_loss': 11.163562, 'test_loss': 10.314601}}
|
|
2024-11-13 17:03:41,243 (client:354) INFO: {'Role': 'Client #8', 'Round': 34, 'Results_raw': {'train_loss': 7.608423, 'val_loss': 15.730577, 'test_loss': 8.164101}}
|
|
2024-11-13 17:04:19,091 (client:354) INFO: {'Role': 'Client #10', 'Round': 34, 'Results_raw': {'train_loss': 15.886386, 'val_loss': 15.84929, 'test_loss': 15.193549}}
|
|
2024-11-13 17:04:57,214 (client:354) INFO: {'Role': 'Client #5', 'Round': 34, 'Results_raw': {'train_loss': 6.038219, 'val_loss': 5.957139, 'test_loss': 5.840021}}
|
|
2024-11-13 17:05:35,067 (client:354) INFO: {'Role': 'Client #2', 'Round': 34, 'Results_raw': {'train_loss': 11.263326, 'val_loss': 10.944633, 'test_loss': 10.231161}}
|
|
2024-11-13 17:06:13,043 (client:354) INFO: {'Role': 'Client #9', 'Round': 34, 'Results_raw': {'train_loss': 13.396876, 'val_loss': 15.502224, 'test_loss': 11.982104}}
|
|
2024-11-13 17:06:49,468 (client:354) INFO: {'Role': 'Client #3', 'Round': 34, 'Results_raw': {'train_loss': 9.054836, 'val_loss': 8.622701, 'test_loss': 9.130674}}
|
|
2024-11-13 17:07:25,344 (client:354) INFO: {'Role': 'Client #1', 'Round': 34, 'Results_raw': {'train_loss': 8.839537, 'val_loss': 8.192691, 'test_loss': 8.534337}}
|
|
2024-11-13 17:08:02,828 (client:354) INFO: {'Role': 'Client #6', 'Round': 34, 'Results_raw': {'train_loss': 9.187697, 'val_loss': 8.926336, 'test_loss': 8.944056}}
|
|
2024-11-13 17:08:02,831 (server:615) INFO: {'Role': 'Server #', 'Round': 33, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.869256), 'test_loss': np.float64(59379.781494), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(18.278443), 'val_loss': np.float64(64340.119934)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.869256), 'test_loss': np.float64(59379.781494), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(18.278443), 'val_loss': np.float64(64340.119934)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(8.730025), 'test_avg_loss_bottom_decile': np.float64(8.509488), 'test_avg_loss_top_decile': np.float64(34.028643), 'test_avg_loss_min': np.float64(8.49251), 'test_avg_loss_max': np.float64(34.028643), 'test_avg_loss_bottom10%': np.float64(8.49251), 'test_avg_loss_top10%': np.float64(34.028643), 'test_avg_loss_cos1': np.float64(0.88812), 'test_avg_loss_entropy': np.float64(2.178732), 'test_loss_std': np.float64(30729.689002), 'test_loss_bottom_decile': np.float64(29953.396423), 'test_loss_top_decile': np.float64(119780.824768), 'test_loss_min': np.float64(29893.636658), 'test_loss_max': np.float64(119780.824768), 'test_loss_bottom10%': np.float64(29893.636658), 'test_loss_top10%': np.float64(119780.824768), 'test_loss_cos1': np.float64(0.88812), 'test_loss_entropy': np.float64(2.178732), 'val_avg_loss_std': np.float64(9.25379), 'val_avg_loss_bottom_decile': np.float64(8.896047), 'val_avg_loss_top_decile': np.float64(34.698546), 'val_avg_loss_min': np.float64(8.671405), 'val_avg_loss_max': np.float64(34.698546), 'val_avg_loss_bottom10%': np.float64(8.671405), 'val_avg_loss_top10%': np.float64(34.698546), 'val_avg_loss_cos1': np.float64(0.892179), 'val_avg_loss_entropy': np.float64(2.181392), 'val_loss_std': np.float64(32573.342142), 'val_loss_bottom_decile': np.float64(31314.084229), 'val_loss_top_decile': np.float64(122138.882996), 'val_loss_min': np.float64(30523.345551), 'val_loss_max': np.float64(122138.882996), 'val_loss_bottom10%': np.float64(30523.345551), 'val_loss_top10%': np.float64(122138.882996), 'val_loss_cos1': np.float64(0.892179), 'val_loss_entropy': np.float64(2.181392)}}
|
|
2024-11-13 17:08:02,869 (server:353) INFO: Server: Starting evaluation at the end of round 34.
|
|
2024-11-13 17:08:02,870 (server:359) INFO: ----------- Starting a new training round (Round #35) -------------
|
|
2024-11-13 17:09:38,371 (client:354) INFO: {'Role': 'Client #3', 'Round': 35, 'Results_raw': {'train_loss': 9.034865, 'val_loss': 8.644745, 'test_loss': 9.145667}}
|
|
2024-11-13 17:10:16,972 (client:354) INFO: {'Role': 'Client #9', 'Round': 35, 'Results_raw': {'train_loss': 13.12398, 'val_loss': 15.543219, 'test_loss': 11.996148}}
|
|
2024-11-13 17:10:55,294 (client:354) INFO: {'Role': 'Client #2', 'Round': 35, 'Results_raw': {'train_loss': 11.130878, 'val_loss': 11.066255, 'test_loss': 10.205709}}
|
|
2024-11-13 17:11:34,737 (client:354) INFO: {'Role': 'Client #8', 'Round': 35, 'Results_raw': {'train_loss': 7.59582, 'val_loss': 14.773483, 'test_loss': 8.066531}}
|
|
2024-11-13 17:12:13,644 (client:354) INFO: {'Role': 'Client #5', 'Round': 35, 'Results_raw': {'train_loss': 6.077758, 'val_loss': 6.036631, 'test_loss': 6.007671}}
|
|
2024-11-13 17:12:52,548 (client:354) INFO: {'Role': 'Client #4', 'Round': 35, 'Results_raw': {'train_loss': 7.422219, 'val_loss': 6.695572, 'test_loss': 6.721559}}
|
|
2024-11-13 17:13:31,199 (client:354) INFO: {'Role': 'Client #6', 'Round': 35, 'Results_raw': {'train_loss': 9.198831, 'val_loss': 9.030692, 'test_loss': 9.089033}}
|
|
2024-11-13 17:14:09,456 (client:354) INFO: {'Role': 'Client #7', 'Round': 35, 'Results_raw': {'train_loss': 11.344288, 'val_loss': 11.047243, 'test_loss': 10.206013}}
|
|
2024-11-13 17:14:47,962 (client:354) INFO: {'Role': 'Client #10', 'Round': 35, 'Results_raw': {'train_loss': 15.475626, 'val_loss': 15.729191, 'test_loss': 15.146765}}
|
|
2024-11-13 17:15:25,864 (client:354) INFO: {'Role': 'Client #1', 'Round': 35, 'Results_raw': {'train_loss': 8.817259, 'val_loss': 8.164946, 'test_loss': 8.567635}}
|
|
2024-11-13 17:15:25,868 (server:615) INFO: {'Role': 'Server #', 'Round': 34, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.555129), 'test_loss': np.float64(58274.053006), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.954991), 'val_loss': np.float64(63201.568741)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.555129), 'test_loss': np.float64(58274.053006), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.954991), 'val_loss': np.float64(63201.568741)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(8.321713), 'test_avg_loss_bottom_decile': np.float64(8.538476), 'test_avg_loss_top_decile': np.float64(32.961279), 'test_avg_loss_min': np.float64(8.520683), 'test_avg_loss_max': np.float64(32.961279), 'test_avg_loss_bottom10%': np.float64(8.520683), 'test_avg_loss_top10%': np.float64(32.961279), 'test_avg_loss_cos1': np.float64(0.893472), 'test_avg_loss_entropy': np.float64(2.185676), 'test_loss_std': np.float64(29292.430375), 'test_loss_bottom_decile': np.float64(30055.43631), 'test_loss_top_decile': np.float64(116023.701294), 'test_loss_min': np.float64(29992.803101), 'test_loss_max': np.float64(116023.701294), 'test_loss_bottom10%': np.float64(29992.803101), 'test_loss_top10%': np.float64(116023.701294), 'test_loss_cos1': np.float64(0.893472), 'test_loss_entropy': np.float64(2.185676), 'val_avg_loss_std': np.float64(8.842943), 'val_avg_loss_bottom_decile': np.float64(8.966377), 'val_avg_loss_top_decile': np.float64(33.559581), 'val_avg_loss_min': np.float64(8.674447), 'val_avg_loss_max': np.float64(33.559581), 'val_avg_loss_bottom10%': np.float64(8.674447), 'val_avg_loss_top10%': np.float64(33.559581), 'val_avg_loss_cos1': np.float64(0.8971), 'val_avg_loss_entropy': np.float64(2.187721), 'val_loss_std': np.float64(31127.15943), 'val_loss_bottom_decile': np.float64(31561.648346), 'val_loss_top_decile': np.float64(118129.726807), 'val_loss_min': np.float64(30534.053101), 'val_loss_max': np.float64(118129.726807), 'val_loss_bottom10%': np.float64(30534.053101), 'val_loss_top10%': np.float64(118129.726807), 'val_loss_cos1': np.float64(0.8971), 'val_loss_entropy': np.float64(2.187721)}}
|
|
2024-11-13 17:15:25,920 (server:353) INFO: Server: Starting evaluation at the end of round 35.
|
|
2024-11-13 17:15:25,921 (server:359) INFO: ----------- Starting a new training round (Round #36) -------------
|
|
2024-11-13 17:17:09,945 (client:354) INFO: {'Role': 'Client #9', 'Round': 36, 'Results_raw': {'train_loss': 13.027228, 'val_loss': 15.93354, 'test_loss': 12.340871}}
|
|
2024-11-13 17:17:50,789 (client:354) INFO: {'Role': 'Client #6', 'Round': 36, 'Results_raw': {'train_loss': 9.122606, 'val_loss': 9.048812, 'test_loss': 9.021129}}
|
|
2024-11-13 17:18:26,703 (client:354) INFO: {'Role': 'Client #8', 'Round': 36, 'Results_raw': {'train_loss': 7.600428, 'val_loss': 15.349992, 'test_loss': 7.902671}}
|
|
2024-11-13 17:19:00,396 (client:354) INFO: {'Role': 'Client #5', 'Round': 36, 'Results_raw': {'train_loss': 6.04638, 'val_loss': 6.05692, 'test_loss': 6.074522}}
|
|
2024-11-13 17:19:34,344 (client:354) INFO: {'Role': 'Client #7', 'Round': 36, 'Results_raw': {'train_loss': 11.309458, 'val_loss': 10.984316, 'test_loss': 10.170883}}
|
|
2024-11-13 17:20:07,923 (client:354) INFO: {'Role': 'Client #4', 'Round': 36, 'Results_raw': {'train_loss': 7.378021, 'val_loss': 6.658919, 'test_loss': 6.775643}}
|
|
2024-11-13 17:20:41,777 (client:354) INFO: {'Role': 'Client #3', 'Round': 36, 'Results_raw': {'train_loss': 9.043947, 'val_loss': 8.576672, 'test_loss': 9.052754}}
|
|
2024-11-13 17:21:15,251 (client:354) INFO: {'Role': 'Client #2', 'Round': 36, 'Results_raw': {'train_loss': 11.080351, 'val_loss': 11.045402, 'test_loss': 10.104309}}
|
|
2024-11-13 17:21:48,657 (client:354) INFO: {'Role': 'Client #10', 'Round': 36, 'Results_raw': {'train_loss': 15.730475, 'val_loss': 15.653034, 'test_loss': 15.153472}}
|
|
2024-11-13 17:22:22,097 (client:354) INFO: {'Role': 'Client #1', 'Round': 36, 'Results_raw': {'train_loss': 8.8511, 'val_loss': 8.087615, 'test_loss': 8.475662}}
|
|
2024-11-13 17:22:22,100 (server:615) INFO: {'Role': 'Server #', 'Round': 35, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.723388), 'test_loss': np.float64(58866.324188), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(18.137658), 'val_loss': np.float64(63844.555692)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.723388), 'test_loss': np.float64(58866.324188), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(18.137658), 'val_loss': np.float64(63844.555692)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(8.488952), 'test_avg_loss_bottom_decile': np.float64(8.548133), 'test_avg_loss_top_decile': np.float64(33.51388), 'test_avg_loss_min': np.float64(8.54495), 'test_avg_loss_max': np.float64(33.51388), 'test_avg_loss_bottom10%': np.float64(8.54495), 'test_avg_loss_top10%': np.float64(33.51388), 'test_avg_loss_cos1': np.float64(0.891697), 'test_avg_loss_entropy': np.float64(2.183416), 'test_loss_std': np.float64(29881.11035), 'test_loss_bottom_decile': np.float64(30089.429321), 'test_loss_top_decile': np.float64(117968.85791), 'test_loss_min': np.float64(30078.223328), 'test_loss_max': np.float64(117968.85791), 'test_loss_bottom10%': np.float64(30078.223328), 'test_loss_top10%': np.float64(117968.85791), 'test_loss_cos1': np.float64(0.891697), 'test_loss_entropy': np.float64(2.183416), 'val_avg_loss_std': np.float64(9.01556), 'val_avg_loss_bottom_decile': np.float64(8.980595), 'val_avg_loss_top_decile': np.float64(34.012612), 'val_avg_loss_min': np.float64(8.698635), 'val_avg_loss_max': np.float64(34.012612), 'val_avg_loss_bottom10%': np.float64(8.698635), 'val_avg_loss_top10%': np.float64(34.012612), 'val_avg_loss_cos1': np.float64(0.895477), 'val_avg_loss_entropy': np.float64(2.185567), 'val_loss_std': np.float64(31734.772692), 'val_loss_bottom_decile': np.float64(31611.693756), 'val_loss_top_decile': np.float64(119724.393066), 'val_loss_min': np.float64(30619.195099), 'val_loss_max': np.float64(119724.393066), 'val_loss_bottom10%': np.float64(30619.195099), 'val_loss_top10%': np.float64(119724.393066), 'val_loss_cos1': np.float64(0.895477), 'val_loss_entropy': np.float64(2.185567)}}
|
|
2024-11-13 17:22:22,132 (server:353) INFO: Server: Starting evaluation at the end of round 36.
|
|
2024-11-13 17:22:22,133 (server:359) INFO: ----------- Starting a new training round (Round #37) -------------
|
|
2024-11-13 17:23:52,993 (client:354) INFO: {'Role': 'Client #9', 'Round': 37, 'Results_raw': {'train_loss': 13.511374, 'val_loss': 15.34487, 'test_loss': 11.97641}}
|
|
2024-11-13 17:24:26,771 (client:354) INFO: {'Role': 'Client #8', 'Round': 37, 'Results_raw': {'train_loss': 7.604608, 'val_loss': 15.11132, 'test_loss': 7.926113}}
|
|
2024-11-13 17:25:00,443 (client:354) INFO: {'Role': 'Client #1', 'Round': 37, 'Results_raw': {'train_loss': 8.800897, 'val_loss': 8.097452, 'test_loss': 8.484785}}
|
|
2024-11-13 17:25:34,639 (client:354) INFO: {'Role': 'Client #2', 'Round': 37, 'Results_raw': {'train_loss': 10.874615, 'val_loss': 10.835069, 'test_loss': 10.035113}}
|
|
2024-11-13 17:26:10,304 (client:354) INFO: {'Role': 'Client #4', 'Round': 37, 'Results_raw': {'train_loss': 7.388379, 'val_loss': 6.573094, 'test_loss': 6.644931}}
|
|
2024-11-13 17:26:45,336 (client:354) INFO: {'Role': 'Client #5', 'Round': 37, 'Results_raw': {'train_loss': 5.96683, 'val_loss': 6.110123, 'test_loss': 5.996414}}
|
|
2024-11-13 17:27:19,912 (client:354) INFO: {'Role': 'Client #3', 'Round': 37, 'Results_raw': {'train_loss': 9.016297, 'val_loss': 8.571122, 'test_loss': 9.073301}}
|
|
2024-11-13 17:27:55,968 (client:354) INFO: {'Role': 'Client #6', 'Round': 37, 'Results_raw': {'train_loss': 9.252432, 'val_loss': 9.30663, 'test_loss': 9.421805}}
|
|
2024-11-13 17:28:31,184 (client:354) INFO: {'Role': 'Client #10', 'Round': 37, 'Results_raw': {'train_loss': 15.40609, 'val_loss': 15.425855, 'test_loss': 14.93288}}
|
|
2024-11-13 17:29:05,697 (client:354) INFO: {'Role': 'Client #7', 'Round': 37, 'Results_raw': {'train_loss': 11.416042, 'val_loss': 10.936969, 'test_loss': 10.147749}}
|
|
2024-11-13 17:29:05,700 (server:615) INFO: {'Role': 'Server #', 'Round': 36, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.522503), 'test_loss': np.float64(58159.211868), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.946899), 'val_loss': np.float64(63173.083588)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.522503), 'test_loss': np.float64(58159.211868), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.946899), 'val_loss': np.float64(63173.083588)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(8.435771), 'test_avg_loss_bottom_decile': np.float64(8.457429), 'test_avg_loss_top_decile': np.float64(33.185302), 'test_avg_loss_min': np.float64(8.419932), 'test_avg_loss_max': np.float64(33.185302), 'test_avg_loss_bottom10%': np.float64(8.419932), 'test_avg_loss_top10%': np.float64(33.185302), 'test_avg_loss_cos1': np.float64(0.890633), 'test_avg_loss_entropy': np.float64(2.182309), 'test_loss_std': np.float64(29693.915016), 'test_loss_bottom_decile': np.float64(29770.148987), 'test_loss_top_decile': np.float64(116812.262878), 'test_loss_min': np.float64(29638.16153), 'test_loss_max': np.float64(116812.262878), 'test_loss_bottom10%': np.float64(29638.16153), 'test_loss_top10%': np.float64(116812.262878), 'test_loss_cos1': np.float64(0.890633), 'test_loss_entropy': np.float64(2.182309), 'val_avg_loss_std': np.float64(8.977121), 'val_avg_loss_bottom_decile': np.float64(8.835936), 'val_avg_loss_top_decile': np.float64(33.952181), 'val_avg_loss_min': np.float64(8.603023), 'val_avg_loss_max': np.float64(33.952181), 'val_avg_loss_bottom10%': np.float64(8.603023), 'val_avg_loss_top10%': np.float64(33.952181), 'val_avg_loss_cos1': np.float64(0.894354), 'val_avg_loss_entropy': np.float64(2.184394), 'val_loss_std': np.float64(31599.465709), 'val_loss_bottom_decile': np.float64(31102.493622), 'val_loss_top_decile': np.float64(119511.677368), 'val_loss_min': np.float64(30282.642426), 'val_loss_max': np.float64(119511.677368), 'val_loss_bottom10%': np.float64(30282.642426), 'val_loss_top10%': np.float64(119511.677368), 'val_loss_cos1': np.float64(0.894354), 'val_loss_entropy': np.float64(2.184394)}}
|
|
2024-11-13 17:29:05,740 (server:353) INFO: Server: Starting evaluation at the end of round 37.
|
|
2024-11-13 17:29:05,740 (server:359) INFO: ----------- Starting a new training round (Round #38) -------------
|
|
2024-11-13 17:30:39,464 (client:354) INFO: {'Role': 'Client #4', 'Round': 38, 'Results_raw': {'train_loss': 7.421911, 'val_loss': 6.674612, 'test_loss': 6.750345}}
|
|
2024-11-13 17:31:14,152 (client:354) INFO: {'Role': 'Client #2', 'Round': 38, 'Results_raw': {'train_loss': 10.721772, 'val_loss': 11.069343, 'test_loss': 10.378126}}
|
|
2024-11-13 17:31:48,071 (client:354) INFO: {'Role': 'Client #9', 'Round': 38, 'Results_raw': {'train_loss': 13.196427, 'val_loss': 15.491976, 'test_loss': 12.11456}}
|
|
2024-11-13 17:32:22,314 (client:354) INFO: {'Role': 'Client #6', 'Round': 38, 'Results_raw': {'train_loss': 9.096916, 'val_loss': 9.072573, 'test_loss': 9.094092}}
|
|
2024-11-13 17:32:58,574 (client:354) INFO: {'Role': 'Client #5', 'Round': 38, 'Results_raw': {'train_loss': 5.984165, 'val_loss': 5.949474, 'test_loss': 5.933888}}
|
|
2024-11-13 17:33:33,841 (client:354) INFO: {'Role': 'Client #7', 'Round': 38, 'Results_raw': {'train_loss': 11.254725, 'val_loss': 11.012317, 'test_loss': 10.117321}}
|
|
2024-11-13 17:34:07,049 (client:354) INFO: {'Role': 'Client #10', 'Round': 38, 'Results_raw': {'train_loss': 15.16131, 'val_loss': 15.595878, 'test_loss': 15.293852}}
|
|
2024-11-13 17:34:41,028 (client:354) INFO: {'Role': 'Client #3', 'Round': 38, 'Results_raw': {'train_loss': 8.99084, 'val_loss': 8.653226, 'test_loss': 9.162748}}
|
|
2024-11-13 17:35:16,220 (client:354) INFO: {'Role': 'Client #1', 'Round': 38, 'Results_raw': {'train_loss': 8.779855, 'val_loss': 8.092412, 'test_loss': 8.516243}}
|
|
2024-11-13 17:35:51,030 (client:354) INFO: {'Role': 'Client #8', 'Round': 38, 'Results_raw': {'train_loss': 7.547644, 'val_loss': 13.90722, 'test_loss': 8.016115}}
|
|
2024-11-13 17:35:51,035 (server:615) INFO: {'Role': 'Server #', 'Round': 37, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.625504), 'test_loss': np.float64(58521.772949), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(18.027049), 'val_loss': np.float64(63455.213797)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.625504), 'test_loss': np.float64(58521.772949), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(18.027049), 'val_loss': np.float64(63455.213797)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(8.511478), 'test_avg_loss_bottom_decile': np.float64(8.509799), 'test_avg_loss_top_decile': np.float64(33.002763), 'test_avg_loss_min': np.float64(8.492981), 'test_avg_loss_max': np.float64(33.002763), 'test_avg_loss_bottom10%': np.float64(8.492981), 'test_avg_loss_top10%': np.float64(33.002763), 'test_avg_loss_cos1': np.float64(0.890131), 'test_avg_loss_entropy': np.float64(2.181579), 'test_loss_std': np.float64(29960.401202), 'test_loss_bottom_decile': np.float64(29954.492737), 'test_loss_top_decile': np.float64(116169.72583), 'test_loss_min': np.float64(29895.293549), 'test_loss_max': np.float64(116169.72583), 'test_loss_bottom10%': np.float64(29895.293549), 'test_loss_top10%': np.float64(116169.72583), 'test_loss_cos1': np.float64(0.890131), 'test_loss_entropy': np.float64(2.181579), 'val_avg_loss_std': np.float64(9.077288), 'val_avg_loss_bottom_decile': np.float64(8.906037), 'val_avg_loss_top_decile': np.float64(34.612543), 'val_avg_loss_min': np.float64(8.652187), 'val_avg_loss_max': np.float64(34.612543), 'val_avg_loss_bottom10%': np.float64(8.652187), 'val_avg_loss_top10%': np.float64(34.612543), 'val_avg_loss_cos1': np.float64(0.89316), 'val_avg_loss_entropy': np.float64(2.183073), 'val_loss_std': np.float64(31952.053116), 'val_loss_bottom_decile': np.float64(31349.251587), 'val_loss_top_decile': np.float64(121836.151428), 'val_loss_min': np.float64(30455.698822), 'val_loss_max': np.float64(121836.151428), 'val_loss_bottom10%': np.float64(30455.698822), 'val_loss_top10%': np.float64(121836.151428), 'val_loss_cos1': np.float64(0.89316), 'val_loss_entropy': np.float64(2.183073)}}
|
|
2024-11-13 17:35:51,070 (server:353) INFO: Server: Starting evaluation at the end of round 38.
|
|
2024-11-13 17:35:51,070 (server:359) INFO: ----------- Starting a new training round (Round #39) -------------
|
|
2024-11-13 17:37:23,548 (client:354) INFO: {'Role': 'Client #5', 'Round': 39, 'Results_raw': {'train_loss': 6.000834, 'val_loss': 5.924383, 'test_loss': 5.936959}}
|
|
2024-11-13 17:37:58,146 (client:354) INFO: {'Role': 'Client #10', 'Round': 39, 'Results_raw': {'train_loss': 15.459097, 'val_loss': 15.677193, 'test_loss': 15.156719}}
|
|
2024-11-13 17:38:31,785 (client:354) INFO: {'Role': 'Client #7', 'Round': 39, 'Results_raw': {'train_loss': 11.298398, 'val_loss': 10.862025, 'test_loss': 10.005413}}
|
|
2024-11-13 17:39:06,783 (client:354) INFO: {'Role': 'Client #3', 'Round': 39, 'Results_raw': {'train_loss': 9.002221, 'val_loss': 8.620072, 'test_loss': 9.13071}}
|
|
2024-11-13 17:39:44,256 (client:354) INFO: {'Role': 'Client #8', 'Round': 39, 'Results_raw': {'train_loss': 7.525014, 'val_loss': 14.773992, 'test_loss': 7.868934}}
|
|
2024-11-13 17:40:19,204 (client:354) INFO: {'Role': 'Client #4', 'Round': 39, 'Results_raw': {'train_loss': 7.377214, 'val_loss': 6.672813, 'test_loss': 6.714005}}
|
|
2024-11-13 17:40:53,993 (client:354) INFO: {'Role': 'Client #2', 'Round': 39, 'Results_raw': {'train_loss': 10.704716, 'val_loss': 11.132058, 'test_loss': 10.403868}}
|
|
2024-11-13 17:41:34,854 (client:354) INFO: {'Role': 'Client #6', 'Round': 39, 'Results_raw': {'train_loss': 9.079449, 'val_loss': 9.19271, 'test_loss': 9.165524}}
|
|
2024-11-13 17:42:10,760 (client:354) INFO: {'Role': 'Client #1', 'Round': 39, 'Results_raw': {'train_loss': 8.782146, 'val_loss': 8.081097, 'test_loss': 8.456163}}
|
|
2024-11-13 17:42:43,654 (client:354) INFO: {'Role': 'Client #9', 'Round': 39, 'Results_raw': {'train_loss': 13.11197, 'val_loss': 15.492715, 'test_loss': 12.065084}}
|
|
2024-11-13 17:42:43,657 (server:615) INFO: {'Role': 'Server #', 'Round': 38, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.463414), 'test_loss': np.float64(57951.218097), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.851999), 'val_loss': np.float64(62839.037094)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.463414), 'test_loss': np.float64(57951.218097), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.851999), 'val_loss': np.float64(62839.037094)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(8.298054), 'test_avg_loss_bottom_decile': np.float64(8.47113), 'test_avg_loss_top_decile': np.float64(32.671063), 'test_avg_loss_min': np.float64(8.394775), 'test_avg_loss_max': np.float64(32.671063), 'test_avg_loss_bottom10%': np.float64(8.394775), 'test_avg_loss_top10%': np.float64(32.671063), 'test_avg_loss_cos1': np.float64(0.892983), 'test_avg_loss_entropy': np.float64(2.18473), 'test_loss_std': np.float64(29209.148656), 'test_loss_bottom_decile': np.float64(29818.379333), 'test_loss_top_decile': np.float64(115002.142029), 'test_loss_min': np.float64(29549.609497), 'test_loss_max': np.float64(115002.142029), 'test_loss_bottom10%': np.float64(29549.609497), 'test_loss_top10%': np.float64(115002.142029), 'test_loss_cos1': np.float64(0.892983), 'test_loss_entropy': np.float64(2.18473), 'val_avg_loss_std': np.float64(8.822587), 'val_avg_loss_bottom_decile': np.float64(8.80197), 'val_avg_loss_top_decile': np.float64(33.424923), 'val_avg_loss_min': np.float64(8.611873), 'val_avg_loss_max': np.float64(33.424923), 'val_avg_loss_bottom10%': np.float64(8.611873), 'val_avg_loss_top10%': np.float64(33.424923), 'val_avg_loss_cos1': np.float64(0.896495), 'val_avg_loss_entropy': np.float64(2.186654), 'val_loss_std': np.float64(31055.504706), 'val_loss_bottom_decile': np.float64(30982.934357), 'val_loss_top_decile': np.float64(117655.727905), 'val_loss_min': np.float64(30313.791351), 'val_loss_max': np.float64(117655.727905), 'val_loss_bottom10%': np.float64(30313.791351), 'val_loss_top10%': np.float64(117655.727905), 'val_loss_cos1': np.float64(0.896495), 'val_loss_entropy': np.float64(2.186654)}}
|
|
2024-11-13 17:42:43,693 (server:353) INFO: Server: Starting evaluation at the end of round 39.
|
|
2024-11-13 17:42:43,694 (server:359) INFO: ----------- Starting a new training round (Round #40) -------------
|
|
2024-11-13 17:44:25,550 (client:354) INFO: {'Role': 'Client #3', 'Round': 40, 'Results_raw': {'train_loss': 9.010126, 'val_loss': 8.630851, 'test_loss': 9.08981}}
|
|
2024-11-13 17:45:00,834 (client:354) INFO: {'Role': 'Client #5', 'Round': 40, 'Results_raw': {'train_loss': 5.936775, 'val_loss': 5.845574, 'test_loss': 5.783337}}
|
|
2024-11-13 17:45:35,711 (client:354) INFO: {'Role': 'Client #4', 'Round': 40, 'Results_raw': {'train_loss': 7.421008, 'val_loss': 6.554647, 'test_loss': 6.619167}}
|
|
2024-11-13 17:46:18,385 (client:354) INFO: {'Role': 'Client #6', 'Round': 40, 'Results_raw': {'train_loss': 9.150107, 'val_loss': 8.995218, 'test_loss': 9.028558}}
|
|
2024-11-13 17:46:55,564 (client:354) INFO: {'Role': 'Client #7', 'Round': 40, 'Results_raw': {'train_loss': 11.164421, 'val_loss': 10.940601, 'test_loss': 10.086123}}
|
|
2024-11-13 17:47:30,564 (client:354) INFO: {'Role': 'Client #2', 'Round': 40, 'Results_raw': {'train_loss': 10.822835, 'val_loss': 10.958761, 'test_loss': 10.108526}}
|
|
2024-11-13 17:48:04,923 (client:354) INFO: {'Role': 'Client #9', 'Round': 40, 'Results_raw': {'train_loss': 13.058375, 'val_loss': 15.19012, 'test_loss': 11.828844}}
|
|
2024-11-13 17:48:39,019 (client:354) INFO: {'Role': 'Client #1', 'Round': 40, 'Results_raw': {'train_loss': 8.766492, 'val_loss': 8.086887, 'test_loss': 8.49565}}
|
|
2024-11-13 17:49:14,097 (client:354) INFO: {'Role': 'Client #8', 'Round': 40, 'Results_raw': {'train_loss': 7.572946, 'val_loss': 15.024522, 'test_loss': 8.081225}}
|
|
2024-11-13 17:49:48,169 (client:354) INFO: {'Role': 'Client #10', 'Round': 40, 'Results_raw': {'train_loss': 15.125695, 'val_loss': 15.791911, 'test_loss': 15.256525}}
|
|
2024-11-13 17:49:48,172 (server:615) INFO: {'Role': 'Server #', 'Round': 39, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.350905), 'test_loss': np.float64(57555.18385), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.736327), 'val_loss': np.float64(62431.872208)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.350905), 'test_loss': np.float64(57555.18385), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.736327), 'val_loss': np.float64(62431.872208)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(8.153575), 'test_avg_loss_bottom_decile': np.float64(8.485041), 'test_avg_loss_top_decile': np.float64(32.166764), 'test_avg_loss_min': np.float64(8.450713), 'test_avg_loss_max': np.float64(32.166764), 'test_avg_loss_bottom10%': np.float64(8.450713), 'test_avg_loss_top10%': np.float64(32.166764), 'test_avg_loss_cos1': np.float64(0.894906), 'test_avg_loss_entropy': np.float64(2.187424), 'test_loss_std': np.float64(28700.582708), 'test_loss_bottom_decile': np.float64(29867.345581), 'test_loss_top_decile': np.float64(113227.00769), 'test_loss_min': np.float64(29746.50882), 'test_loss_max': np.float64(113227.00769), 'test_loss_bottom10%': np.float64(29746.50882), 'test_loss_top10%': np.float64(113227.00769), 'test_loss_cos1': np.float64(0.894906), 'test_loss_entropy': np.float64(2.187424), 'val_avg_loss_std': np.float64(8.676442), 'val_avg_loss_bottom_decile': np.float64(8.863629), 'val_avg_loss_top_decile': np.float64(33.378618), 'val_avg_loss_min': np.float64(8.62529), 'val_avg_loss_max': np.float64(33.378618), 'val_avg_loss_bottom10%': np.float64(8.62529), 'val_avg_loss_top10%': np.float64(33.378618), 'val_avg_loss_cos1': np.float64(0.898277), 'val_avg_loss_entropy': np.float64(2.189119), 'val_loss_std': np.float64(30541.076993), 'val_loss_bottom_decile': np.float64(31199.972839), 'val_loss_top_decile': np.float64(117492.736328), 'val_loss_min': np.float64(30361.021545), 'val_loss_max': np.float64(117492.736328), 'val_loss_bottom10%': np.float64(30361.021545), 'val_loss_top10%': np.float64(117492.736328), 'val_loss_cos1': np.float64(0.898277), 'val_loss_entropy': np.float64(2.189119)}}
|
|
2024-11-13 17:49:48,208 (server:353) INFO: Server: Starting evaluation at the end of round 40.
|
|
2024-11-13 17:49:48,208 (server:359) INFO: ----------- Starting a new training round (Round #41) -------------
|
|
2024-11-13 17:51:19,819 (client:354) INFO: {'Role': 'Client #6', 'Round': 41, 'Results_raw': {'train_loss': 9.129641, 'val_loss': 9.131488, 'test_loss': 9.171169}}
|
|
2024-11-13 17:51:53,494 (client:354) INFO: {'Role': 'Client #4', 'Round': 41, 'Results_raw': {'train_loss': 7.358833, 'val_loss': 6.655798, 'test_loss': 6.768513}}
|
|
2024-11-13 17:52:27,698 (client:354) INFO: {'Role': 'Client #9', 'Round': 41, 'Results_raw': {'train_loss': 13.325793, 'val_loss': 15.539313, 'test_loss': 12.173968}}
|
|
2024-11-13 17:53:01,491 (client:354) INFO: {'Role': 'Client #8', 'Round': 41, 'Results_raw': {'train_loss': 7.495086, 'val_loss': 14.92229, 'test_loss': 7.840364}}
|
|
2024-11-13 17:53:34,794 (client:354) INFO: {'Role': 'Client #7', 'Round': 41, 'Results_raw': {'train_loss': 11.19919, 'val_loss': 10.910097, 'test_loss': 10.133124}}
|
|
2024-11-13 17:54:07,518 (client:354) INFO: {'Role': 'Client #1', 'Round': 41, 'Results_raw': {'train_loss': 8.763632, 'val_loss': 8.058222, 'test_loss': 8.478825}}
|
|
2024-11-13 17:54:41,782 (client:354) INFO: {'Role': 'Client #10', 'Round': 41, 'Results_raw': {'train_loss': 15.090594, 'val_loss': 15.24166, 'test_loss': 14.830913}}
|
|
2024-11-13 17:55:16,374 (client:354) INFO: {'Role': 'Client #3', 'Round': 41, 'Results_raw': {'train_loss': 8.970808, 'val_loss': 8.603624, 'test_loss': 9.072321}}
|
|
2024-11-13 17:55:50,542 (client:354) INFO: {'Role': 'Client #5', 'Round': 41, 'Results_raw': {'train_loss': 5.954152, 'val_loss': 6.051834, 'test_loss': 5.791005}}
|
|
2024-11-13 17:56:25,300 (client:354) INFO: {'Role': 'Client #2', 'Round': 41, 'Results_raw': {'train_loss': 10.87776, 'val_loss': 10.975992, 'test_loss': 10.331369}}
|
|
2024-11-13 17:56:25,303 (server:615) INFO: {'Role': 'Server #', 'Round': 40, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.751924), 'test_loss': np.float64(58966.772229), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(18.178363), 'val_loss': np.float64(63987.836307)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.751924), 'test_loss': np.float64(58966.772229), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(18.178363), 'val_loss': np.float64(63987.836307)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(8.668569), 'test_avg_loss_bottom_decile': np.float64(8.565187), 'test_avg_loss_top_decile': np.float64(33.625067), 'test_avg_loss_min': np.float64(8.398298), 'test_avg_loss_max': np.float64(33.625067), 'test_avg_loss_bottom10%': np.float64(8.398298), 'test_avg_loss_top10%': np.float64(33.625067), 'test_avg_loss_cos1': np.float64(0.888136), 'test_avg_loss_entropy': np.float64(2.178982), 'test_loss_std': np.float64(30513.362081), 'test_loss_bottom_decile': np.float64(30149.456696), 'test_loss_top_decile': np.float64(118360.234741), 'test_loss_min': np.float64(29562.010223), 'test_loss_max': np.float64(118360.234741), 'test_loss_bottom10%': np.float64(29562.010223), 'test_loss_top10%': np.float64(118360.234741), 'test_loss_cos1': np.float64(0.888136), 'test_loss_entropy': np.float64(2.178982), 'val_avg_loss_std': np.float64(9.215767), 'val_avg_loss_bottom_decile': np.float64(8.786038), 'val_avg_loss_top_decile': np.float64(34.78049), 'val_avg_loss_min': np.float64(8.696299), 'val_avg_loss_max': np.float64(34.78049), 'val_avg_loss_bottom10%': np.float64(8.696299), 'val_avg_loss_top10%': np.float64(34.78049), 'val_avg_loss_cos1': np.float64(0.891929), 'val_avg_loss_entropy': np.float64(2.181131), 'val_loss_std': np.float64(32439.499541), 'val_loss_bottom_decile': np.float64(30926.853058), 'val_loss_top_decile': np.float64(122427.326477), 'val_loss_min': np.float64(30610.972198), 'val_loss_max': np.float64(122427.326477), 'val_loss_bottom10%': np.float64(30610.972198), 'val_loss_top10%': np.float64(122427.326477), 'val_loss_cos1': np.float64(0.891929), 'val_loss_entropy': np.float64(2.181131)}}
|
|
2024-11-13 17:56:25,340 (server:353) INFO: Server: Starting evaluation at the end of round 41.
|
|
2024-11-13 17:56:25,341 (server:359) INFO: ----------- Starting a new training round (Round #42) -------------
|
|
2024-11-13 17:57:56,422 (client:354) INFO: {'Role': 'Client #3', 'Round': 42, 'Results_raw': {'train_loss': 8.991509, 'val_loss': 8.568629, 'test_loss': 9.038921}}
|
|
2024-11-13 17:58:30,856 (client:354) INFO: {'Role': 'Client #6', 'Round': 42, 'Results_raw': {'train_loss': 9.013424, 'val_loss': 9.102457, 'test_loss': 9.207986}}
|
|
2024-11-13 17:59:05,091 (client:354) INFO: {'Role': 'Client #10', 'Round': 42, 'Results_raw': {'train_loss': 15.245894, 'val_loss': 15.74945, 'test_loss': 15.322959}}
|
|
2024-11-13 17:59:40,275 (client:354) INFO: {'Role': 'Client #8', 'Round': 42, 'Results_raw': {'train_loss': 7.523144, 'val_loss': 15.807391, 'test_loss': 7.927567}}
|
|
2024-11-13 18:00:16,413 (client:354) INFO: {'Role': 'Client #7', 'Round': 42, 'Results_raw': {'train_loss': 11.268959, 'val_loss': 10.848251, 'test_loss': 10.033245}}
|
|
2024-11-13 18:00:50,767 (client:354) INFO: {'Role': 'Client #4', 'Round': 42, 'Results_raw': {'train_loss': 7.344146, 'val_loss': 6.574051, 'test_loss': 6.632153}}
|
|
2024-11-13 18:01:23,701 (client:354) INFO: {'Role': 'Client #5', 'Round': 42, 'Results_raw': {'train_loss': 6.003516, 'val_loss': 5.94609, 'test_loss': 5.948552}}
|
|
2024-11-13 18:01:56,040 (client:354) INFO: {'Role': 'Client #2', 'Round': 42, 'Results_raw': {'train_loss': 10.638062, 'val_loss': 10.949241, 'test_loss': 10.144436}}
|
|
2024-11-13 18:02:28,434 (client:354) INFO: {'Role': 'Client #9', 'Round': 42, 'Results_raw': {'train_loss': 13.067889, 'val_loss': 15.527743, 'test_loss': 12.116862}}
|
|
2024-11-13 18:03:00,768 (client:354) INFO: {'Role': 'Client #1', 'Round': 42, 'Results_raw': {'train_loss': 8.757243, 'val_loss': 8.125206, 'test_loss': 8.476642}}
|
|
2024-11-13 18:03:00,771 (server:615) INFO: {'Role': 'Server #', 'Round': 41, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.532567), 'test_loss': np.float64(58194.635233), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.954219), 'val_loss': np.float64(63198.852612)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.532567), 'test_loss': np.float64(58194.635233), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.954219), 'val_loss': np.float64(63198.852612)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(8.305239), 'test_avg_loss_bottom_decile': np.float64(8.474626), 'test_avg_loss_top_decile': np.float64(32.822395), 'test_avg_loss_min': np.float64(8.444365), 'test_avg_loss_max': np.float64(32.822395), 'test_avg_loss_bottom10%': np.float64(8.444365), 'test_avg_loss_top10%': np.float64(32.822395), 'test_avg_loss_cos1': np.float64(0.893583), 'test_avg_loss_entropy': np.float64(2.185264), 'test_loss_std': np.float64(29234.442992), 'test_loss_bottom_decile': np.float64(29830.683685), 'test_loss_top_decile': np.float64(115534.83197), 'test_loss_min': np.float64(29724.165039), 'test_loss_max': np.float64(115534.83197), 'test_loss_bottom10%': np.float64(29724.165039), 'test_loss_top10%': np.float64(115534.83197), 'test_loss_cos1': np.float64(0.893583), 'test_loss_entropy': np.float64(2.185264), 'val_avg_loss_std': np.float64(8.832111), 'val_avg_loss_bottom_decile': np.float64(8.8495), 'val_avg_loss_top_decile': np.float64(33.357742), 'val_avg_loss_min': np.float64(8.616382), 'val_avg_loss_max': np.float64(33.357742), 'val_avg_loss_bottom10%': np.float64(8.616382), 'val_avg_loss_top10%': np.float64(33.357742), 'val_avg_loss_cos1': np.float64(0.897307), 'val_avg_loss_entropy': np.float64(2.187278), 'val_loss_std': np.float64(31089.029732), 'val_loss_bottom_decile': np.float64(31150.238831), 'val_loss_top_decile': np.float64(117419.251404), 'val_loss_min': np.float64(30329.664154), 'val_loss_max': np.float64(117419.251404), 'val_loss_bottom10%': np.float64(30329.664154), 'val_loss_top10%': np.float64(117419.251404), 'val_loss_cos1': np.float64(0.897307), 'val_loss_entropy': np.float64(2.187278)}}
|
|
2024-11-13 18:03:00,798 (server:353) INFO: Server: Starting evaluation at the end of round 42.
|
|
2024-11-13 18:03:00,798 (server:359) INFO: ----------- Starting a new training round (Round #43) -------------
|
|
2024-11-13 18:04:32,096 (client:354) INFO: {'Role': 'Client #9', 'Round': 43, 'Results_raw': {'train_loss': 12.981949, 'val_loss': 15.460064, 'test_loss': 11.984681}}
|
|
2024-11-13 18:05:05,905 (client:354) INFO: {'Role': 'Client #3', 'Round': 43, 'Results_raw': {'train_loss': 8.984678, 'val_loss': 8.591723, 'test_loss': 9.067837}}
|
|
2024-11-13 18:05:40,042 (client:354) INFO: {'Role': 'Client #2', 'Round': 43, 'Results_raw': {'train_loss': 10.951833, 'val_loss': 11.019365, 'test_loss': 10.338286}}
|
|
2024-11-13 18:06:14,713 (client:354) INFO: {'Role': 'Client #1', 'Round': 43, 'Results_raw': {'train_loss': 8.775514, 'val_loss': 8.114692, 'test_loss': 8.495087}}
|
|
2024-11-13 18:06:48,930 (client:354) INFO: {'Role': 'Client #10', 'Round': 43, 'Results_raw': {'train_loss': 15.300495, 'val_loss': 15.681769, 'test_loss': 14.907079}}
|
|
2024-11-13 18:07:23,678 (client:354) INFO: {'Role': 'Client #6', 'Round': 43, 'Results_raw': {'train_loss': 9.03837, 'val_loss': 9.044973, 'test_loss': 9.105313}}
|
|
2024-11-13 18:08:00,311 (client:354) INFO: {'Role': 'Client #8', 'Round': 43, 'Results_raw': {'train_loss': 7.529242, 'val_loss': 13.925559, 'test_loss': 7.923673}}
|
|
2024-11-13 18:08:35,625 (client:354) INFO: {'Role': 'Client #7', 'Round': 43, 'Results_raw': {'train_loss': 11.16407, 'val_loss': 11.063465, 'test_loss': 10.160954}}
|
|
2024-11-13 18:09:10,198 (client:354) INFO: {'Role': 'Client #4', 'Round': 43, 'Results_raw': {'train_loss': 7.353148, 'val_loss': 6.747242, 'test_loss': 6.849517}}
|
|
2024-11-13 18:09:43,828 (client:354) INFO: {'Role': 'Client #5', 'Round': 43, 'Results_raw': {'train_loss': 5.995182, 'val_loss': 6.077018, 'test_loss': 5.901054}}
|
|
2024-11-13 18:09:43,830 (server:615) INFO: {'Role': 'Server #', 'Round': 42, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.141033), 'test_loss': np.float64(56816.437695), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.544273), 'val_loss': np.float64(61755.840173)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.141033), 'test_loss': np.float64(56816.437695), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.544273), 'val_loss': np.float64(61755.840173)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(8.022668), 'test_avg_loss_bottom_decile': np.float64(8.414162), 'test_avg_loss_top_decile': np.float64(31.822381), 'test_avg_loss_min': np.float64(8.352653), 'test_avg_loss_max': np.float64(31.822381), 'test_avg_loss_bottom10%': np.float64(8.352653), 'test_avg_loss_top10%': np.float64(31.822381), 'test_avg_loss_cos1': np.float64(0.895486), 'test_avg_loss_entropy': np.float64(2.188215), 'test_loss_std': np.float64(28239.792733), 'test_loss_bottom_decile': np.float64(29617.8508), 'test_loss_top_decile': np.float64(112014.780334), 'test_loss_min': np.float64(29401.338684), 'test_loss_max': np.float64(112014.780334), 'test_loss_bottom10%': np.float64(29401.338684), 'test_loss_top10%': np.float64(112014.780334), 'test_loss_cos1': np.float64(0.895486), 'test_loss_entropy': np.float64(2.188215), 'val_avg_loss_std': np.float64(8.546043), 'val_avg_loss_bottom_decile': np.float64(8.750971), 'val_avg_loss_top_decile': np.float64(32.890279), 'val_avg_loss_min': np.float64(8.545873), 'val_avg_loss_max': np.float64(32.890279), 'val_avg_loss_bottom10%': np.float64(8.545873), 'val_avg_loss_top10%': np.float64(32.890279), 'val_avg_loss_cos1': np.float64(0.899013), 'val_avg_loss_entropy': np.float64(2.189888), 'val_loss_std': np.float64(30082.072268), 'val_loss_bottom_decile': np.float64(30803.41684), 'val_loss_top_decile': np.float64(115773.781677), 'val_loss_min': np.float64(30081.472656), 'val_loss_max': np.float64(115773.781677), 'val_loss_bottom10%': np.float64(30081.472656), 'val_loss_top10%': np.float64(115773.781677), 'val_loss_cos1': np.float64(0.899013), 'val_loss_entropy': np.float64(2.189888)}}
|
|
2024-11-13 18:09:43,861 (server:353) INFO: Server: Starting evaluation at the end of round 43.
|
|
2024-11-13 18:09:43,861 (server:359) INFO: ----------- Starting a new training round (Round #44) -------------
|
|
2024-11-13 18:11:15,487 (client:354) INFO: {'Role': 'Client #1', 'Round': 44, 'Results_raw': {'train_loss': 8.74994, 'val_loss': 8.103972, 'test_loss': 8.491905}}
|
|
2024-11-13 18:11:50,136 (client:354) INFO: {'Role': 'Client #8', 'Round': 44, 'Results_raw': {'train_loss': 7.509122, 'val_loss': 14.892252, 'test_loss': 8.227967}}
|
|
2024-11-13 18:12:24,646 (client:354) INFO: {'Role': 'Client #4', 'Round': 44, 'Results_raw': {'train_loss': 7.356265, 'val_loss': 6.49016, 'test_loss': 6.565558}}
|
|
2024-11-13 18:12:57,857 (client:354) INFO: {'Role': 'Client #7', 'Round': 44, 'Results_raw': {'train_loss': 11.039812, 'val_loss': 11.058227, 'test_loss': 10.179703}}
|
|
2024-11-13 18:13:31,807 (client:354) INFO: {'Role': 'Client #6', 'Round': 44, 'Results_raw': {'train_loss': 9.046841, 'val_loss': 8.999801, 'test_loss': 9.161296}}
|
|
2024-11-13 18:14:05,339 (client:354) INFO: {'Role': 'Client #5', 'Round': 44, 'Results_raw': {'train_loss': 5.923569, 'val_loss': 5.964666, 'test_loss': 5.94592}}
|
|
2024-11-13 18:14:38,587 (client:354) INFO: {'Role': 'Client #10', 'Round': 44, 'Results_raw': {'train_loss': 15.059961, 'val_loss': 15.171197, 'test_loss': 14.692659}}
|
|
2024-11-13 18:15:14,083 (client:354) INFO: {'Role': 'Client #9', 'Round': 44, 'Results_raw': {'train_loss': 13.209562, 'val_loss': 15.247628, 'test_loss': 11.77158}}
|
|
2024-11-13 18:15:50,812 (client:354) INFO: {'Role': 'Client #2', 'Round': 44, 'Results_raw': {'train_loss': 10.631803, 'val_loss': 10.730655, 'test_loss': 9.928942}}
|
|
2024-11-13 18:16:24,863 (client:354) INFO: {'Role': 'Client #3', 'Round': 44, 'Results_raw': {'train_loss': 8.978052, 'val_loss': 8.565991, 'test_loss': 9.042029}}
|
|
2024-11-13 18:16:24,865 (server:615) INFO: {'Role': 'Server #', 'Round': 43, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.092591), 'test_loss': np.float64(56645.920331), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.464534), 'val_loss': np.float64(61475.158414)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.092591), 'test_loss': np.float64(56645.920331), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.464534), 'val_loss': np.float64(61475.158414)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(7.872879), 'test_avg_loss_bottom_decile': np.float64(8.364827), 'test_avg_loss_top_decile': np.float64(31.208122), 'test_avg_loss_min': np.float64(8.315671), 'test_avg_loss_max': np.float64(31.208122), 'test_avg_loss_bottom10%': np.float64(8.315671), 'test_avg_loss_top10%': np.float64(31.208122), 'test_avg_loss_cos1': np.float64(0.898266), 'test_avg_loss_entropy': np.float64(2.191056), 'test_loss_std': np.float64(27712.535016), 'test_loss_bottom_decile': np.float64(29444.19104), 'test_loss_top_decile': np.float64(109852.587769), 'test_loss_min': np.float64(29271.162354), 'test_loss_max': np.float64(109852.587769), 'test_loss_bottom10%': np.float64(29271.162354), 'test_loss_top10%': np.float64(109852.587769), 'test_loss_cos1': np.float64(0.898266), 'test_loss_entropy': np.float64(2.191056), 'val_avg_loss_std': np.float64(8.417021), 'val_avg_loss_bottom_decile': np.float64(8.701402), 'val_avg_loss_top_decile': np.float64(32.628928), 'val_avg_loss_min': np.float64(8.507246), 'val_avg_loss_max': np.float64(32.628928), 'val_avg_loss_bottom10%': np.float64(8.507246), 'val_avg_loss_top10%': np.float64(32.628928), 'val_avg_loss_cos1': np.float64(0.900837), 'val_avg_loss_entropy': np.float64(2.19189), 'val_loss_std': np.float64(29627.913808), 'val_loss_bottom_decile': np.float64(30628.933624), 'val_loss_top_decile': np.float64(114853.825684), 'val_loss_min': np.float64(29945.504364), 'val_loss_max': np.float64(114853.825684), 'val_loss_bottom10%': np.float64(29945.504364), 'val_loss_top10%': np.float64(114853.825684), 'val_loss_cos1': np.float64(0.900837), 'val_loss_entropy': np.float64(2.19189)}}
|
|
2024-11-13 18:16:24,892 (server:353) INFO: Server: Starting evaluation at the end of round 44.
|
|
2024-11-13 18:16:24,892 (server:359) INFO: ----------- Starting a new training round (Round #45) -------------
|
|
2024-11-13 18:18:19,434 (client:354) INFO: {'Role': 'Client #4', 'Round': 45, 'Results_raw': {'train_loss': 7.324245, 'val_loss': 6.580118, 'test_loss': 6.682375}}
|
|
2024-11-13 18:19:21,211 (client:354) INFO: {'Role': 'Client #7', 'Round': 45, 'Results_raw': {'train_loss': 11.040571, 'val_loss': 10.913981, 'test_loss': 10.048634}}
|
|
2024-11-13 18:20:23,307 (client:354) INFO: {'Role': 'Client #5', 'Round': 45, 'Results_raw': {'train_loss': 5.910217, 'val_loss': 5.922751, 'test_loss': 5.843053}}
|
|
2024-11-13 18:21:26,130 (client:354) INFO: {'Role': 'Client #10', 'Round': 45, 'Results_raw': {'train_loss': 15.209691, 'val_loss': 15.483388, 'test_loss': 14.936072}}
|
|
2024-11-13 18:22:30,041 (client:354) INFO: {'Role': 'Client #9', 'Round': 45, 'Results_raw': {'train_loss': 13.213985, 'val_loss': 15.591513, 'test_loss': 12.057922}}
|
|
2024-11-13 18:23:34,329 (client:354) INFO: {'Role': 'Client #2', 'Round': 45, 'Results_raw': {'train_loss': 10.807931, 'val_loss': 11.237676, 'test_loss': 10.221797}}
|
|
2024-11-13 18:24:38,851 (client:354) INFO: {'Role': 'Client #1', 'Round': 45, 'Results_raw': {'train_loss': 8.744491, 'val_loss': 8.109642, 'test_loss': 8.484899}}
|
|
2024-11-13 18:25:41,369 (client:354) INFO: {'Role': 'Client #8', 'Round': 45, 'Results_raw': {'train_loss': 7.513005, 'val_loss': 14.912095, 'test_loss': 7.936684}}
|
|
2024-11-13 18:26:44,176 (client:354) INFO: {'Role': 'Client #6', 'Round': 45, 'Results_raw': {'train_loss': 9.013711, 'val_loss': 8.978582, 'test_loss': 9.086498}}
|
|
2024-11-13 18:27:46,891 (client:354) INFO: {'Role': 'Client #3', 'Round': 45, 'Results_raw': {'train_loss': 9.005387, 'val_loss': 8.637916, 'test_loss': 9.118855}}
|
|
2024-11-13 18:27:46,895 (server:615) INFO: {'Role': 'Server #', 'Round': 44, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.352896), 'test_loss': np.float64(57562.193762), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.76897), 'val_loss': np.float64(62546.774976)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.352896), 'test_loss': np.float64(57562.193762), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.76897), 'val_loss': np.float64(62546.774976)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(8.186465), 'test_avg_loss_bottom_decile': np.float64(8.427317), 'test_avg_loss_top_decile': np.float64(32.143256), 'test_avg_loss_min': np.float64(8.378686), 'test_avg_loss_max': np.float64(32.143256), 'test_avg_loss_bottom10%': np.float64(8.378686), 'test_avg_loss_top10%': np.float64(32.143256), 'test_avg_loss_cos1': np.float64(0.894208), 'test_avg_loss_entropy': np.float64(2.186299), 'test_loss_std': np.float64(28816.358006), 'test_loss_bottom_decile': np.float64(29664.155884), 'test_loss_top_decile': np.float64(113144.262146), 'test_loss_min': np.float64(29492.973877), 'test_loss_max': np.float64(113144.262146), 'test_loss_bottom10%': np.float64(29492.973877), 'test_loss_top10%': np.float64(113144.262146), 'test_loss_cos1': np.float64(0.894208), 'test_loss_entropy': np.float64(2.186299), 'val_avg_loss_std': np.float64(8.73982), 'val_avg_loss_bottom_decile': np.float64(8.775522), 'val_avg_loss_top_decile': np.float64(33.640703), 'val_avg_loss_min': np.float64(8.575243), 'val_avg_loss_max': np.float64(33.640703), 'val_avg_loss_bottom10%': np.float64(8.575243), 'val_avg_loss_top10%': np.float64(33.640703), 'val_avg_loss_cos1': np.float64(0.89733), 'val_avg_loss_entropy': np.float64(2.187683), 'val_loss_std': np.float64(30764.168106), 'val_loss_bottom_decile': np.float64(30889.836975), 'val_loss_top_decile': np.float64(118415.273926), 'val_loss_min': np.float64(30184.854004), 'val_loss_max': np.float64(118415.273926), 'val_loss_bottom10%': np.float64(30184.854004), 'val_loss_top10%': np.float64(118415.273926), 'val_loss_cos1': np.float64(0.89733), 'val_loss_entropy': np.float64(2.187683)}}
|
|
2024-11-13 18:27:46,937 (server:353) INFO: Server: Starting evaluation at the end of round 45.
|
|
2024-11-13 18:27:46,937 (server:359) INFO: ----------- Starting a new training round (Round #46) -------------
|
|
2024-11-13 18:31:02,384 (client:354) INFO: {'Role': 'Client #10', 'Round': 46, 'Results_raw': {'train_loss': 15.165721, 'val_loss': 16.790606, 'test_loss': 16.514747}}
|
|
2024-11-13 18:32:04,028 (client:354) INFO: {'Role': 'Client #8', 'Round': 46, 'Results_raw': {'train_loss': 7.498813, 'val_loss': 14.351305, 'test_loss': 7.827206}}
|
|
2024-11-13 18:33:06,711 (client:354) INFO: {'Role': 'Client #4', 'Round': 46, 'Results_raw': {'train_loss': 7.286168, 'val_loss': 6.54316, 'test_loss': 6.640382}}
|
|
2024-11-13 18:34:09,292 (client:354) INFO: {'Role': 'Client #5', 'Round': 46, 'Results_raw': {'train_loss': 5.956332, 'val_loss': 6.099863, 'test_loss': 6.060083}}
|
|
2024-11-13 18:35:10,466 (client:354) INFO: {'Role': 'Client #3', 'Round': 46, 'Results_raw': {'train_loss': 8.954015, 'val_loss': 8.752604, 'test_loss': 9.261709}}
|
|
2024-11-13 18:36:09,753 (client:354) INFO: {'Role': 'Client #2', 'Round': 46, 'Results_raw': {'train_loss': 10.574655, 'val_loss': 10.865297, 'test_loss': 10.078963}}
|
|
2024-11-13 18:37:09,358 (client:354) INFO: {'Role': 'Client #6', 'Round': 46, 'Results_raw': {'train_loss': 8.985209, 'val_loss': 9.07229, 'test_loss': 9.216372}}
|
|
2024-11-13 18:38:11,588 (client:354) INFO: {'Role': 'Client #7', 'Round': 46, 'Results_raw': {'train_loss': 11.078749, 'val_loss': 10.89884, 'test_loss': 10.100484}}
|
|
2024-11-13 18:39:13,422 (client:354) INFO: {'Role': 'Client #1', 'Round': 46, 'Results_raw': {'train_loss': 8.742681, 'val_loss': 8.145767, 'test_loss': 8.544791}}
|
|
2024-11-13 18:40:15,760 (client:354) INFO: {'Role': 'Client #9', 'Round': 46, 'Results_raw': {'train_loss': 13.503494, 'val_loss': 15.525974, 'test_loss': 12.169039}}
|
|
2024-11-13 18:40:15,765 (server:615) INFO: {'Role': 'Server #', 'Round': 45, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.421516), 'test_loss': np.float64(57803.735712), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.798812), 'val_loss': np.float64(62651.819101)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.421516), 'test_loss': np.float64(57803.735712), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.798812), 'val_loss': np.float64(62651.819101)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(8.180059), 'test_avg_loss_bottom_decile': np.float64(8.454981), 'test_avg_loss_top_decile': np.float64(31.897111), 'test_avg_loss_min': np.float64(8.399866), 'test_avg_loss_max': np.float64(31.897111), 'test_avg_loss_bottom10%': np.float64(8.399866), 'test_avg_loss_top10%': np.float64(31.897111), 'test_avg_loss_cos1': np.float64(0.895096), 'test_avg_loss_entropy': np.float64(2.186981), 'test_loss_std': np.float64(28793.806197), 'test_loss_bottom_decile': np.float64(29761.534607), 'test_loss_top_decile': np.float64(112277.830994), 'test_loss_min': np.float64(29567.527588), 'test_loss_max': np.float64(112277.830994), 'test_loss_bottom10%': np.float64(29567.527588), 'test_loss_top10%': np.float64(112277.830994), 'test_loss_cos1': np.float64(0.895096), 'test_loss_entropy': np.float64(2.186981), 'val_avg_loss_std': np.float64(8.725735), 'val_avg_loss_bottom_decile': np.float64(8.778565), 'val_avg_loss_top_decile': np.float64(33.728619), 'val_avg_loss_min': np.float64(8.58126), 'val_avg_loss_max': np.float64(33.728619), 'val_avg_loss_bottom10%': np.float64(8.58126), 'val_avg_loss_top10%': np.float64(33.728619), 'val_avg_loss_cos1': np.float64(0.897904), 'val_avg_loss_entropy': np.float64(2.188186), 'val_loss_std': np.float64(30714.585455), 'val_loss_bottom_decile': np.float64(30900.548981), 'val_loss_top_decile': np.float64(118724.739868), 'val_loss_min': np.float64(30206.034424), 'val_loss_max': np.float64(118724.739868), 'val_loss_bottom10%': np.float64(30206.034424), 'val_loss_top10%': np.float64(118724.739868), 'val_loss_cos1': np.float64(0.897904), 'val_loss_entropy': np.float64(2.188186)}}
|
|
2024-11-13 18:40:15,802 (server:353) INFO: Server: Starting evaluation at the end of round 46.
|
|
2024-11-13 18:40:15,803 (server:359) INFO: ----------- Starting a new training round (Round #47) -------------
|
|
2024-11-13 18:43:29,134 (client:354) INFO: {'Role': 'Client #7', 'Round': 47, 'Results_raw': {'train_loss': 11.253191, 'val_loss': 10.900487, 'test_loss': 10.074516}}
|
|
2024-11-13 18:44:32,075 (client:354) INFO: {'Role': 'Client #5', 'Round': 47, 'Results_raw': {'train_loss': 5.922961, 'val_loss': 6.079357, 'test_loss': 6.054477}}
|
|
2024-11-13 18:45:33,941 (client:354) INFO: {'Role': 'Client #3', 'Round': 47, 'Results_raw': {'train_loss': 8.95796, 'val_loss': 8.559512, 'test_loss': 9.031238}}
|
|
2024-11-13 18:46:35,618 (client:354) INFO: {'Role': 'Client #8', 'Round': 47, 'Results_raw': {'train_loss': 7.49659, 'val_loss': 15.058318, 'test_loss': 8.108295}}
|
|
2024-11-13 18:47:38,065 (client:354) INFO: {'Role': 'Client #2', 'Round': 47, 'Results_raw': {'train_loss': 10.682518, 'val_loss': 10.969687, 'test_loss': 10.330346}}
|
|
2024-11-13 18:48:39,502 (client:354) INFO: {'Role': 'Client #4', 'Round': 47, 'Results_raw': {'train_loss': 7.302476, 'val_loss': 6.621818, 'test_loss': 6.701559}}
|
|
2024-11-13 18:49:40,187 (client:354) INFO: {'Role': 'Client #1', 'Round': 47, 'Results_raw': {'train_loss': 8.724366, 'val_loss': 8.08582, 'test_loss': 8.500081}}
|
|
2024-11-13 18:50:41,792 (client:354) INFO: {'Role': 'Client #10', 'Round': 47, 'Results_raw': {'train_loss': 14.840699, 'val_loss': 15.898481, 'test_loss': 15.506053}}
|
|
2024-11-13 18:51:44,267 (client:354) INFO: {'Role': 'Client #9', 'Round': 47, 'Results_raw': {'train_loss': 12.712216, 'val_loss': 15.04475, 'test_loss': 11.721521}}
|
|
2024-11-13 18:52:45,927 (client:354) INFO: {'Role': 'Client #6', 'Round': 47, 'Results_raw': {'train_loss': 9.046557, 'val_loss': 8.797394, 'test_loss': 8.953286}}
|
|
2024-11-13 18:52:45,932 (server:615) INFO: {'Role': 'Server #', 'Round': 46, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.323413), 'test_loss': np.float64(57458.412732), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.71586), 'val_loss': np.float64(62359.828)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.323413), 'test_loss': np.float64(57458.412732), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.71586), 'val_loss': np.float64(62359.828)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(8.192784), 'test_avg_loss_bottom_decile': np.float64(8.43466), 'test_avg_loss_top_decile': np.float64(31.892396), 'test_avg_loss_min': np.float64(8.357777), 'test_avg_loss_max': np.float64(31.892396), 'test_avg_loss_bottom10%': np.float64(8.357777), 'test_avg_loss_top10%': np.float64(31.892396), 'test_avg_loss_cos1': np.float64(0.893746), 'test_avg_loss_entropy': np.float64(2.185743), 'test_loss_std': np.float64(28838.600226), 'test_loss_bottom_decile': np.float64(29690.002838), 'test_loss_top_decile': np.float64(112261.233093), 'test_loss_min': np.float64(29419.373962), 'test_loss_max': np.float64(112261.233093), 'test_loss_bottom10%': np.float64(29419.373962), 'test_loss_top10%': np.float64(112261.233093), 'test_loss_cos1': np.float64(0.893746), 'test_loss_entropy': np.float64(2.185743), 'val_avg_loss_std': np.float64(8.74085), 'val_avg_loss_bottom_decile': np.float64(8.753271), 'val_avg_loss_top_decile': np.float64(33.814599), 'val_avg_loss_min': np.float64(8.564257), 'val_avg_loss_max': np.float64(33.814599), 'val_avg_loss_bottom10%': np.float64(8.564257), 'val_avg_loss_top10%': np.float64(33.814599), 'val_avg_loss_cos1': np.float64(0.896785), 'val_avg_loss_entropy': np.float64(2.187129), 'val_loss_std': np.float64(30767.7915), 'val_loss_bottom_decile': np.float64(30811.512238), 'val_loss_top_decile': np.float64(119027.387024), 'val_loss_min': np.float64(30146.183075), 'val_loss_max': np.float64(119027.387024), 'val_loss_bottom10%': np.float64(30146.183075), 'val_loss_top10%': np.float64(119027.387024), 'val_loss_cos1': np.float64(0.896785), 'val_loss_entropy': np.float64(2.187129)}}
|
|
2024-11-13 18:52:45,977 (server:353) INFO: Server: Starting evaluation at the end of round 47.
|
|
2024-11-13 18:52:45,978 (server:359) INFO: ----------- Starting a new training round (Round #48) -------------
|
|
2024-11-13 18:55:59,431 (client:354) INFO: {'Role': 'Client #7', 'Round': 48, 'Results_raw': {'train_loss': 11.156402, 'val_loss': 11.086891, 'test_loss': 10.194663}}
|
|
2024-11-13 18:57:00,756 (client:354) INFO: {'Role': 'Client #4', 'Round': 48, 'Results_raw': {'train_loss': 7.266378, 'val_loss': 6.492721, 'test_loss': 6.536428}}
|
|
2024-11-13 18:58:02,599 (client:354) INFO: {'Role': 'Client #8', 'Round': 48, 'Results_raw': {'train_loss': 7.457178, 'val_loss': 15.485795, 'test_loss': 8.026183}}
|
|
2024-11-13 18:59:03,873 (client:354) INFO: {'Role': 'Client #5', 'Round': 48, 'Results_raw': {'train_loss': 5.879751, 'val_loss': 5.956068, 'test_loss': 5.762027}}
|
|
2024-11-13 19:00:04,292 (client:354) INFO: {'Role': 'Client #6', 'Round': 48, 'Results_raw': {'train_loss': 9.019419, 'val_loss': 9.296965, 'test_loss': 9.394929}}
|
|
2024-11-13 19:01:06,858 (client:354) INFO: {'Role': 'Client #9', 'Round': 48, 'Results_raw': {'train_loss': 13.104906, 'val_loss': 15.784168, 'test_loss': 12.23809}}
|
|
2024-11-13 19:02:08,577 (client:354) INFO: {'Role': 'Client #2', 'Round': 48, 'Results_raw': {'train_loss': 10.614461, 'val_loss': 11.015047, 'test_loss': 10.205315}}
|
|
2024-11-13 19:03:10,666 (client:354) INFO: {'Role': 'Client #10', 'Round': 48, 'Results_raw': {'train_loss': 15.55635, 'val_loss': 15.499227, 'test_loss': 15.066353}}
|
|
2024-11-13 19:04:14,423 (client:354) INFO: {'Role': 'Client #3', 'Round': 48, 'Results_raw': {'train_loss': 8.936985, 'val_loss': 8.76514, 'test_loss': 9.250738}}
|
|
2024-11-13 19:05:17,998 (client:354) INFO: {'Role': 'Client #1', 'Round': 48, 'Results_raw': {'train_loss': 8.727916, 'val_loss': 8.067135, 'test_loss': 8.467121}}
|
|
2024-11-13 19:05:18,002 (server:615) INFO: {'Role': 'Server #', 'Round': 47, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.154227), 'test_loss': np.float64(56862.877802), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.525108), 'val_loss': np.float64(61688.378534)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.154227), 'test_loss': np.float64(56862.877802), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.525108), 'val_loss': np.float64(61688.378534)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(7.97699), 'test_avg_loss_bottom_decile': np.float64(8.476382), 'test_avg_loss_top_decile': np.float64(31.153687), 'test_avg_loss_min': np.float64(8.383924), 'test_avg_loss_max': np.float64(31.153687), 'test_avg_loss_bottom10%': np.float64(8.383924), 'test_avg_loss_top10%': np.float64(31.153687), 'test_avg_loss_cos1': np.float64(0.896639), 'test_avg_loss_entropy': np.float64(2.189558), 'test_loss_std': np.float64(28079.005197), 'test_loss_bottom_decile': np.float64(29836.863037), 'test_loss_top_decile': np.float64(109660.97876), 'test_loss_min': np.float64(29511.411713), 'test_loss_max': np.float64(109660.97876), 'test_loss_bottom10%': np.float64(29511.411713), 'test_loss_top10%': np.float64(109660.97876), 'test_loss_cos1': np.float64(0.896639), 'test_loss_entropy': np.float64(2.189558), 'val_avg_loss_std': np.float64(8.556833), 'val_avg_loss_bottom_decile': np.float64(8.794854), 'val_avg_loss_top_decile': np.float64(33.534389), 'val_avg_loss_min': np.float64(8.605027), 'val_avg_loss_max': np.float64(33.534389), 'val_avg_loss_bottom10%': np.float64(8.605027), 'val_avg_loss_top10%': np.float64(33.534389), 'val_avg_loss_cos1': np.float64(0.898607), 'val_avg_loss_entropy': np.float64(2.189822), 'val_loss_std': np.float64(30120.05264), 'val_loss_bottom_decile': np.float64(30957.887054), 'val_loss_top_decile': np.float64(118041.047607), 'val_loss_min': np.float64(30289.696655), 'val_loss_max': np.float64(118041.047607), 'val_loss_bottom10%': np.float64(30289.696655), 'val_loss_top10%': np.float64(118041.047607), 'val_loss_cos1': np.float64(0.898607), 'val_loss_entropy': np.float64(2.189822)}}
|
|
2024-11-13 19:05:18,040 (server:353) INFO: Server: Starting evaluation at the end of round 48.
|
|
2024-11-13 19:05:18,041 (server:359) INFO: ----------- Starting a new training round (Round #49) -------------
|
|
2024-11-13 19:08:34,623 (client:354) INFO: {'Role': 'Client #10', 'Round': 49, 'Results_raw': {'train_loss': 15.02649, 'val_loss': 15.205322, 'test_loss': 14.867237}}
|
|
2024-11-13 19:09:36,158 (client:354) INFO: {'Role': 'Client #3', 'Round': 49, 'Results_raw': {'train_loss': 8.897348, 'val_loss': 8.502179, 'test_loss': 9.013742}}
|
|
2024-11-13 19:10:37,455 (client:354) INFO: {'Role': 'Client #2', 'Round': 49, 'Results_raw': {'train_loss': 10.572565, 'val_loss': 11.164394, 'test_loss': 10.308013}}
|
|
2024-11-13 19:11:38,933 (client:354) INFO: {'Role': 'Client #6', 'Round': 49, 'Results_raw': {'train_loss': 8.942174, 'val_loss': 8.828541, 'test_loss': 8.879803}}
|
|
2024-11-13 19:12:36,745 (client:354) INFO: {'Role': 'Client #7', 'Round': 49, 'Results_raw': {'train_loss': 10.987667, 'val_loss': 10.921667, 'test_loss': 10.074871}}
|
|
2024-11-13 19:13:27,289 (client:354) INFO: {'Role': 'Client #4', 'Round': 49, 'Results_raw': {'train_loss': 7.294277, 'val_loss': 6.661001, 'test_loss': 6.717107}}
|
|
2024-11-13 19:14:05,738 (client:354) INFO: {'Role': 'Client #5', 'Round': 49, 'Results_raw': {'train_loss': 5.828538, 'val_loss': 5.89363, 'test_loss': 6.023484}}
|
|
2024-11-13 19:14:41,786 (client:354) INFO: {'Role': 'Client #9', 'Round': 49, 'Results_raw': {'train_loss': 12.56276, 'val_loss': 15.393319, 'test_loss': 12.067761}}
|
|
2024-11-13 19:15:19,415 (client:354) INFO: {'Role': 'Client #8', 'Round': 49, 'Results_raw': {'train_loss': 7.452021, 'val_loss': 15.435134, 'test_loss': 7.783598}}
|
|
2024-11-13 19:15:57,187 (client:354) INFO: {'Role': 'Client #1', 'Round': 49, 'Results_raw': {'train_loss': 8.739752, 'val_loss': 8.142531, 'test_loss': 8.53563}}
|
|
2024-11-13 19:15:57,191 (server:615) INFO: {'Role': 'Server #', 'Round': 48, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.356924), 'test_loss': np.float64(57576.371149), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.764463), 'val_loss': np.float64(62530.910834)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.356924), 'test_loss': np.float64(57576.371149), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.764463), 'val_loss': np.float64(62530.910834)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(8.201799), 'test_avg_loss_bottom_decile': np.float64(8.459309), 'test_avg_loss_top_decile': np.float64(31.914946), 'test_avg_loss_min': np.float64(8.406992), 'test_avg_loss_max': np.float64(31.914946), 'test_avg_loss_bottom10%': np.float64(8.406992), 'test_avg_loss_top10%': np.float64(31.914946), 'test_avg_loss_cos1': np.float64(0.893916), 'test_avg_loss_entropy': np.float64(2.186164), 'test_loss_std': np.float64(28870.331342), 'test_loss_bottom_decile': np.float64(29776.766937), 'test_loss_top_decile': np.float64(112340.610107), 'test_loss_min': np.float64(29592.611755), 'test_loss_max': np.float64(112340.610107), 'test_loss_bottom10%': np.float64(29592.611755), 'test_loss_top10%': np.float64(112340.610107), 'test_loss_cos1': np.float64(0.893916), 'test_loss_entropy': np.float64(2.186164), 'val_avg_loss_std': np.float64(8.73912), 'val_avg_loss_bottom_decile': np.float64(8.813658), 'val_avg_loss_top_decile': np.float64(33.942094), 'val_avg_loss_min': np.float64(8.589358), 'val_avg_loss_max': np.float64(33.942094), 'val_avg_loss_bottom10%': np.float64(8.589358), 'val_avg_loss_top10%': np.float64(33.942094), 'val_avg_loss_cos1': np.float64(0.8973), 'val_avg_loss_entropy': np.float64(2.187844), 'val_loss_std': np.float64(30761.701007), 'val_loss_bottom_decile': np.float64(31024.076813), 'val_loss_top_decile': np.float64(119476.169434), 'val_loss_min': np.float64(30234.53952), 'val_loss_max': np.float64(119476.169434), 'val_loss_bottom10%': np.float64(30234.53952), 'val_loss_top10%': np.float64(119476.169434), 'val_loss_cos1': np.float64(0.8973), 'val_loss_entropy': np.float64(2.187844)}}
|
|
2024-11-13 19:15:57,226 (server:353) INFO: Server: Starting evaluation at the end of round 49.
|
|
2024-11-13 19:15:57,227 (server:359) INFO: ----------- Starting a new training round (Round #50) -------------
|
|
2024-11-13 19:17:35,043 (client:354) INFO: {'Role': 'Client #8', 'Round': 50, 'Results_raw': {'train_loss': 7.439888, 'val_loss': 16.390989, 'test_loss': 7.942964}}
|
|
2024-11-13 19:18:11,598 (client:354) INFO: {'Role': 'Client #1', 'Round': 50, 'Results_raw': {'train_loss': 8.685897, 'val_loss': 8.064858, 'test_loss': 8.472479}}
|
|
2024-11-13 19:18:48,192 (client:354) INFO: {'Role': 'Client #9', 'Round': 50, 'Results_raw': {'train_loss': 12.712247, 'val_loss': 15.684082, 'test_loss': 12.159589}}
|
|
2024-11-13 19:19:23,719 (client:354) INFO: {'Role': 'Client #10', 'Round': 50, 'Results_raw': {'train_loss': 14.793959, 'val_loss': 14.913808, 'test_loss': 14.787127}}
|
|
2024-11-13 19:20:03,869 (client:354) INFO: {'Role': 'Client #3', 'Round': 50, 'Results_raw': {'train_loss': 8.878364, 'val_loss': 8.583625, 'test_loss': 9.107153}}
|
|
2024-11-13 19:20:40,515 (client:354) INFO: {'Role': 'Client #5', 'Round': 50, 'Results_raw': {'train_loss': 5.834072, 'val_loss': 5.890493, 'test_loss': 5.780336}}
|
|
2024-11-13 19:21:16,729 (client:354) INFO: {'Role': 'Client #7', 'Round': 50, 'Results_raw': {'train_loss': 10.988069, 'val_loss': 11.083964, 'test_loss': 10.210301}}
|
|
2024-11-13 19:21:49,980 (client:354) INFO: {'Role': 'Client #2', 'Round': 50, 'Results_raw': {'train_loss': 10.588231, 'val_loss': 10.8551, 'test_loss': 10.062535}}
|
|
2024-11-13 19:22:23,121 (client:354) INFO: {'Role': 'Client #6', 'Round': 50, 'Results_raw': {'train_loss': 9.212449, 'val_loss': 9.579438, 'test_loss': 9.421458}}
|
|
2024-11-13 19:22:55,790 (client:354) INFO: {'Role': 'Client #4', 'Round': 50, 'Results_raw': {'train_loss': 7.267522, 'val_loss': 6.594134, 'test_loss': 6.731594}}
|
|
2024-11-13 19:22:55,792 (server:615) INFO: {'Role': 'Server #', 'Round': 49, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.435099), 'test_loss': np.float64(57851.548792), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.815763), 'val_loss': np.float64(62711.486346)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.435099), 'test_loss': np.float64(57851.548792), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.815763), 'val_loss': np.float64(62711.486346)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(8.35826), 'test_avg_loss_bottom_decile': np.float64(8.425907), 'test_avg_loss_top_decile': np.float64(32.746749), 'test_avg_loss_min': np.float64(8.310589), 'test_avg_loss_max': np.float64(32.746749), 'test_avg_loss_bottom10%': np.float64(8.310589), 'test_avg_loss_top10%': np.float64(32.746749), 'test_avg_loss_cos1': np.float64(0.891354), 'test_avg_loss_entropy': np.float64(2.182767), 'test_loss_std': np.float64(29421.076913), 'test_loss_bottom_decile': np.float64(29659.191498), 'test_loss_top_decile': np.float64(115268.557678), 'test_loss_min': np.float64(29253.271545), 'test_loss_max': np.float64(115268.557678), 'test_loss_bottom10%': np.float64(29253.271545), 'test_loss_top10%': np.float64(115268.557678), 'test_loss_cos1': np.float64(0.891354), 'test_loss_entropy': np.float64(2.182767), 'val_avg_loss_std': np.float64(8.885839), 'val_avg_loss_bottom_decile': np.float64(8.691503), 'val_avg_loss_top_decile': np.float64(33.57916), 'val_avg_loss_min': np.float64(8.547208), 'val_avg_loss_max': np.float64(33.57916), 'val_avg_loss_bottom10%': np.float64(8.547208), 'val_avg_loss_top10%': np.float64(33.57916), 'val_avg_loss_cos1': np.float64(0.89487), 'val_avg_loss_entropy': np.float64(2.184546), 'val_loss_std': np.float64(31278.153482), 'val_loss_bottom_decile': np.float64(30594.090027), 'val_loss_top_decile': np.float64(118198.641846), 'val_loss_min': np.float64(30086.170654), 'val_loss_max': np.float64(118198.641846), 'val_loss_bottom10%': np.float64(30086.170654), 'val_loss_top10%': np.float64(118198.641846), 'val_loss_cos1': np.float64(0.89487), 'val_loss_entropy': np.float64(2.184546)}}
|
|
2024-11-13 19:22:55,829 (server:353) INFO: Server: Starting evaluation at the end of round 50.
|
|
2024-11-13 19:22:55,829 (server:359) INFO: ----------- Starting a new training round (Round #51) -------------
|
|
2024-11-13 19:24:28,051 (client:354) INFO: {'Role': 'Client #8', 'Round': 51, 'Results_raw': {'train_loss': 7.458206, 'val_loss': 15.742562, 'test_loss': 7.985467}}
|
|
2024-11-13 19:25:02,233 (client:354) INFO: {'Role': 'Client #1', 'Round': 51, 'Results_raw': {'train_loss': 8.693826, 'val_loss': 8.073365, 'test_loss': 8.515263}}
|
|
2024-11-13 19:25:36,641 (client:354) INFO: {'Role': 'Client #4', 'Round': 51, 'Results_raw': {'train_loss': 7.249347, 'val_loss': 6.52433, 'test_loss': 6.682208}}
|
|
2024-11-13 19:26:09,654 (client:354) INFO: {'Role': 'Client #10', 'Round': 51, 'Results_raw': {'train_loss': 14.915769, 'val_loss': 15.967443, 'test_loss': 15.506895}}
|
|
2024-11-13 19:26:44,094 (client:354) INFO: {'Role': 'Client #3', 'Round': 51, 'Results_raw': {'train_loss': 8.910252, 'val_loss': 8.53518, 'test_loss': 9.01853}}
|
|
2024-11-13 19:27:19,412 (client:354) INFO: {'Role': 'Client #2', 'Round': 51, 'Results_raw': {'train_loss': 10.716514, 'val_loss': 11.139547, 'test_loss': 10.398251}}
|
|
2024-11-13 19:27:56,543 (client:354) INFO: {'Role': 'Client #7', 'Round': 51, 'Results_raw': {'train_loss': 11.045086, 'val_loss': 10.873959, 'test_loss': 9.990802}}
|
|
2024-11-13 19:28:42,208 (client:354) INFO: {'Role': 'Client #5', 'Round': 51, 'Results_raw': {'train_loss': 5.847594, 'val_loss': 5.890124, 'test_loss': 5.76385}}
|
|
2024-11-13 19:29:43,479 (client:354) INFO: {'Role': 'Client #9', 'Round': 51, 'Results_raw': {'train_loss': 12.869606, 'val_loss': 15.132352, 'test_loss': 11.576509}}
|
|
2024-11-13 19:30:46,735 (client:354) INFO: {'Role': 'Client #6', 'Round': 51, 'Results_raw': {'train_loss': 8.934952, 'val_loss': 8.941043, 'test_loss': 8.927461}}
|
|
2024-11-13 19:30:46,741 (server:615) INFO: {'Role': 'Server #', 'Round': 50, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.252119), 'test_loss': np.float64(57207.459131), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.65092), 'val_loss': np.float64(62131.237344)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.252119), 'test_loss': np.float64(57207.459131), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.65092), 'val_loss': np.float64(62131.237344)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(8.074185), 'test_avg_loss_bottom_decile': np.float64(8.490063), 'test_avg_loss_top_decile': np.float64(31.727606), 'test_avg_loss_min': np.float64(8.333889), 'test_avg_loss_max': np.float64(31.727606), 'test_avg_loss_bottom10%': np.float64(8.333889), 'test_avg_loss_top10%': np.float64(31.727606), 'test_avg_loss_cos1': np.float64(0.895568), 'test_avg_loss_entropy': np.float64(2.188015), 'test_loss_std': np.float64(28421.131602), 'test_loss_bottom_decile': np.float64(29885.020691), 'test_loss_top_decile': np.float64(111681.171875), 'test_loss_min': np.float64(29335.287933), 'test_loss_max': np.float64(111681.171875), 'test_loss_bottom10%': np.float64(29335.287933), 'test_loss_top10%': np.float64(111681.171875), 'test_loss_cos1': np.float64(0.895568), 'test_loss_entropy': np.float64(2.188015), 'val_avg_loss_std': np.float64(8.603012), 'val_avg_loss_bottom_decile': np.float64(8.704749), 'val_avg_loss_top_decile': np.float64(33.225166), 'val_avg_loss_min': np.float64(8.618952), 'val_avg_loss_max': np.float64(33.225166), 'val_avg_loss_bottom10%': np.float64(8.618952), 'val_avg_loss_top10%': np.float64(33.225166), 'val_avg_loss_cos1': np.float64(0.898913), 'val_avg_loss_entropy': np.float64(2.18952), 'val_loss_std': np.float64(30282.603212), 'val_loss_bottom_decile': np.float64(30640.71698), 'val_loss_top_decile': np.float64(116952.585876), 'val_loss_min': np.float64(30338.710846), 'val_loss_max': np.float64(116952.585876), 'val_loss_bottom10%': np.float64(30338.710846), 'val_loss_top10%': np.float64(116952.585876), 'val_loss_cos1': np.float64(0.898913), 'val_loss_entropy': np.float64(2.18952)}}
|
|
2024-11-13 19:30:46,779 (server:353) INFO: Server: Starting evaluation at the end of round 51.
|
|
2024-11-13 19:30:46,780 (server:359) INFO: ----------- Starting a new training round (Round #52) -------------
|
|
2024-11-13 19:34:00,429 (client:354) INFO: {'Role': 'Client #10', 'Round': 52, 'Results_raw': {'train_loss': 14.800443, 'val_loss': 15.510884, 'test_loss': 14.788397}}
|
|
2024-11-13 19:35:03,239 (client:354) INFO: {'Role': 'Client #1', 'Round': 52, 'Results_raw': {'train_loss': 8.670854, 'val_loss': 8.139204, 'test_loss': 8.555994}}
|
|
2024-11-13 19:36:03,852 (client:354) INFO: {'Role': 'Client #5', 'Round': 52, 'Results_raw': {'train_loss': 5.850827, 'val_loss': 5.935099, 'test_loss': 5.850916}}
|
|
2024-11-13 19:37:04,847 (client:354) INFO: {'Role': 'Client #4', 'Round': 52, 'Results_raw': {'train_loss': 7.271655, 'val_loss': 6.508895, 'test_loss': 6.59691}}
|
|
2024-11-13 19:38:05,139 (client:354) INFO: {'Role': 'Client #7', 'Round': 52, 'Results_raw': {'train_loss': 10.928431, 'val_loss': 10.907003, 'test_loss': 10.147032}}
|
|
2024-11-13 19:39:07,623 (client:354) INFO: {'Role': 'Client #9', 'Round': 52, 'Results_raw': {'train_loss': 12.515525, 'val_loss': 15.119802, 'test_loss': 11.58891}}
|
|
2024-11-13 19:40:10,620 (client:354) INFO: {'Role': 'Client #3', 'Round': 52, 'Results_raw': {'train_loss': 8.882113, 'val_loss': 8.562254, 'test_loss': 9.01042}}
|
|
2024-11-13 19:41:14,059 (client:354) INFO: {'Role': 'Client #6', 'Round': 52, 'Results_raw': {'train_loss': 8.959165, 'val_loss': 8.922239, 'test_loss': 8.976914}}
|
|
2024-11-13 19:42:16,599 (client:354) INFO: {'Role': 'Client #2', 'Round': 52, 'Results_raw': {'train_loss': 10.506268, 'val_loss': 10.665367, 'test_loss': 9.8599}}
|
|
2024-11-13 19:43:19,499 (client:354) INFO: {'Role': 'Client #8', 'Round': 52, 'Results_raw': {'train_loss': 7.45606, 'val_loss': 15.563268, 'test_loss': 7.864346}}
|
|
2024-11-13 19:43:19,503 (server:615) INFO: {'Role': 'Server #', 'Round': 51, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.272036), 'test_loss': np.float64(57277.568396), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.655997), 'val_loss': np.float64(62149.108432)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.272036), 'test_loss': np.float64(57277.568396), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.655997), 'val_loss': np.float64(62149.108432)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(8.151036), 'test_avg_loss_bottom_decile': np.float64(8.416426), 'test_avg_loss_top_decile': np.float64(32.17697), 'test_avg_loss_min': np.float64(8.364871), 'test_avg_loss_max': np.float64(32.17697), 'test_avg_loss_bottom10%': np.float64(8.364871), 'test_avg_loss_top10%': np.float64(32.17697), 'test_avg_loss_cos1': np.float64(0.894097), 'test_avg_loss_entropy': np.float64(2.186387), 'test_loss_std': np.float64(28691.64786), 'test_loss_bottom_decile': np.float64(29625.818024), 'test_loss_top_decile': np.float64(113262.934326), 'test_loss_min': np.float64(29444.345551), 'test_loss_max': np.float64(113262.934326), 'test_loss_bottom10%': np.float64(29444.345551), 'test_loss_top10%': np.float64(113262.934326), 'test_loss_cos1': np.float64(0.894097), 'test_loss_entropy': np.float64(2.186387), 'val_avg_loss_std': np.float64(8.669837), 'val_avg_loss_bottom_decile': np.float64(8.731344), 'val_avg_loss_top_decile': np.float64(33.141492), 'val_avg_loss_min': np.float64(8.543636), 'val_avg_loss_max': np.float64(33.141492), 'val_avg_loss_bottom10%': np.float64(8.543636), 'val_avg_loss_top10%': np.float64(33.141492), 'val_avg_loss_cos1': np.float64(0.89762), 'val_avg_loss_entropy': np.float64(2.188093), 'val_loss_std': np.float64(30517.827829), 'val_loss_bottom_decile': np.float64(30734.331787), 'val_loss_top_decile': np.float64(116658.053162), 'val_loss_min': np.float64(30073.600037), 'val_loss_max': np.float64(116658.053162), 'val_loss_bottom10%': np.float64(30073.600037), 'val_loss_top10%': np.float64(116658.053162), 'val_loss_cos1': np.float64(0.89762), 'val_loss_entropy': np.float64(2.188093)}}
|
|
2024-11-13 19:43:19,534 (server:353) INFO: Server: Starting evaluation at the end of round 52.
|
|
2024-11-13 19:43:19,535 (server:359) INFO: ----------- Starting a new training round (Round #53) -------------
|
|
2024-11-13 19:46:37,178 (client:354) INFO: {'Role': 'Client #9', 'Round': 53, 'Results_raw': {'train_loss': 13.070347, 'val_loss': 15.485759, 'test_loss': 11.841827}}
|
|
2024-11-13 19:47:38,760 (client:354) INFO: {'Role': 'Client #1', 'Round': 53, 'Results_raw': {'train_loss': 8.644539, 'val_loss': 8.028174, 'test_loss': 8.454826}}
|
|
2024-11-13 19:48:38,654 (client:354) INFO: {'Role': 'Client #2', 'Round': 53, 'Results_raw': {'train_loss': 10.760316, 'val_loss': 10.916605, 'test_loss': 10.246269}}
|
|
2024-11-13 19:49:37,511 (client:354) INFO: {'Role': 'Client #6', 'Round': 53, 'Results_raw': {'train_loss': 8.91578, 'val_loss': 8.966733, 'test_loss': 9.027039}}
|
|
2024-11-13 19:50:38,929 (client:354) INFO: {'Role': 'Client #3', 'Round': 53, 'Results_raw': {'train_loss': 8.919615, 'val_loss': 8.503537, 'test_loss': 8.961446}}
|
|
2024-11-13 19:51:40,899 (client:354) INFO: {'Role': 'Client #4', 'Round': 53, 'Results_raw': {'train_loss': 7.236579, 'val_loss': 6.541702, 'test_loss': 6.628453}}
|
|
2024-11-13 19:52:43,122 (client:354) INFO: {'Role': 'Client #10', 'Round': 53, 'Results_raw': {'train_loss': 14.571169, 'val_loss': 15.329177, 'test_loss': 14.792136}}
|
|
2024-11-13 19:53:45,487 (client:354) INFO: {'Role': 'Client #8', 'Round': 53, 'Results_raw': {'train_loss': 7.427805, 'val_loss': 15.587333, 'test_loss': 7.959425}}
|
|
2024-11-13 19:54:47,456 (client:354) INFO: {'Role': 'Client #7', 'Round': 53, 'Results_raw': {'train_loss': 10.916663, 'val_loss': 10.842724, 'test_loss': 9.923153}}
|
|
2024-11-13 19:55:49,751 (client:354) INFO: {'Role': 'Client #5', 'Round': 53, 'Results_raw': {'train_loss': 5.846404, 'val_loss': 5.848329, 'test_loss': 5.857149}}
|
|
2024-11-13 19:55:49,756 (server:615) INFO: {'Role': 'Server #', 'Round': 52, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.126606), 'test_loss': np.float64(56765.653082), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.511001), 'val_loss': np.float64(61638.724057)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.126606), 'test_loss': np.float64(56765.653082), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.511001), 'val_loss': np.float64(61638.724057)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(8.037038), 'test_avg_loss_bottom_decile': np.float64(8.4036), 'test_avg_loss_top_decile': np.float64(31.824162), 'test_avg_loss_min': np.float64(8.36828), 'test_avg_loss_max': np.float64(31.824162), 'test_avg_loss_bottom10%': np.float64(8.36828), 'test_avg_loss_top10%': np.float64(31.824162), 'test_avg_loss_cos1': np.float64(0.89501), 'test_avg_loss_entropy': np.float64(2.187882), 'test_loss_std': np.float64(28290.372863), 'test_loss_bottom_decile': np.float64(29580.671661), 'test_loss_top_decile': np.float64(112021.051392), 'test_loss_min': np.float64(29456.347015), 'test_loss_max': np.float64(112021.051392), 'test_loss_bottom10%': np.float64(29456.347015), 'test_loss_top10%': np.float64(112021.051392), 'test_loss_cos1': np.float64(0.89501), 'test_loss_entropy': np.float64(2.187882), 'val_avg_loss_std': np.float64(8.558578), 'val_avg_loss_bottom_decile': np.float64(8.744733), 'val_avg_loss_top_decile': np.float64(32.914107), 'val_avg_loss_min': np.float64(8.537024), 'val_avg_loss_max': np.float64(32.914107), 'val_avg_loss_bottom10%': np.float64(8.537024), 'val_avg_loss_top10%': np.float64(32.914107), 'val_avg_loss_cos1': np.float64(0.898432), 'val_avg_loss_entropy': np.float64(2.189398), 'val_loss_std': np.float64(30126.192907), 'val_loss_bottom_decile': np.float64(30781.460907), 'val_loss_top_decile': np.float64(115857.657104), 'val_loss_min': np.float64(30050.32312), 'val_loss_max': np.float64(115857.657104), 'val_loss_bottom10%': np.float64(30050.32312), 'val_loss_top10%': np.float64(115857.657104), 'val_loss_cos1': np.float64(0.898432), 'val_loss_entropy': np.float64(2.189398)}}
|
|
2024-11-13 19:55:49,793 (server:353) INFO: Server: Starting evaluation at the end of round 53.
|
|
2024-11-13 19:55:49,794 (server:359) INFO: ----------- Starting a new training round (Round #54) -------------
|
|
2024-11-13 19:59:11,381 (client:354) INFO: {'Role': 'Client #5', 'Round': 54, 'Results_raw': {'train_loss': 5.834846, 'val_loss': 6.046498, 'test_loss': 5.834125}}
|
|
2024-11-13 20:00:11,854 (client:354) INFO: {'Role': 'Client #4', 'Round': 54, 'Results_raw': {'train_loss': 7.243096, 'val_loss': 6.603759, 'test_loss': 6.645155}}
|
|
2024-11-13 20:01:13,024 (client:354) INFO: {'Role': 'Client #2', 'Round': 54, 'Results_raw': {'train_loss': 10.552091, 'val_loss': 10.963116, 'test_loss': 10.040556}}
|
|
2024-11-13 20:02:16,694 (client:354) INFO: {'Role': 'Client #9', 'Round': 54, 'Results_raw': {'train_loss': 12.631622, 'val_loss': 15.401471, 'test_loss': 12.071646}}
|
|
2024-11-13 20:03:17,871 (client:354) INFO: {'Role': 'Client #7', 'Round': 54, 'Results_raw': {'train_loss': 10.88751, 'val_loss': 10.956739, 'test_loss': 10.102701}}
|
|
2024-11-13 20:04:20,586 (client:354) INFO: {'Role': 'Client #10', 'Round': 54, 'Results_raw': {'train_loss': 14.938059, 'val_loss': 15.150322, 'test_loss': 14.703736}}
|
|
2024-11-13 20:05:26,024 (client:354) INFO: {'Role': 'Client #3', 'Round': 54, 'Results_raw': {'train_loss': 8.871451, 'val_loss': 8.525094, 'test_loss': 8.986619}}
|
|
2024-11-13 20:06:29,552 (client:354) INFO: {'Role': 'Client #8', 'Round': 54, 'Results_raw': {'train_loss': 7.430915, 'val_loss': 16.079462, 'test_loss': 7.93945}}
|
|
2024-11-13 20:07:34,336 (client:354) INFO: {'Role': 'Client #1', 'Round': 54, 'Results_raw': {'train_loss': 8.666858, 'val_loss': 8.02898, 'test_loss': 8.491618}}
|
|
2024-11-13 20:08:35,692 (client:354) INFO: {'Role': 'Client #6', 'Round': 54, 'Results_raw': {'train_loss': 9.168735, 'val_loss': 11.346396, 'test_loss': 11.339325}}
|
|
2024-11-13 20:08:35,700 (server:615) INFO: {'Role': 'Server #', 'Round': 53, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.153507), 'test_loss': np.float64(56860.345413), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.544376), 'val_loss': np.float64(61756.205151)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.153507), 'test_loss': np.float64(56860.345413), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.544376), 'val_loss': np.float64(61756.205151)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(7.992721), 'test_avg_loss_bottom_decile': np.float64(8.419028), 'test_avg_loss_top_decile': np.float64(31.133612), 'test_avg_loss_min': np.float64(8.356045), 'test_avg_loss_max': np.float64(31.133612), 'test_avg_loss_bottom10%': np.float64(8.356045), 'test_avg_loss_top10%': np.float64(31.133612), 'test_avg_loss_cos1': np.float64(0.896284), 'test_avg_loss_entropy': np.float64(2.18891), 'test_loss_std': np.float64(28134.377985), 'test_loss_bottom_decile': np.float64(29634.979095), 'test_loss_top_decile': np.float64(109590.315125), 'test_loss_min': np.float64(29413.278259), 'test_loss_max': np.float64(109590.315125), 'test_loss_bottom10%': np.float64(29413.278259), 'test_loss_top10%': np.float64(109590.315125), 'test_loss_cos1': np.float64(0.896284), 'test_loss_entropy': np.float64(2.18891), 'val_avg_loss_std': np.float64(8.541164), 'val_avg_loss_bottom_decile': np.float64(8.695844), 'val_avg_loss_top_decile': np.float64(33.274861), 'val_avg_loss_min': np.float64(8.551074), 'val_avg_loss_max': np.float64(33.274861), 'val_avg_loss_bottom10%': np.float64(8.551074), 'val_avg_loss_top10%': np.float64(33.274861), 'val_avg_loss_cos1': np.float64(0.899113), 'val_avg_loss_entropy': np.float64(2.189896), 'val_loss_std': np.float64(30064.89788), 'val_loss_bottom_decile': np.float64(30609.369659), 'val_loss_top_decile': np.float64(117127.512085), 'val_loss_min': np.float64(30099.782166), 'val_loss_max': np.float64(117127.512085), 'val_loss_bottom10%': np.float64(30099.782166), 'val_loss_top10%': np.float64(117127.512085), 'val_loss_cos1': np.float64(0.899113), 'val_loss_entropy': np.float64(2.189896)}}
|
|
2024-11-13 20:08:35,752 (server:353) INFO: Server: Starting evaluation at the end of round 54.
|
|
2024-11-13 20:08:35,753 (server:359) INFO: ----------- Starting a new training round (Round #55) -------------
|
|
2024-11-13 20:12:00,966 (client:354) INFO: {'Role': 'Client #5', 'Round': 55, 'Results_raw': {'train_loss': 5.813791, 'val_loss': 5.790252, 'test_loss': 5.866015}}
|
|
2024-11-13 20:12:51,105 (client:354) INFO: {'Role': 'Client #2', 'Round': 55, 'Results_raw': {'train_loss': 10.45453, 'val_loss': 10.805325, 'test_loss': 9.919992}}
|
|
2024-11-13 20:13:37,241 (client:354) INFO: {'Role': 'Client #3', 'Round': 55, 'Results_raw': {'train_loss': 8.874161, 'val_loss': 8.550049, 'test_loss': 9.009091}}
|
|
2024-11-13 20:14:25,097 (client:354) INFO: {'Role': 'Client #7', 'Round': 55, 'Results_raw': {'train_loss': 10.902114, 'val_loss': 10.767573, 'test_loss': 9.947569}}
|
|
2024-11-13 20:15:13,877 (client:354) INFO: {'Role': 'Client #6', 'Round': 55, 'Results_raw': {'train_loss': 8.856154, 'val_loss': 8.774035, 'test_loss': 8.824022}}
|
|
2024-11-13 20:16:01,577 (client:354) INFO: {'Role': 'Client #9', 'Round': 55, 'Results_raw': {'train_loss': 12.924281, 'val_loss': 15.873794, 'test_loss': 12.432586}}
|
|
2024-11-13 20:16:50,284 (client:354) INFO: {'Role': 'Client #1', 'Round': 55, 'Results_raw': {'train_loss': 8.664979, 'val_loss': 7.960578, 'test_loss': 8.400072}}
|
|
2024-11-13 20:17:40,412 (client:354) INFO: {'Role': 'Client #10', 'Round': 55, 'Results_raw': {'train_loss': 14.680589, 'val_loss': 15.222032, 'test_loss': 14.685267}}
|
|
2024-11-13 20:18:29,041 (client:354) INFO: {'Role': 'Client #4', 'Round': 55, 'Results_raw': {'train_loss': 7.23108, 'val_loss': 6.515101, 'test_loss': 6.586839}}
|
|
2024-11-13 20:19:17,932 (client:354) INFO: {'Role': 'Client #8', 'Round': 55, 'Results_raw': {'train_loss': 7.419356, 'val_loss': 16.526675, 'test_loss': 7.958367}}
|
|
2024-11-13 20:19:17,935 (server:615) INFO: {'Role': 'Server #', 'Round': 54, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.077631), 'test_loss': np.float64(56593.260968), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.481373), 'val_loss': np.float64(61534.431927)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.077631), 'test_loss': np.float64(56593.260968), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.481373), 'val_loss': np.float64(61534.431927)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(7.866698), 'test_avg_loss_bottom_decile': np.float64(8.407171), 'test_avg_loss_top_decile': np.float64(31.498839), 'test_avg_loss_min': np.float64(8.391176), 'test_avg_loss_max': np.float64(31.498839), 'test_avg_loss_bottom10%': np.float64(8.391176), 'test_avg_loss_top10%': np.float64(31.498839), 'test_avg_loss_cos1': np.float64(0.898241), 'test_avg_loss_entropy': np.float64(2.191506), 'test_loss_std': np.float64(27690.777616), 'test_loss_bottom_decile': np.float64(29593.241974), 'test_loss_top_decile': np.float64(110875.912048), 'test_loss_min': np.float64(29536.940247), 'test_loss_max': np.float64(110875.912048), 'test_loss_bottom10%': np.float64(29536.940247), 'test_loss_top10%': np.float64(110875.912048), 'test_loss_cos1': np.float64(0.898241), 'test_loss_entropy': np.float64(2.191506), 'val_avg_loss_std': np.float64(8.387705), 'val_avg_loss_bottom_decile': np.float64(8.75918), 'val_avg_loss_top_decile': np.float64(32.194688), 'val_avg_loss_min': np.float64(8.532985), 'val_avg_loss_max': np.float64(32.194688), 'val_avg_loss_bottom10%': np.float64(8.532985), 'val_avg_loss_top10%': np.float64(32.194688), 'val_avg_loss_cos1': np.float64(0.901591), 'val_avg_loss_entropy': np.float64(2.192818), 'val_loss_std': np.float64(29524.722106), 'val_loss_bottom_decile': np.float64(30832.31485), 'val_loss_top_decile': np.float64(113325.302551), 'val_loss_min': np.float64(30036.105682), 'val_loss_max': np.float64(113325.302551), 'val_loss_bottom10%': np.float64(30036.105682), 'val_loss_top10%': np.float64(113325.302551), 'val_loss_cos1': np.float64(0.901591), 'val_loss_entropy': np.float64(2.192818)}}
|
|
2024-11-13 20:19:17,973 (server:353) INFO: Server: Starting evaluation at the end of round 55.
|
|
2024-11-13 20:19:17,973 (server:359) INFO: ----------- Starting a new training round (Round #56) -------------
|
|
2024-11-13 20:20:53,709 (client:354) INFO: {'Role': 'Client #5', 'Round': 56, 'Results_raw': {'train_loss': 5.784374, 'val_loss': 5.809036, 'test_loss': 5.831585}}
|
|
2024-11-13 20:21:27,462 (client:354) INFO: {'Role': 'Client #10', 'Round': 56, 'Results_raw': {'train_loss': 14.507866, 'val_loss': 15.122795, 'test_loss': 14.658626}}
|
|
2024-11-13 20:22:00,722 (client:354) INFO: {'Role': 'Client #7', 'Round': 56, 'Results_raw': {'train_loss': 10.962441, 'val_loss': 10.830104, 'test_loss': 9.976729}}
|
|
2024-11-13 20:22:34,084 (client:354) INFO: {'Role': 'Client #8', 'Round': 56, 'Results_raw': {'train_loss': 7.451619, 'val_loss': 17.385792, 'test_loss': 8.160637}}
|
|
2024-11-13 20:23:06,708 (client:354) INFO: {'Role': 'Client #9', 'Round': 56, 'Results_raw': {'train_loss': 12.668969, 'val_loss': 15.108462, 'test_loss': 11.537661}}
|
|
2024-11-13 20:23:40,197 (client:354) INFO: {'Role': 'Client #4', 'Round': 56, 'Results_raw': {'train_loss': 7.19523, 'val_loss': 6.580262, 'test_loss': 6.667959}}
|
|
2024-11-13 20:24:13,885 (client:354) INFO: {'Role': 'Client #3', 'Round': 56, 'Results_raw': {'train_loss': 8.860477, 'val_loss': 8.4966, 'test_loss': 8.930291}}
|
|
2024-11-13 20:24:46,429 (client:354) INFO: {'Role': 'Client #1', 'Round': 56, 'Results_raw': {'train_loss': 8.646301, 'val_loss': 8.064661, 'test_loss': 8.502678}}
|
|
2024-11-13 20:25:19,812 (client:354) INFO: {'Role': 'Client #2', 'Round': 56, 'Results_raw': {'train_loss': 10.549617, 'val_loss': 10.833358, 'test_loss': 10.049254}}
|
|
2024-11-13 20:25:53,469 (client:354) INFO: {'Role': 'Client #6', 'Round': 56, 'Results_raw': {'train_loss': 8.915883, 'val_loss': 8.870685, 'test_loss': 9.026874}}
|
|
2024-11-13 20:25:53,472 (server:615) INFO: {'Role': 'Server #', 'Round': 55, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.036656), 'test_loss': np.float64(56449.028229), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.427058), 'val_loss': np.float64(61343.244492)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.036656), 'test_loss': np.float64(56449.028229), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.427058), 'val_loss': np.float64(61343.244492)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(7.905105), 'test_avg_loss_bottom_decile': np.float64(8.406331), 'test_avg_loss_top_decile': np.float64(31.817608), 'test_avg_loss_min': np.float64(8.292338), 'test_avg_loss_max': np.float64(31.817608), 'test_avg_loss_bottom10%': np.float64(8.292338), 'test_avg_loss_top10%': np.float64(31.817608), 'test_avg_loss_cos1': np.float64(0.896946), 'test_avg_loss_entropy': np.float64(2.190043), 'test_loss_std': np.float64(27825.971079), 'test_loss_bottom_decile': np.float64(29590.285767), 'test_loss_top_decile': np.float64(111997.981018), 'test_loss_min': np.float64(29189.028931), 'test_loss_max': np.float64(111997.981018), 'test_loss_bottom10%': np.float64(29189.028931), 'test_loss_top10%': np.float64(111997.981018), 'test_loss_cos1': np.float64(0.896946), 'test_loss_entropy': np.float64(2.190043), 'val_avg_loss_std': np.float64(8.438352), 'val_avg_loss_bottom_decile': np.float64(8.656913), 'val_avg_loss_top_decile': np.float64(32.306366), 'val_avg_loss_min': np.float64(8.523017), 'val_avg_loss_max': np.float64(32.306366), 'val_avg_loss_bottom10%': np.float64(8.523017), 'val_avg_loss_top10%': np.float64(32.306366), 'val_avg_loss_cos1': np.float64(0.90004), 'val_avg_loss_entropy': np.float64(2.191005), 'val_loss_std': np.float64(29703.000377), 'val_loss_bottom_decile': np.float64(30472.33371), 'val_loss_top_decile': np.float64(113718.407104), 'val_loss_min': np.float64(30001.020538), 'val_loss_max': np.float64(113718.407104), 'val_loss_bottom10%': np.float64(30001.020538), 'val_loss_top10%': np.float64(113718.407104), 'val_loss_cos1': np.float64(0.90004), 'val_loss_entropy': np.float64(2.191005)}}
|
|
2024-11-13 20:25:53,500 (server:353) INFO: Server: Starting evaluation at the end of round 56.
|
|
2024-11-13 20:25:53,500 (server:359) INFO: ----------- Starting a new training round (Round #57) -------------
|
|
2024-11-13 20:27:23,164 (client:354) INFO: {'Role': 'Client #2', 'Round': 57, 'Results_raw': {'train_loss': 10.628808, 'val_loss': 10.90214, 'test_loss': 10.050975}}
|
|
2024-11-13 20:27:58,392 (client:354) INFO: {'Role': 'Client #10', 'Round': 57, 'Results_raw': {'train_loss': 14.969279, 'val_loss': 15.290217, 'test_loss': 15.077248}}
|
|
2024-11-13 20:28:32,288 (client:354) INFO: {'Role': 'Client #5', 'Round': 57, 'Results_raw': {'train_loss': 5.843497, 'val_loss': 5.89684, 'test_loss': 5.813452}}
|
|
2024-11-13 20:29:05,743 (client:354) INFO: {'Role': 'Client #7', 'Round': 57, 'Results_raw': {'train_loss': 10.956049, 'val_loss': 10.860298, 'test_loss': 10.028786}}
|
|
2024-11-13 20:29:38,055 (client:354) INFO: {'Role': 'Client #4', 'Round': 57, 'Results_raw': {'train_loss': 7.201072, 'val_loss': 6.44045, 'test_loss': 6.571432}}
|
|
2024-11-13 20:30:09,746 (client:354) INFO: {'Role': 'Client #6', 'Round': 57, 'Results_raw': {'train_loss': 8.890911, 'val_loss': 8.99364, 'test_loss': 9.045296}}
|
|
2024-11-13 20:30:41,459 (client:354) INFO: {'Role': 'Client #8', 'Round': 57, 'Results_raw': {'train_loss': 7.505269, 'val_loss': 14.642678, 'test_loss': 8.334557}}
|
|
2024-11-13 20:31:13,539 (client:354) INFO: {'Role': 'Client #1', 'Round': 57, 'Results_raw': {'train_loss': 8.640272, 'val_loss': 7.974936, 'test_loss': 8.398561}}
|
|
2024-11-13 20:31:45,416 (client:354) INFO: {'Role': 'Client #9', 'Round': 57, 'Results_raw': {'train_loss': 12.475356, 'val_loss': 15.257372, 'test_loss': 11.615363}}
|
|
2024-11-13 20:32:17,866 (client:354) INFO: {'Role': 'Client #3', 'Round': 57, 'Results_raw': {'train_loss': 8.856833, 'val_loss': 8.64336, 'test_loss': 9.150842}}
|
|
2024-11-13 20:32:17,869 (server:615) INFO: {'Role': 'Server #', 'Round': 56, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.080785), 'test_loss': np.float64(56604.362778), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.452682), 'val_loss': np.float64(61433.441815)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.080785), 'test_loss': np.float64(56604.362778), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.452682), 'val_loss': np.float64(61433.441815)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(7.966894), 'test_avg_loss_bottom_decile': np.float64(8.368062), 'test_avg_loss_top_decile': np.float64(31.81635), 'test_avg_loss_min': np.float64(8.285507), 'test_avg_loss_max': np.float64(31.81635), 'test_avg_loss_bottom10%': np.float64(8.285507), 'test_avg_loss_top10%': np.float64(31.81635), 'test_avg_loss_cos1': np.float64(0.896059), 'test_avg_loss_entropy': np.float64(2.188864), 'test_loss_std': np.float64(28043.467813), 'test_loss_bottom_decile': np.float64(29455.578491), 'test_loss_top_decile': np.float64(111993.553345), 'test_loss_min': np.float64(29164.986298), 'test_loss_max': np.float64(111993.553345), 'test_loss_bottom10%': np.float64(29164.986298), 'test_loss_top10%': np.float64(111993.553345), 'test_loss_cos1': np.float64(0.896059), 'test_loss_entropy': np.float64(2.188864), 'val_avg_loss_std': np.float64(8.485797), 'val_avg_loss_bottom_decile': np.float64(8.649635), 'val_avg_loss_top_decile': np.float64(32.328087), 'val_avg_loss_min': np.float64(8.482627), 'val_avg_loss_max': np.float64(32.328087), 'val_avg_loss_bottom10%': np.float64(8.482627), 'val_avg_loss_top10%': np.float64(32.328087), 'val_avg_loss_cos1': np.float64(0.89933), 'val_avg_loss_entropy': np.float64(2.190118), 'val_loss_std': np.float64(29870.004938), 'val_loss_bottom_decile': np.float64(30446.716339), 'val_loss_top_decile': np.float64(113794.866272), 'val_loss_min': np.float64(29858.848175), 'val_loss_max': np.float64(113794.866272), 'val_loss_bottom10%': np.float64(29858.848175), 'val_loss_top10%': np.float64(113794.866272), 'val_loss_cos1': np.float64(0.89933), 'val_loss_entropy': np.float64(2.190118)}}
|
|
2024-11-13 20:32:17,902 (server:353) INFO: Server: Starting evaluation at the end of round 57.
|
|
2024-11-13 20:32:17,902 (server:359) INFO: ----------- Starting a new training round (Round #58) -------------
|
|
2024-11-13 20:33:46,482 (client:354) INFO: {'Role': 'Client #6', 'Round': 58, 'Results_raw': {'train_loss': 8.903213, 'val_loss': 9.02598, 'test_loss': 9.183336}}
|
|
2024-11-13 20:34:18,372 (client:354) INFO: {'Role': 'Client #8', 'Round': 58, 'Results_raw': {'train_loss': 7.421811, 'val_loss': 17.174918, 'test_loss': 7.961401}}
|
|
2024-11-13 20:34:50,261 (client:354) INFO: {'Role': 'Client #10', 'Round': 58, 'Results_raw': {'train_loss': 14.660554, 'val_loss': 15.19399, 'test_loss': 14.859541}}
|
|
2024-11-13 20:35:22,537 (client:354) INFO: {'Role': 'Client #9', 'Round': 58, 'Results_raw': {'train_loss': 12.841276, 'val_loss': 15.142561, 'test_loss': 11.800247}}
|
|
2024-11-13 20:35:54,718 (client:354) INFO: {'Role': 'Client #4', 'Round': 58, 'Results_raw': {'train_loss': 7.20929, 'val_loss': 6.436141, 'test_loss': 6.564814}}
|
|
2024-11-13 20:36:27,255 (client:354) INFO: {'Role': 'Client #2', 'Round': 58, 'Results_raw': {'train_loss': 10.572618, 'val_loss': 10.851029, 'test_loss': 10.001625}}
|
|
2024-11-13 20:36:59,476 (client:354) INFO: {'Role': 'Client #3', 'Round': 58, 'Results_raw': {'train_loss': 8.891103, 'val_loss': 8.565833, 'test_loss': 9.068379}}
|
|
2024-11-13 20:37:31,538 (client:354) INFO: {'Role': 'Client #5', 'Round': 58, 'Results_raw': {'train_loss': 5.863448, 'val_loss': 5.919663, 'test_loss': 5.954013}}
|
|
2024-11-13 20:38:03,707 (client:354) INFO: {'Role': 'Client #7', 'Round': 58, 'Results_raw': {'train_loss': 10.891931, 'val_loss': 10.874628, 'test_loss': 10.077867}}
|
|
2024-11-13 20:38:36,202 (client:354) INFO: {'Role': 'Client #1', 'Round': 58, 'Results_raw': {'train_loss': 8.640554, 'val_loss': 8.013075, 'test_loss': 8.435258}}
|
|
2024-11-13 20:38:36,205 (server:615) INFO: {'Role': 'Server #', 'Round': 57, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.255593), 'test_loss': np.float64(57219.686731), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.622801), 'val_loss': np.float64(62032.260794)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.255593), 'test_loss': np.float64(57219.686731), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.622801), 'val_loss': np.float64(62032.260794)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(8.185033), 'test_avg_loss_bottom_decile': np.float64(8.404564), 'test_avg_loss_top_decile': np.float64(32.076744), 'test_avg_loss_min': np.float64(8.351572), 'test_avg_loss_max': np.float64(32.076744), 'test_avg_loss_bottom10%': np.float64(8.351572), 'test_avg_loss_top10%': np.float64(32.076744), 'test_avg_loss_cos1': np.float64(0.893166), 'test_avg_loss_entropy': np.float64(2.185245), 'test_loss_std': np.float64(28811.315232), 'test_loss_bottom_decile': np.float64(29584.066254), 'test_loss_top_decile': np.float64(112910.140015), 'test_loss_min': np.float64(29397.531769), 'test_loss_max': np.float64(112910.140015), 'test_loss_bottom10%': np.float64(29397.531769), 'test_loss_top10%': np.float64(112910.140015), 'test_loss_cos1': np.float64(0.893166), 'test_loss_entropy': np.float64(2.185245), 'val_avg_loss_std': np.float64(8.731347), 'val_avg_loss_bottom_decile': np.float64(8.691321), 'val_avg_loss_top_decile': np.float64(33.287785), 'val_avg_loss_min': np.float64(8.521372), 'val_avg_loss_max': np.float64(33.287785), 'val_avg_loss_bottom10%': np.float64(8.521372), 'val_avg_loss_top10%': np.float64(33.287785), 'val_avg_loss_cos1': np.float64(0.896049), 'val_avg_loss_entropy': np.float64(2.186226), 'val_loss_std': np.float64(30734.341179), 'val_loss_bottom_decile': np.float64(30593.448914), 'val_loss_top_decile': np.float64(117173.004517), 'val_loss_min': np.float64(29995.229065), 'val_loss_max': np.float64(117173.004517), 'val_loss_bottom10%': np.float64(29995.229065), 'val_loss_top10%': np.float64(117173.004517), 'val_loss_cos1': np.float64(0.896049), 'val_loss_entropy': np.float64(2.186226)}}
|
|
2024-11-13 20:38:36,235 (server:353) INFO: Server: Starting evaluation at the end of round 58.
|
|
2024-11-13 20:38:36,235 (server:359) INFO: ----------- Starting a new training round (Round #59) -------------
|
|
2024-11-13 20:40:04,032 (client:354) INFO: {'Role': 'Client #1', 'Round': 59, 'Results_raw': {'train_loss': 8.635906, 'val_loss': 8.044542, 'test_loss': 8.450731}}
|
|
2024-11-13 20:40:36,578 (client:354) INFO: {'Role': 'Client #10', 'Round': 59, 'Results_raw': {'train_loss': 14.580843, 'val_loss': 15.264417, 'test_loss': 14.981586}}
|
|
2024-11-13 20:41:08,555 (client:354) INFO: {'Role': 'Client #5', 'Round': 59, 'Results_raw': {'train_loss': 5.840803, 'val_loss': 6.004803, 'test_loss': 5.942561}}
|
|
2024-11-13 20:41:40,637 (client:354) INFO: {'Role': 'Client #3', 'Round': 59, 'Results_raw': {'train_loss': 8.851521, 'val_loss': 8.522485, 'test_loss': 8.98118}}
|
|
2024-11-13 20:42:13,510 (client:354) INFO: {'Role': 'Client #8', 'Round': 59, 'Results_raw': {'train_loss': 7.373177, 'val_loss': 16.610852, 'test_loss': 7.961005}}
|
|
2024-11-13 20:42:47,361 (client:354) INFO: {'Role': 'Client #2', 'Round': 59, 'Results_raw': {'train_loss': 10.432765, 'val_loss': 11.069272, 'test_loss': 10.118089}}
|
|
2024-11-13 20:43:22,366 (client:354) INFO: {'Role': 'Client #6', 'Round': 59, 'Results_raw': {'train_loss': 8.851788, 'val_loss': 8.814834, 'test_loss': 9.035521}}
|
|
2024-11-13 20:43:57,296 (client:354) INFO: {'Role': 'Client #7', 'Round': 59, 'Results_raw': {'train_loss': 10.968858, 'val_loss': 10.796232, 'test_loss': 9.880173}}
|
|
2024-11-13 20:44:31,866 (client:354) INFO: {'Role': 'Client #9', 'Round': 59, 'Results_raw': {'train_loss': 12.537931, 'val_loss': 15.189246, 'test_loss': 11.517268}}
|
|
2024-11-13 20:45:07,210 (client:354) INFO: {'Role': 'Client #4', 'Round': 59, 'Results_raw': {'train_loss': 7.180937, 'val_loss': 6.513835, 'test_loss': 6.66696}}
|
|
2024-11-13 20:45:07,212 (server:615) INFO: {'Role': 'Server #', 'Round': 58, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.081107), 'test_loss': np.float64(56605.494977), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.467896), 'val_loss': np.float64(61486.99472)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.081107), 'test_loss': np.float64(56605.494977), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.467896), 'val_loss': np.float64(61486.99472)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(8.066628), 'test_avg_loss_bottom_decile': np.float64(8.335308), 'test_avg_loss_top_decile': np.float64(32.043116), 'test_avg_loss_min': np.float64(8.232084), 'test_avg_loss_max': np.float64(32.043116), 'test_avg_loss_bottom10%': np.float64(8.232084), 'test_avg_loss_top10%': np.float64(32.043116), 'test_avg_loss_cos1': np.float64(0.893847), 'test_avg_loss_entropy': np.float64(2.186308), 'test_loss_std': np.float64(28394.530902), 'test_loss_bottom_decile': np.float64(29340.283691), 'test_loss_top_decile': np.float64(112791.766846), 'test_loss_min': np.float64(28976.936432), 'test_loss_max': np.float64(112791.766846), 'test_loss_bottom10%': np.float64(28976.936432), 'test_loss_top10%': np.float64(112791.766846), 'test_loss_cos1': np.float64(0.893847), 'test_loss_entropy': np.float64(2.186308), 'val_avg_loss_std': np.float64(8.562839), 'val_avg_loss_bottom_decile': np.float64(8.59861), 'val_avg_loss_top_decile': np.float64(32.54685), 'val_avg_loss_min': np.float64(8.461918), 'val_avg_loss_max': np.float64(32.54685), 'val_avg_loss_bottom10%': np.float64(8.461918), 'val_avg_loss_top10%': np.float64(32.54685), 'val_avg_loss_cos1': np.float64(0.897918), 'val_avg_loss_entropy': np.float64(2.188335), 'val_loss_std': np.float64(30141.194554), 'val_loss_bottom_decile': np.float64(30267.108704), 'val_loss_top_decile': np.float64(114564.913635), 'val_loss_min': np.float64(29785.950592), 'val_loss_max': np.float64(114564.913635), 'val_loss_bottom10%': np.float64(29785.950592), 'val_loss_top10%': np.float64(114564.913635), 'val_loss_cos1': np.float64(0.897918), 'val_loss_entropy': np.float64(2.188335)}}
|
|
2024-11-13 20:45:07,243 (server:353) INFO: Server: Starting evaluation at the end of round 59.
|
|
2024-11-13 20:45:07,244 (server:359) INFO: ----------- Starting a new training round (Round #60) -------------
|
|
2024-11-13 20:46:37,396 (client:354) INFO: {'Role': 'Client #4', 'Round': 60, 'Results_raw': {'train_loss': 7.22088, 'val_loss': 6.460829, 'test_loss': 6.614829}}
|
|
2024-11-13 20:47:11,678 (client:354) INFO: {'Role': 'Client #10', 'Round': 60, 'Results_raw': {'train_loss': 14.556518, 'val_loss': 15.587755, 'test_loss': 14.846614}}
|
|
2024-11-13 20:47:45,394 (client:354) INFO: {'Role': 'Client #1', 'Round': 60, 'Results_raw': {'train_loss': 8.619511, 'val_loss': 8.021919, 'test_loss': 8.42959}}
|
|
2024-11-13 20:48:17,547 (client:354) INFO: {'Role': 'Client #9', 'Round': 60, 'Results_raw': {'train_loss': 12.674865, 'val_loss': 15.118345, 'test_loss': 11.53086}}
|
|
2024-11-13 20:48:52,126 (client:354) INFO: {'Role': 'Client #5', 'Round': 60, 'Results_raw': {'train_loss': 5.798565, 'val_loss': 5.761903, 'test_loss': 5.743481}}
|
|
2024-11-13 20:49:25,562 (client:354) INFO: {'Role': 'Client #3', 'Round': 60, 'Results_raw': {'train_loss': 8.854079, 'val_loss': 8.536531, 'test_loss': 9.037059}}
|
|
2024-11-13 20:49:59,000 (client:354) INFO: {'Role': 'Client #7', 'Round': 60, 'Results_raw': {'train_loss': 10.790943, 'val_loss': 10.807269, 'test_loss': 9.969225}}
|
|
2024-11-13 20:50:32,362 (client:354) INFO: {'Role': 'Client #2', 'Round': 60, 'Results_raw': {'train_loss': 10.452878, 'val_loss': 10.868792, 'test_loss': 9.994044}}
|
|
2024-11-13 20:51:05,832 (client:354) INFO: {'Role': 'Client #6', 'Round': 60, 'Results_raw': {'train_loss': 8.963948, 'val_loss': 8.85823, 'test_loss': 8.933699}}
|
|
2024-11-13 20:51:39,454 (client:354) INFO: {'Role': 'Client #8', 'Round': 60, 'Results_raw': {'train_loss': 7.378874, 'val_loss': 18.477302, 'test_loss': 8.027081}}
|
|
2024-11-13 20:51:39,457 (server:615) INFO: {'Role': 'Server #', 'Round': 59, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.245843), 'test_loss': np.float64(57185.366339), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.639025), 'val_loss': np.float64(62089.369083)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.245843), 'test_loss': np.float64(57185.366339), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.639025), 'val_loss': np.float64(62089.369083)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(8.116539), 'test_avg_loss_bottom_decile': np.float64(8.392027), 'test_avg_loss_top_decile': np.float64(31.911869), 'test_avg_loss_min': np.float64(8.300242), 'test_avg_loss_max': np.float64(31.911869), 'test_avg_loss_bottom10%': np.float64(8.300242), 'test_avg_loss_top10%': np.float64(31.911869), 'test_avg_loss_cos1': np.float64(0.894568), 'test_avg_loss_entropy': np.float64(2.186691), 'test_loss_std': np.float64(28570.217769), 'test_loss_bottom_decile': np.float64(29539.934113), 'test_loss_top_decile': np.float64(112329.779236), 'test_loss_min': np.float64(29216.851562), 'test_loss_max': np.float64(112329.779236), 'test_loss_bottom10%': np.float64(29216.851562), 'test_loss_top10%': np.float64(112329.779236), 'test_loss_cos1': np.float64(0.894568), 'test_loss_entropy': np.float64(2.186691), 'val_avg_loss_std': np.float64(8.627527), 'val_avg_loss_bottom_decile': np.float64(8.691735), 'val_avg_loss_top_decile': np.float64(33.046362), 'val_avg_loss_min': np.float64(8.519523), 'val_avg_loss_max': np.float64(33.046362), 'val_avg_loss_bottom10%': np.float64(8.519523), 'val_avg_loss_top10%': np.float64(33.046362), 'val_avg_loss_cos1': np.float64(0.898304), 'val_avg_loss_entropy': np.float64(2.188551), 'val_loss_std': np.float64(30368.894943), 'val_loss_bottom_decile': np.float64(30594.907898), 'val_loss_top_decile': np.float64(116323.192566), 'val_loss_min': np.float64(29988.719421), 'val_loss_max': np.float64(116323.192566), 'val_loss_bottom10%': np.float64(29988.719421), 'val_loss_top10%': np.float64(116323.192566), 'val_loss_cos1': np.float64(0.898304), 'val_loss_entropy': np.float64(2.188551)}}
|
|
2024-11-13 20:51:39,489 (server:353) INFO: Server: Starting evaluation at the end of round 60.
|
|
2024-11-13 20:51:39,490 (server:359) INFO: ----------- Starting a new training round (Round #61) -------------
|
|
2024-11-13 20:53:09,551 (client:354) INFO: {'Role': 'Client #6', 'Round': 61, 'Results_raw': {'train_loss': 8.896161, 'val_loss': 9.125542, 'test_loss': 9.213771}}
|
|
2024-11-13 20:53:42,212 (client:354) INFO: {'Role': 'Client #2', 'Round': 61, 'Results_raw': {'train_loss': 10.394607, 'val_loss': 10.679426, 'test_loss': 9.81457}}
|
|
2024-11-13 20:54:14,224 (client:354) INFO: {'Role': 'Client #8', 'Round': 61, 'Results_raw': {'train_loss': 7.375941, 'val_loss': 16.382711, 'test_loss': 7.873815}}
|
|
2024-11-13 20:54:46,359 (client:354) INFO: {'Role': 'Client #4', 'Round': 61, 'Results_raw': {'train_loss': 7.210016, 'val_loss': 6.451936, 'test_loss': 6.555581}}
|
|
2024-11-13 20:55:18,336 (client:354) INFO: {'Role': 'Client #5', 'Round': 61, 'Results_raw': {'train_loss': 5.908595, 'val_loss': 5.888582, 'test_loss': 5.958464}}
|
|
2024-11-13 20:55:50,381 (client:354) INFO: {'Role': 'Client #7', 'Round': 61, 'Results_raw': {'train_loss': 10.871597, 'val_loss': 10.812908, 'test_loss': 9.925349}}
|
|
2024-11-13 20:56:22,409 (client:354) INFO: {'Role': 'Client #9', 'Round': 61, 'Results_raw': {'train_loss': 12.686748, 'val_loss': 15.086182, 'test_loss': 11.509054}}
|
|
2024-11-13 20:56:54,548 (client:354) INFO: {'Role': 'Client #10', 'Round': 61, 'Results_raw': {'train_loss': 14.687239, 'val_loss': 16.048111, 'test_loss': 15.655371}}
|
|
2024-11-13 20:57:27,794 (client:354) INFO: {'Role': 'Client #1', 'Round': 61, 'Results_raw': {'train_loss': 8.59714, 'val_loss': 8.130074, 'test_loss': 8.538062}}
|
|
2024-11-13 20:57:59,681 (client:354) INFO: {'Role': 'Client #3', 'Round': 61, 'Results_raw': {'train_loss': 8.822564, 'val_loss': 8.559903, 'test_loss': 9.028944}}
|
|
2024-11-13 20:57:59,684 (server:615) INFO: {'Role': 'Server #', 'Round': 60, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.098481), 'test_loss': np.float64(56666.654788), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.487066), 'val_loss': np.float64(61554.472452)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.098481), 'test_loss': np.float64(56666.654788), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.487066), 'val_loss': np.float64(61554.472452)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(7.984901), 'test_avg_loss_bottom_decile': np.float64(8.415827), 'test_avg_loss_top_decile': np.float64(31.583975), 'test_avg_loss_min': np.float64(8.31964), 'test_avg_loss_max': np.float64(31.583975), 'test_avg_loss_bottom10%': np.float64(8.31964), 'test_avg_loss_top10%': np.float64(31.583975), 'test_avg_loss_cos1': np.float64(0.895855), 'test_avg_loss_entropy': np.float64(2.188677), 'test_loss_std': np.float64(28106.850783), 'test_loss_bottom_decile': np.float64(29623.70932), 'test_loss_top_decile': np.float64(111175.590454), 'test_loss_min': np.float64(29285.132385), 'test_loss_max': np.float64(111175.590454), 'test_loss_bottom10%': np.float64(29285.132385), 'test_loss_top10%': np.float64(111175.590454), 'test_loss_cos1': np.float64(0.895855), 'test_loss_entropy': np.float64(2.188677), 'val_avg_loss_std': np.float64(8.510343), 'val_avg_loss_bottom_decile': np.float64(8.678151), 'val_avg_loss_top_decile': np.float64(32.819773), 'val_avg_loss_min': np.float64(8.531874), 'val_avg_loss_max': np.float64(32.819773), 'val_avg_loss_bottom10%': np.float64(8.531874), 'val_avg_loss_top10%': np.float64(32.819773), 'val_avg_loss_cos1': np.float64(0.899172), 'val_avg_loss_entropy': np.float64(2.189993), 'val_loss_std': np.float64(29956.405685), 'val_loss_bottom_decile': np.float64(30547.090942), 'val_loss_top_decile': np.float64(115525.599487), 'val_loss_min': np.float64(30032.19632), 'val_loss_max': np.float64(115525.599487), 'val_loss_bottom10%': np.float64(30032.19632), 'val_loss_top10%': np.float64(115525.599487), 'val_loss_cos1': np.float64(0.899172), 'val_loss_entropy': np.float64(2.189993)}}
|
|
2024-11-13 20:57:59,712 (server:353) INFO: Server: Starting evaluation at the end of round 61.
|
|
2024-11-13 20:57:59,712 (server:359) INFO: ----------- Starting a new training round (Round #62) -------------
|
|
2024-11-13 20:59:27,952 (client:354) INFO: {'Role': 'Client #4', 'Round': 62, 'Results_raw': {'train_loss': 7.242982, 'val_loss': 6.576958, 'test_loss': 6.689361}}
|
|
2024-11-13 21:00:01,095 (client:354) INFO: {'Role': 'Client #8', 'Round': 62, 'Results_raw': {'train_loss': 7.421172, 'val_loss': 15.724459, 'test_loss': 7.850123}}
|
|
2024-11-13 21:00:34,444 (client:354) INFO: {'Role': 'Client #3', 'Round': 62, 'Results_raw': {'train_loss': 8.839866, 'val_loss': 8.499495, 'test_loss': 8.988344}}
|
|
2024-11-13 21:01:06,881 (client:354) INFO: {'Role': 'Client #10', 'Round': 62, 'Results_raw': {'train_loss': 14.480042, 'val_loss': 15.206677, 'test_loss': 14.760085}}
|
|
2024-11-13 21:01:38,787 (client:354) INFO: {'Role': 'Client #2', 'Round': 62, 'Results_raw': {'train_loss': 10.504169, 'val_loss': 10.942841, 'test_loss': 10.160194}}
|
|
2024-11-13 21:02:11,429 (client:354) INFO: {'Role': 'Client #6', 'Round': 62, 'Results_raw': {'train_loss': 8.872839, 'val_loss': 8.890055, 'test_loss': 9.036947}}
|
|
2024-11-13 21:02:45,412 (client:354) INFO: {'Role': 'Client #9', 'Round': 62, 'Results_raw': {'train_loss': 12.852095, 'val_loss': 15.423654, 'test_loss': 11.997572}}
|
|
2024-11-13 21:03:21,962 (client:354) INFO: {'Role': 'Client #5', 'Round': 62, 'Results_raw': {'train_loss': 5.763985, 'val_loss': 5.95594, 'test_loss': 6.042376}}
|
|
2024-11-13 21:03:59,272 (client:354) INFO: {'Role': 'Client #7', 'Round': 62, 'Results_raw': {'train_loss': 10.901361, 'val_loss': 10.955863, 'test_loss': 10.077447}}
|
|
2024-11-13 21:04:36,504 (client:354) INFO: {'Role': 'Client #1', 'Round': 62, 'Results_raw': {'train_loss': 8.600665, 'val_loss': 8.089048, 'test_loss': 8.495128}}
|
|
2024-11-13 21:04:36,507 (server:615) INFO: {'Role': 'Server #', 'Round': 61, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.016701), 'test_loss': np.float64(56378.786798), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.369006), 'val_loss': np.float64(61138.901208)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.016701), 'test_loss': np.float64(56378.786798), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.369006), 'val_loss': np.float64(61138.901208)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(7.957522), 'test_avg_loss_bottom_decile': np.float64(8.44226), 'test_avg_loss_top_decile': np.float64(31.672435), 'test_avg_loss_min': np.float64(8.321288), 'test_avg_loss_max': np.float64(31.672435), 'test_avg_loss_bottom10%': np.float64(8.321288), 'test_avg_loss_top10%': np.float64(31.672435), 'test_avg_loss_cos1': np.float64(0.895561), 'test_avg_loss_entropy': np.float64(2.188595), 'test_loss_std': np.float64(28010.477991), 'test_loss_bottom_decile': np.float64(29716.754852), 'test_loss_top_decile': np.float64(111486.972412), 'test_loss_min': np.float64(29290.932465), 'test_loss_max': np.float64(111486.972412), 'test_loss_bottom10%': np.float64(29290.932465), 'test_loss_top10%': np.float64(111486.972412), 'test_loss_cos1': np.float64(0.895561), 'test_loss_entropy': np.float64(2.188595), 'val_avg_loss_std': np.float64(8.492743), 'val_avg_loss_bottom_decile': np.float64(8.631906), 'val_avg_loss_top_decile': np.float64(32.444072), 'val_avg_loss_min': np.float64(8.571552), 'val_avg_loss_max': np.float64(32.444072), 'val_avg_loss_bottom10%': np.float64(8.571552), 'val_avg_loss_top10%': np.float64(32.444072), 'val_avg_loss_cos1': np.float64(0.898359), 'val_avg_loss_entropy': np.float64(2.18932), 'val_loss_std': np.float64(29894.456766), 'val_loss_bottom_decile': np.float64(30384.309692), 'val_loss_top_decile': np.float64(114203.13501), 'val_loss_min': np.float64(30171.861908), 'val_loss_max': np.float64(114203.13501), 'val_loss_bottom10%': np.float64(30171.861908), 'val_loss_top10%': np.float64(114203.13501), 'val_loss_cos1': np.float64(0.898359), 'val_loss_entropy': np.float64(2.18932)}}
|
|
2024-11-13 21:04:36,544 (server:353) INFO: Server: Starting evaluation at the end of round 62.
|
|
2024-11-13 21:04:36,544 (server:359) INFO: ----------- Starting a new training round (Round #63) -------------
|
|
2024-11-13 21:06:25,321 (client:354) INFO: {'Role': 'Client #8', 'Round': 63, 'Results_raw': {'train_loss': 7.394771, 'val_loss': 18.873385, 'test_loss': 8.141571}}
|
|
2024-11-13 21:07:02,378 (client:354) INFO: {'Role': 'Client #3', 'Round': 63, 'Results_raw': {'train_loss': 8.832132, 'val_loss': 8.553374, 'test_loss': 9.037206}}
|
|
2024-11-13 21:07:39,758 (client:354) INFO: {'Role': 'Client #10', 'Round': 63, 'Results_raw': {'train_loss': 14.535709, 'val_loss': 15.316271, 'test_loss': 15.125823}}
|
|
2024-11-13 21:08:16,695 (client:354) INFO: {'Role': 'Client #1', 'Round': 63, 'Results_raw': {'train_loss': 8.587796, 'val_loss': 8.011624, 'test_loss': 8.434881}}
|
|
2024-11-13 21:08:54,410 (client:354) INFO: {'Role': 'Client #9', 'Round': 63, 'Results_raw': {'train_loss': 12.339758, 'val_loss': 15.613915, 'test_loss': 11.992933}}
|
|
2024-11-13 21:09:32,113 (client:354) INFO: {'Role': 'Client #7', 'Round': 63, 'Results_raw': {'train_loss': 10.851834, 'val_loss': 10.793224, 'test_loss': 9.91908}}
|
|
2024-11-13 21:10:08,951 (client:354) INFO: {'Role': 'Client #4', 'Round': 63, 'Results_raw': {'train_loss': 7.170478, 'val_loss': 6.500452, 'test_loss': 6.665344}}
|
|
2024-11-13 21:10:45,958 (client:354) INFO: {'Role': 'Client #5', 'Round': 63, 'Results_raw': {'train_loss': 5.787307, 'val_loss': 5.914749, 'test_loss': 5.906005}}
|
|
2024-11-13 21:11:23,841 (client:354) INFO: {'Role': 'Client #2', 'Round': 63, 'Results_raw': {'train_loss': 10.574748, 'val_loss': 10.784013, 'test_loss': 9.999896}}
|
|
2024-11-13 21:12:00,315 (client:354) INFO: {'Role': 'Client #6', 'Round': 63, 'Results_raw': {'train_loss': 8.868368, 'val_loss': 8.852611, 'test_loss': 8.964009}}
|
|
2024-11-13 21:12:00,317 (server:615) INFO: {'Role': 'Server #', 'Round': 62, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.112002), 'test_loss': np.float64(56714.248227), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.512768), 'val_loss': np.float64(61644.943741)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.112002), 'test_loss': np.float64(56714.248227), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.512768), 'val_loss': np.float64(61644.943741)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(8.031097), 'test_avg_loss_bottom_decile': np.float64(8.392128), 'test_avg_loss_top_decile': np.float64(30.993181), 'test_avg_loss_min': np.float64(8.291058), 'test_avg_loss_max': np.float64(30.993181), 'test_avg_loss_bottom10%': np.float64(8.291058), 'test_avg_loss_top10%': np.float64(30.993181), 'test_avg_loss_cos1': np.float64(0.89498), 'test_avg_loss_entropy': np.float64(2.18739), 'test_loss_std': np.float64(28269.462876), 'test_loss_bottom_decile': np.float64(29540.289062), 'test_loss_top_decile': np.float64(109095.995972), 'test_loss_min': np.float64(29184.523895), 'test_loss_max': np.float64(109095.995972), 'test_loss_bottom10%': np.float64(29184.523895), 'test_loss_top10%': np.float64(109095.995972), 'test_loss_cos1': np.float64(0.89498), 'test_loss_entropy': np.float64(2.18739), 'val_avg_loss_std': np.float64(8.583599), 'val_avg_loss_bottom_decile': np.float64(8.62694), 'val_avg_loss_top_decile': np.float64(33.599538), 'val_avg_loss_min': np.float64(8.520623), 'val_avg_loss_max': np.float64(33.599538), 'val_avg_loss_bottom10%': np.float64(8.520623), 'val_avg_loss_top10%': np.float64(33.599538), 'val_avg_loss_cos1': np.float64(0.897943), 'val_avg_loss_entropy': np.float64(2.188517), 'val_loss_std': np.float64(30214.269469), 'val_loss_bottom_decile': np.float64(30366.829834), 'val_loss_top_decile': np.float64(118270.37384), 'val_loss_min': np.float64(29992.591705), 'val_loss_max': np.float64(118270.37384), 'val_loss_bottom10%': np.float64(29992.591705), 'val_loss_top10%': np.float64(118270.37384), 'val_loss_cos1': np.float64(0.897943), 'val_loss_entropy': np.float64(2.188517)}}
|
|
2024-11-13 21:12:00,346 (server:353) INFO: Server: Starting evaluation at the end of round 63.
|
|
2024-11-13 21:12:00,346 (server:359) INFO: ----------- Starting a new training round (Round #64) -------------
|
|
2024-11-13 21:13:45,835 (client:354) INFO: {'Role': 'Client #10', 'Round': 64, 'Results_raw': {'train_loss': 14.263391, 'val_loss': 15.413454, 'test_loss': 14.937817}}
|
|
2024-11-13 21:14:24,928 (client:354) INFO: {'Role': 'Client #9', 'Round': 64, 'Results_raw': {'train_loss': 12.783388, 'val_loss': 15.072892, 'test_loss': 11.689449}}
|
|
2024-11-13 21:15:03,840 (client:354) INFO: {'Role': 'Client #1', 'Round': 64, 'Results_raw': {'train_loss': 8.609745, 'val_loss': 8.096376, 'test_loss': 8.537785}}
|
|
2024-11-13 21:15:42,941 (client:354) INFO: {'Role': 'Client #5', 'Round': 64, 'Results_raw': {'train_loss': 5.772712, 'val_loss': 5.842673, 'test_loss': 5.845249}}
|
|
2024-11-13 21:16:23,797 (client:354) INFO: {'Role': 'Client #2', 'Round': 64, 'Results_raw': {'train_loss': 10.29719, 'val_loss': 10.95542, 'test_loss': 10.087113}}
|
|
2024-11-13 21:17:03,460 (client:354) INFO: {'Role': 'Client #7', 'Round': 64, 'Results_raw': {'train_loss': 10.923779, 'val_loss': 10.78223, 'test_loss': 9.998204}}
|
|
2024-11-13 21:17:43,529 (client:354) INFO: {'Role': 'Client #6', 'Round': 64, 'Results_raw': {'train_loss': 8.860863, 'val_loss': 8.773031, 'test_loss': 8.895245}}
|
|
2024-11-13 21:18:26,847 (client:354) INFO: {'Role': 'Client #8', 'Round': 64, 'Results_raw': {'train_loss': 7.339209, 'val_loss': 15.44187, 'test_loss': 7.705392}}
|
|
2024-11-13 21:19:09,098 (client:354) INFO: {'Role': 'Client #3', 'Round': 64, 'Results_raw': {'train_loss': 8.820148, 'val_loss': 8.478863, 'test_loss': 8.99044}}
|
|
2024-11-13 21:19:49,893 (client:354) INFO: {'Role': 'Client #4', 'Round': 64, 'Results_raw': {'train_loss': 7.150121, 'val_loss': 6.430763, 'test_loss': 6.600441}}
|
|
2024-11-13 21:19:49,896 (server:615) INFO: {'Role': 'Server #', 'Round': 63, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.107324), 'test_loss': np.float64(56697.779099), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.483538), 'val_loss': np.float64(61542.055234)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.107324), 'test_loss': np.float64(56697.779099), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.483538), 'val_loss': np.float64(61542.055234)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(8.043707), 'test_avg_loss_bottom_decile': np.float64(8.34545), 'test_avg_loss_top_decile': np.float64(31.732058), 'test_avg_loss_min': np.float64(8.285195), 'test_avg_loss_max': np.float64(31.732058), 'test_avg_loss_bottom10%': np.float64(8.285195), 'test_avg_loss_top10%': np.float64(31.732058), 'test_avg_loss_cos1': np.float64(0.894648), 'test_avg_loss_entropy': np.float64(2.18699), 'test_loss_std': np.float64(28313.849497), 'test_loss_bottom_decile': np.float64(29375.983704), 'test_loss_top_decile': np.float64(111696.843323), 'test_loss_min': np.float64(29163.885773), 'test_loss_max': np.float64(111696.843323), 'test_loss_bottom10%': np.float64(29163.885773), 'test_loss_top10%': np.float64(111696.843323), 'test_loss_cos1': np.float64(0.894648), 'test_loss_entropy': np.float64(2.18699), 'val_avg_loss_std': np.float64(8.571293), 'val_avg_loss_bottom_decile': np.float64(8.656803), 'val_avg_loss_top_decile': np.float64(32.74138), 'val_avg_loss_min': np.float64(8.46405), 'val_avg_loss_max': np.float64(32.74138), 'val_avg_loss_bottom10%': np.float64(8.46405), 'val_avg_loss_top10%': np.float64(32.74138), 'val_avg_loss_cos1': np.float64(0.897902), 'val_avg_loss_entropy': np.float64(2.188334), 'val_loss_std': np.float64(30170.952031), 'val_loss_bottom_decile': np.float64(30471.948029), 'val_loss_top_decile': np.float64(115249.656067), 'val_loss_min': np.float64(29793.456024), 'val_loss_max': np.float64(115249.656067), 'val_loss_bottom10%': np.float64(29793.456024), 'val_loss_top10%': np.float64(115249.656067), 'val_loss_cos1': np.float64(0.897902), 'val_loss_entropy': np.float64(2.188334)}}
|
|
2024-11-13 21:19:49,930 (server:353) INFO: Server: Starting evaluation at the end of round 64.
|
|
2024-11-13 21:19:49,931 (server:359) INFO: ----------- Starting a new training round (Round #65) -------------
|
|
2024-11-13 21:21:42,827 (client:354) INFO: {'Role': 'Client #2', 'Round': 65, 'Results_raw': {'train_loss': 10.517544, 'val_loss': 11.35307, 'test_loss': 10.399942}}
|
|
2024-11-13 21:22:23,171 (client:354) INFO: {'Role': 'Client #5', 'Round': 65, 'Results_raw': {'train_loss': 5.758579, 'val_loss': 5.895669, 'test_loss': 5.833844}}
|
|
2024-11-13 21:23:05,327 (client:354) INFO: {'Role': 'Client #10', 'Round': 65, 'Results_raw': {'train_loss': 14.826187, 'val_loss': 15.606958, 'test_loss': 15.100018}}
|
|
2024-11-13 21:23:46,642 (client:354) INFO: {'Role': 'Client #1', 'Round': 65, 'Results_raw': {'train_loss': 8.564408, 'val_loss': 8.106669, 'test_loss': 8.506017}}
|
|
2024-11-13 21:24:27,050 (client:354) INFO: {'Role': 'Client #7', 'Round': 65, 'Results_raw': {'train_loss': 10.798706, 'val_loss': 10.840214, 'test_loss': 10.007854}}
|
|
2024-11-13 21:25:06,351 (client:354) INFO: {'Role': 'Client #3', 'Round': 65, 'Results_raw': {'train_loss': 8.799331, 'val_loss': 8.465652, 'test_loss': 8.939353}}
|
|
2024-11-13 21:25:44,679 (client:354) INFO: {'Role': 'Client #9', 'Round': 65, 'Results_raw': {'train_loss': 12.322198, 'val_loss': 15.567938, 'test_loss': 11.999821}}
|
|
2024-11-13 21:26:24,783 (client:354) INFO: {'Role': 'Client #8', 'Round': 65, 'Results_raw': {'train_loss': 7.327371, 'val_loss': 15.083086, 'test_loss': 7.772559}}
|
|
2024-11-13 21:27:03,113 (client:354) INFO: {'Role': 'Client #4', 'Round': 65, 'Results_raw': {'train_loss': 7.129517, 'val_loss': 6.494243, 'test_loss': 6.627486}}
|
|
2024-11-13 21:27:40,748 (client:354) INFO: {'Role': 'Client #6', 'Round': 65, 'Results_raw': {'train_loss': 8.830661, 'val_loss': 9.01299, 'test_loss': 9.1833}}
|
|
2024-11-13 21:27:40,752 (server:615) INFO: {'Role': 'Server #', 'Round': 64, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(15.879955), 'test_loss': np.float64(55897.441782), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.267449), 'val_loss': np.float64(60781.420969)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(15.879955), 'test_loss': np.float64(55897.441782), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.267449), 'val_loss': np.float64(60781.420969)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(7.710199), 'test_avg_loss_bottom_decile': np.float64(8.344641), 'test_avg_loss_top_decile': np.float64(30.739371), 'test_avg_loss_min': np.float64(8.253398), 'test_avg_loss_max': np.float64(30.739371), 'test_avg_loss_bottom10%': np.float64(8.253398), 'test_avg_loss_top10%': np.float64(30.739371), 'test_avg_loss_cos1': np.float64(0.899573), 'test_avg_loss_entropy': np.float64(2.192821), 'test_loss_std': np.float64(27139.901045), 'test_loss_bottom_decile': np.float64(29373.135071), 'test_loss_top_decile': np.float64(108202.585938), 'test_loss_min': np.float64(29051.962341), 'test_loss_max': np.float64(108202.585938), 'test_loss_bottom10%': np.float64(29051.962341), 'test_loss_top10%': np.float64(108202.585938), 'test_loss_cos1': np.float64(0.899573), 'test_loss_entropy': np.float64(2.192821), 'val_avg_loss_std': np.float64(8.228944), 'val_avg_loss_bottom_decile': np.float64(8.608237), 'val_avg_loss_top_decile': np.float64(31.931294), 'val_avg_loss_min': np.float64(8.461284), 'val_avg_loss_max': np.float64(31.931294), 'val_avg_loss_bottom10%': np.float64(8.461284), 'val_avg_loss_top10%': np.float64(31.931294), 'val_avg_loss_cos1': np.float64(0.902732), 'val_avg_loss_entropy': np.float64(2.193965), 'val_loss_std': np.float64(28965.88402), 'val_loss_bottom_decile': np.float64(30300.993408), 'val_loss_top_decile': np.float64(112398.15332), 'val_loss_min': np.float64(29783.718964), 'val_loss_max': np.float64(112398.15332), 'val_loss_bottom10%': np.float64(29783.718964), 'val_loss_top10%': np.float64(112398.15332), 'val_loss_cos1': np.float64(0.902732), 'val_loss_entropy': np.float64(2.193965)}}
|
|
2024-11-13 21:27:40,793 (server:353) INFO: Server: Starting evaluation at the end of round 65.
|
|
2024-11-13 21:27:40,794 (server:359) INFO: ----------- Starting a new training round (Round #66) -------------
|
|
2024-11-13 21:29:30,009 (client:354) INFO: {'Role': 'Client #4', 'Round': 66, 'Results_raw': {'train_loss': 7.177462, 'val_loss': 6.451951, 'test_loss': 6.510241}}
|
|
2024-11-13 21:30:10,807 (client:354) INFO: {'Role': 'Client #6', 'Round': 66, 'Results_raw': {'train_loss': 8.839953, 'val_loss': 8.96493, 'test_loss': 9.14272}}
|
|
2024-11-13 21:30:49,626 (client:354) INFO: {'Role': 'Client #9', 'Round': 66, 'Results_raw': {'train_loss': 12.320014, 'val_loss': 15.022439, 'test_loss': 11.403725}}
|
|
2024-11-13 21:31:28,691 (client:354) INFO: {'Role': 'Client #5', 'Round': 66, 'Results_raw': {'train_loss': 5.734041, 'val_loss': 5.866667, 'test_loss': 5.664111}}
|
|
2024-11-13 21:32:09,424 (client:354) INFO: {'Role': 'Client #2', 'Round': 66, 'Results_raw': {'train_loss': 10.30174, 'val_loss': 10.965146, 'test_loss': 10.077072}}
|
|
2024-11-13 21:32:52,711 (client:354) INFO: {'Role': 'Client #10', 'Round': 66, 'Results_raw': {'train_loss': 14.393919, 'val_loss': 14.972019, 'test_loss': 14.797446}}
|
|
2024-11-13 21:33:35,538 (client:354) INFO: {'Role': 'Client #8', 'Round': 66, 'Results_raw': {'train_loss': 7.323864, 'val_loss': 15.466575, 'test_loss': 7.724366}}
|
|
2024-11-13 21:34:16,650 (client:354) INFO: {'Role': 'Client #1', 'Round': 66, 'Results_raw': {'train_loss': 8.608141, 'val_loss': 8.037931, 'test_loss': 8.446271}}
|
|
2024-11-13 21:34:57,700 (client:354) INFO: {'Role': 'Client #7', 'Round': 66, 'Results_raw': {'train_loss': 10.90776, 'val_loss': 10.845416, 'test_loss': 10.031509}}
|
|
2024-11-13 21:35:38,822 (client:354) INFO: {'Role': 'Client #3', 'Round': 66, 'Results_raw': {'train_loss': 8.799994, 'val_loss': 8.472673, 'test_loss': 8.98315}}
|
|
2024-11-13 21:35:38,827 (server:615) INFO: {'Role': 'Server #', 'Round': 65, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.078809), 'test_loss': np.float64(56597.406183), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.521658), 'val_loss': np.float64(61676.237762)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.078809), 'test_loss': np.float64(56597.406183), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.521658), 'val_loss': np.float64(61676.237762)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(8.033983), 'test_avg_loss_bottom_decile': np.float64(8.3428), 'test_avg_loss_top_decile': np.float64(31.771358), 'test_avg_loss_min': np.float64(8.208639), 'test_avg_loss_max': np.float64(31.771358), 'test_avg_loss_bottom10%': np.float64(8.208639), 'test_avg_loss_top10%': np.float64(31.771358), 'test_avg_loss_cos1': np.float64(0.894548), 'test_avg_loss_entropy': np.float64(2.18689), 'test_loss_std': np.float64(28279.61927), 'test_loss_bottom_decile': np.float64(29366.65567), 'test_loss_top_decile': np.float64(111835.178894), 'test_loss_min': np.float64(28894.408112), 'test_loss_max': np.float64(111835.178894), 'test_loss_bottom10%': np.float64(28894.408112), 'test_loss_top10%': np.float64(111835.178894), 'test_loss_cos1': np.float64(0.894548), 'test_loss_entropy': np.float64(2.18689), 'val_avg_loss_std': np.float64(8.569253), 'val_avg_loss_bottom_decile': np.float64(8.561149), 'val_avg_loss_top_decile': np.float64(32.599396), 'val_avg_loss_min': np.float64(8.455816), 'val_avg_loss_max': np.float64(32.599396), 'val_avg_loss_bottom10%': np.float64(8.455816), 'val_avg_loss_top10%': np.float64(32.599396), 'val_avg_loss_cos1': np.float64(0.898321), 'val_avg_loss_entropy': np.float64(2.188409), 'val_loss_std': np.float64(30163.769195), 'val_loss_bottom_decile': np.float64(30135.242859), 'val_loss_top_decile': np.float64(114749.873535), 'val_loss_min': np.float64(29764.47345), 'val_loss_max': np.float64(114749.873535), 'val_loss_bottom10%': np.float64(29764.47345), 'val_loss_top10%': np.float64(114749.873535), 'val_loss_cos1': np.float64(0.898321), 'val_loss_entropy': np.float64(2.188409)}}
|
|
2024-11-13 21:35:38,874 (server:353) INFO: Server: Starting evaluation at the end of round 66.
|
|
2024-11-13 21:35:38,875 (server:359) INFO: ----------- Starting a new training round (Round #67) -------------
|
|
2024-11-13 21:37:33,844 (client:354) INFO: {'Role': 'Client #3', 'Round': 67, 'Results_raw': {'train_loss': 8.828322, 'val_loss': 8.532957, 'test_loss': 8.995953}}
|
|
2024-11-13 21:38:12,513 (client:354) INFO: {'Role': 'Client #9', 'Round': 67, 'Results_raw': {'train_loss': 12.295293, 'val_loss': 15.28217, 'test_loss': 11.514049}}
|
|
2024-11-13 21:38:54,256 (client:354) INFO: {'Role': 'Client #5', 'Round': 67, 'Results_raw': {'train_loss': 5.837741, 'val_loss': 6.046258, 'test_loss': 5.778364}}
|
|
2024-11-13 21:39:32,819 (client:354) INFO: {'Role': 'Client #7', 'Round': 67, 'Results_raw': {'train_loss': 10.789134, 'val_loss': 10.772759, 'test_loss': 9.916225}}
|
|
2024-11-13 21:40:12,818 (client:354) INFO: {'Role': 'Client #4', 'Round': 67, 'Results_raw': {'train_loss': 7.137201, 'val_loss': 6.509285, 'test_loss': 6.665394}}
|
|
2024-11-13 21:40:53,942 (client:354) INFO: {'Role': 'Client #1', 'Round': 67, 'Results_raw': {'train_loss': 8.555247, 'val_loss': 8.089492, 'test_loss': 8.462472}}
|
|
2024-11-13 21:41:38,577 (client:354) INFO: {'Role': 'Client #6', 'Round': 67, 'Results_raw': {'train_loss': 8.803215, 'val_loss': 8.779421, 'test_loss': 8.880293}}
|
|
2024-11-13 21:42:24,731 (client:354) INFO: {'Role': 'Client #10', 'Round': 67, 'Results_raw': {'train_loss': 14.43233, 'val_loss': 15.539563, 'test_loss': 15.256391}}
|
|
2024-11-13 21:43:06,855 (client:354) INFO: {'Role': 'Client #2', 'Round': 67, 'Results_raw': {'train_loss': 10.33543, 'val_loss': 10.870775, 'test_loss': 9.977547}}
|
|
2024-11-13 21:43:48,602 (client:354) INFO: {'Role': 'Client #8', 'Round': 67, 'Results_raw': {'train_loss': 7.358591, 'val_loss': 15.726042, 'test_loss': 7.895268}}
|
|
2024-11-13 21:43:48,605 (server:615) INFO: {'Role': 'Server #', 'Round': 66, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.458236), 'test_loss': np.float64(57932.99191), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.842009), 'val_loss': np.float64(62803.871896)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.458236), 'test_loss': np.float64(57932.99191), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.842009), 'val_loss': np.float64(62803.871896)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(8.419243), 'test_avg_loss_bottom_decile': np.float64(8.398002), 'test_avg_loss_top_decile': np.float64(32.94007), 'test_avg_loss_min': np.float64(8.274903), 'test_avg_loss_max': np.float64(32.94007), 'test_avg_loss_bottom10%': np.float64(8.274903), 'test_avg_loss_top10%': np.float64(32.94007), 'test_avg_loss_cos1': np.float64(0.890276), 'test_avg_loss_entropy': np.float64(2.181501), 'test_loss_std': np.float64(29635.735051), 'test_loss_bottom_decile': np.float64(29560.966797), 'test_loss_top_decile': np.float64(115949.046753), 'test_loss_min': np.float64(29127.659241), 'test_loss_max': np.float64(115949.046753), 'test_loss_bottom10%': np.float64(29127.659241), 'test_loss_top10%': np.float64(115949.046753), 'test_loss_cos1': np.float64(0.890276), 'test_loss_entropy': np.float64(2.181501), 'val_avg_loss_std': np.float64(8.959771), 'val_avg_loss_bottom_decile': np.float64(8.606553), 'val_avg_loss_top_decile': np.float64(33.601311), 'val_avg_loss_min': np.float64(8.511369), 'val_avg_loss_max': np.float64(33.601311), 'val_avg_loss_bottom10%': np.float64(8.511369), 'val_avg_loss_top10%': np.float64(33.601311), 'val_avg_loss_cos1': np.float64(0.893649), 'val_avg_loss_entropy': np.float64(2.182919), 'val_loss_std': np.float64(31538.39382), 'val_loss_bottom_decile': np.float64(30295.066681), 'val_loss_top_decile': np.float64(118276.614258), 'val_loss_min': np.float64(29960.018341), 'val_loss_max': np.float64(118276.614258), 'val_loss_bottom10%': np.float64(29960.018341), 'val_loss_top10%': np.float64(118276.614258), 'val_loss_cos1': np.float64(0.893649), 'val_loss_entropy': np.float64(2.182919)}}
|
|
2024-11-13 21:43:48,649 (server:353) INFO: Server: Starting evaluation at the end of round 67.
|
|
2024-11-13 21:43:48,649 (server:359) INFO: ----------- Starting a new training round (Round #68) -------------
|
|
2024-11-13 21:45:52,797 (client:354) INFO: {'Role': 'Client #9', 'Round': 68, 'Results_raw': {'train_loss': 12.408269, 'val_loss': 15.451568, 'test_loss': 11.913635}}
|
|
2024-11-13 21:46:35,973 (client:354) INFO: {'Role': 'Client #2', 'Round': 68, 'Results_raw': {'train_loss': 10.543537, 'val_loss': 11.37748, 'test_loss': 10.45269}}
|
|
2024-11-13 21:47:19,822 (client:354) INFO: {'Role': 'Client #5', 'Round': 68, 'Results_raw': {'train_loss': 5.748267, 'val_loss': 6.016899, 'test_loss': 5.909113}}
|
|
2024-11-13 21:47:59,720 (client:354) INFO: {'Role': 'Client #1', 'Round': 68, 'Results_raw': {'train_loss': 8.563936, 'val_loss': 7.974106, 'test_loss': 8.425583}}
|
|
2024-11-13 21:48:39,363 (client:354) INFO: {'Role': 'Client #10', 'Round': 68, 'Results_raw': {'train_loss': 14.671595, 'val_loss': 15.829029, 'test_loss': 15.658693}}
|
|
2024-11-13 21:49:20,446 (client:354) INFO: {'Role': 'Client #4', 'Round': 68, 'Results_raw': {'train_loss': 7.157297, 'val_loss': 6.586111, 'test_loss': 6.779309}}
|
|
2024-11-13 21:49:59,727 (client:354) INFO: {'Role': 'Client #3', 'Round': 68, 'Results_raw': {'train_loss': 8.795667, 'val_loss': 8.51633, 'test_loss': 9.002639}}
|
|
2024-11-13 21:50:39,472 (client:354) INFO: {'Role': 'Client #7', 'Round': 68, 'Results_raw': {'train_loss': 10.862173, 'val_loss': 11.089897, 'test_loss': 10.293134}}
|
|
2024-11-13 21:51:21,572 (client:354) INFO: {'Role': 'Client #8', 'Round': 68, 'Results_raw': {'train_loss': 7.332699, 'val_loss': 17.42806, 'test_loss': 8.070795}}
|
|
2024-11-13 21:52:03,042 (client:354) INFO: {'Role': 'Client #6', 'Round': 68, 'Results_raw': {'train_loss': 8.797088, 'val_loss': 9.020628, 'test_loss': 9.135921}}
|
|
2024-11-13 21:52:03,045 (server:615) INFO: {'Role': 'Server #', 'Round': 67, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(15.798441), 'test_loss': np.float64(55610.512787), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.180103), 'val_loss': np.float64(60473.962485)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(15.798441), 'test_loss': np.float64(55610.512787), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.180103), 'val_loss': np.float64(60473.962485)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(7.671731), 'test_avg_loss_bottom_decile': np.float64(8.317317), 'test_avg_loss_top_decile': np.float64(30.56448), 'test_avg_loss_min': np.float64(8.265649), 'test_avg_loss_max': np.float64(30.56448), 'test_avg_loss_bottom10%': np.float64(8.265649), 'test_avg_loss_top10%': np.float64(30.56448), 'test_avg_loss_cos1': np.float64(0.899548), 'test_avg_loss_entropy': np.float64(2.193103), 'test_loss_std': np.float64(27004.493176), 'test_loss_bottom_decile': np.float64(29276.956116), 'test_loss_top_decile': np.float64(107586.969299), 'test_loss_min': np.float64(29095.085052), 'test_loss_max': np.float64(107586.969299), 'test_loss_bottom10%': np.float64(29095.085052), 'test_loss_top10%': np.float64(107586.969299), 'test_loss_cos1': np.float64(0.899548), 'test_loss_entropy': np.float64(2.193103), 'val_avg_loss_std': np.float64(8.201161), 'val_avg_loss_bottom_decile': np.float64(8.612605), 'val_avg_loss_top_decile': np.float64(31.965686), 'val_avg_loss_min': np.float64(8.434149), 'val_avg_loss_max': np.float64(31.965686), 'val_avg_loss_bottom10%': np.float64(8.434149), 'val_avg_loss_top10%': np.float64(31.965686), 'val_avg_loss_cos1': np.float64(0.902449), 'val_avg_loss_entropy': np.float64(2.193804), 'val_loss_std': np.float64(28868.087704), 'val_loss_bottom_decile': np.float64(30316.369629), 'val_loss_top_decile': np.float64(112519.215454), 'val_loss_min': np.float64(29688.205475), 'val_loss_max': np.float64(112519.215454), 'val_loss_bottom10%': np.float64(29688.205475), 'val_loss_top10%': np.float64(112519.215454), 'val_loss_cos1': np.float64(0.902449), 'val_loss_entropy': np.float64(2.193804)}}
|
|
2024-11-13 21:52:03,076 (server:353) INFO: Server: Starting evaluation at the end of round 68.
|
|
2024-11-13 21:52:03,076 (server:359) INFO: ----------- Starting a new training round (Round #69) -------------
|
|
2024-11-13 21:53:53,259 (client:354) INFO: {'Role': 'Client #10', 'Round': 69, 'Results_raw': {'train_loss': 14.481184, 'val_loss': 15.462077, 'test_loss': 15.237604}}
|
|
2024-11-13 21:54:32,658 (client:354) INFO: {'Role': 'Client #8', 'Round': 69, 'Results_raw': {'train_loss': 7.376713, 'val_loss': 18.280423, 'test_loss': 7.828687}}
|
|
2024-11-13 21:55:11,598 (client:354) INFO: {'Role': 'Client #6', 'Round': 69, 'Results_raw': {'train_loss': 8.835181, 'val_loss': 8.953623, 'test_loss': 9.010401}}
|
|
2024-11-13 21:55:49,426 (client:354) INFO: {'Role': 'Client #5', 'Round': 69, 'Results_raw': {'train_loss': 5.757606, 'val_loss': 5.779043, 'test_loss': 5.825499}}
|
|
2024-11-13 21:56:29,964 (client:354) INFO: {'Role': 'Client #9', 'Round': 69, 'Results_raw': {'train_loss': 12.503511, 'val_loss': 15.519371, 'test_loss': 11.716765}}
|
|
2024-11-13 21:57:10,630 (client:354) INFO: {'Role': 'Client #7', 'Round': 69, 'Results_raw': {'train_loss': 10.800297, 'val_loss': 10.924449, 'test_loss': 10.03377}}
|
|
2024-11-13 21:57:48,530 (client:354) INFO: {'Role': 'Client #2', 'Round': 69, 'Results_raw': {'train_loss': 10.287079, 'val_loss': 10.914865, 'test_loss': 10.236145}}
|
|
2024-11-13 21:58:27,109 (client:354) INFO: {'Role': 'Client #4', 'Round': 69, 'Results_raw': {'train_loss': 7.23301, 'val_loss': 6.539184, 'test_loss': 6.66987}}
|
|
2024-11-13 21:59:06,089 (client:354) INFO: {'Role': 'Client #1', 'Round': 69, 'Results_raw': {'train_loss': 8.536265, 'val_loss': 8.057999, 'test_loss': 8.465915}}
|
|
2024-11-13 21:59:44,613 (client:354) INFO: {'Role': 'Client #3', 'Round': 69, 'Results_raw': {'train_loss': 8.81454, 'val_loss': 8.693894, 'test_loss': 9.153865}}
|
|
2024-11-13 21:59:44,618 (server:615) INFO: {'Role': 'Server #', 'Round': 68, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.165265), 'test_loss': np.float64(56901.733759), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.565493), 'val_loss': np.float64(61830.534354)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(16.165265), 'test_loss': np.float64(56901.733759), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.565493), 'val_loss': np.float64(61830.534354)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(8.050847), 'test_avg_loss_bottom_decile': np.float64(8.378765), 'test_avg_loss_top_decile': np.float64(32.206544), 'test_avg_loss_min': np.float64(8.291879), 'test_avg_loss_max': np.float64(32.206544), 'test_avg_loss_bottom10%': np.float64(8.291879), 'test_avg_loss_top10%': np.float64(32.206544), 'test_avg_loss_cos1': np.float64(0.89513), 'test_avg_loss_entropy': np.float64(2.18746), 'test_loss_std': np.float64(28338.982068), 'test_loss_bottom_decile': np.float64(29493.254303), 'test_loss_top_decile': np.float64(113367.033142), 'test_loss_min': np.float64(29187.412659), 'test_loss_max': np.float64(113367.033142), 'test_loss_bottom10%': np.float64(29187.412659), 'test_loss_top10%': np.float64(113367.033142), 'test_loss_cos1': np.float64(0.89513), 'test_loss_entropy': np.float64(2.18746), 'val_avg_loss_std': np.float64(8.581408), 'val_avg_loss_bottom_decile': np.float64(8.605517), 'val_avg_loss_top_decile': np.float64(32.692781), 'val_avg_loss_min': np.float64(8.497416), 'val_avg_loss_max': np.float64(32.692781), 'val_avg_loss_bottom10%': np.float64(8.497416), 'val_avg_loss_top10%': np.float64(32.692781), 'val_avg_loss_cos1': np.float64(0.898509), 'val_avg_loss_entropy': np.float64(2.188652), 'val_loss_std': np.float64(30206.554825), 'val_loss_bottom_decile': np.float64(30291.420746), 'val_loss_top_decile': np.float64(115078.59082), 'val_loss_min': np.float64(29910.904053), 'val_loss_max': np.float64(115078.59082), 'val_loss_bottom10%': np.float64(29910.904053), 'val_loss_top10%': np.float64(115078.59082), 'val_loss_cos1': np.float64(0.898509), 'val_loss_entropy': np.float64(2.188652)}}
|
|
2024-11-13 21:59:44,664 (server:370) INFO: Server: Training is finished! Starting evaluation.
|
|
2024-11-13 22:00:51,896 (server:615) INFO: {'Role': 'Server #', 'Round': 69, 'Results_weighted_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(15.951275), 'test_loss': np.float64(56148.488596), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.364767), 'val_loss': np.float64(61123.979611)}, 'Results_avg': {'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(15.951275), 'test_loss': np.float64(56148.488596), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.364767), 'val_loss': np.float64(61123.979611)}, 'Results_fairness': {'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(7.828651), 'test_avg_loss_bottom_decile': np.float64(8.343513), 'test_avg_loss_top_decile': np.float64(31.055774), 'test_avg_loss_min': np.float64(8.268829), 'test_avg_loss_max': np.float64(31.055774), 'test_avg_loss_bottom10%': np.float64(8.268829), 'test_avg_loss_top10%': np.float64(31.055774), 'test_avg_loss_cos1': np.float64(0.897712), 'test_avg_loss_entropy': np.float64(2.190667), 'test_loss_std': np.float64(27556.852059), 'test_loss_bottom_decile': np.float64(29369.166534), 'test_loss_top_decile': np.float64(109316.324219), 'test_loss_min': np.float64(29106.276886), 'test_loss_max': np.float64(109316.324219), 'test_loss_bottom10%': np.float64(29106.276886), 'test_loss_top10%': np.float64(109316.324219), 'test_loss_cos1': np.float64(0.897712), 'test_loss_entropy': np.float64(2.190667), 'val_avg_loss_std': np.float64(8.35522), 'val_avg_loss_bottom_decile': np.float64(8.60725), 'val_avg_loss_top_decile': np.float64(32.32784), 'val_avg_loss_min': np.float64(8.456885), 'val_avg_loss_max': np.float64(32.32784), 'val_avg_loss_bottom10%': np.float64(8.456885), 'val_avg_loss_top10%': np.float64(32.32784), 'val_avg_loss_cos1': np.float64(0.901115), 'val_avg_loss_entropy': np.float64(2.19197), 'val_loss_std': np.float64(29410.373029), 'val_loss_bottom_decile': np.float64(30297.519104), 'val_loss_top_decile': np.float64(113793.997192), 'val_loss_min': np.float64(29768.234924), 'val_loss_max': np.float64(113793.997192), 'val_loss_bottom10%': np.float64(29768.234924), 'val_loss_top10%': np.float64(113793.997192), 'val_loss_cos1': np.float64(0.901115), 'val_loss_entropy': np.float64(2.19197)}}
|
|
2024-11-13 22:00:51,899 (server:420) INFO: Server: Final evaluation is finished! Starting merging results.
|
|
2024-11-13 22:00:51,908 (server:546) INFO: {'Role': 'Server #', 'Round': 'Final', 'Results_raw': {'client_best_individual': {'val_loss': 29688.205475, 'test_total': 3520.0, 'test_avg_loss': 8.265649, 'test_loss': 29095.085052, 'val_total': 3520.0, 'val_avg_loss': 8.434149}, 'client_summarized_weighted_avg': {'val_loss': np.float64(60473.962485), 'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(15.798441), 'test_loss': np.float64(55610.512787), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.180103)}, 'client_summarized_avg': {'val_loss': np.float64(60473.962485), 'test_total': np.float64(3520.0), 'test_avg_loss': np.float64(15.798441), 'test_loss': np.float64(55610.512787), 'val_total': np.float64(3520.0), 'val_avg_loss': np.float64(17.180103)}, 'client_summarized_fairness': {'val_loss_entropy': np.float64(2.07183), 'val_loss_cos1': np.float64(0.815944), 'val_loss_top10%': np.float64(567983.946045), 'val_loss_bottom10%': np.float64(89326.009033), 'val_loss_max': np.float64(567983.946045), 'val_loss_min': np.float64(89326.009033), 'val_loss_top_decile': np.float64(567983.946045), 'val_loss_bottom_decile': np.float64(92915.005676), 'val_loss_std': np.float64(172872.756838), 'test_total': np.float64(3520.0), 'val_total': np.float64(3520.0), 'test_avg_loss_std': np.float64(46.251132), 'test_avg_loss_bottom_decile': np.float64(26.195873), 'test_avg_loss_top_decile': np.float64(156.573859), 'test_avg_loss_min': np.float64(25.715192), 'test_avg_loss_max': np.float64(156.573859), 'test_avg_loss_bottom10%': np.float64(25.715192), 'test_avg_loss_top10%': np.float64(156.573859), 'test_avg_loss_cos1': np.float64(0.819109), 'test_avg_loss_entropy': np.float64(2.07647), 'test_loss_std': np.float64(162803.984082), 'test_loss_bottom_decile': np.float64(92209.471863), 'test_loss_top_decile': np.float64(551139.982422), 'test_loss_min': np.float64(90517.476074), 'test_loss_max': np.float64(551139.982422), 'test_loss_bottom10%': np.float64(90517.476074), 'test_loss_top10%': np.float64(551139.982422), 'test_loss_cos1': np.float64(0.819109), 'test_loss_entropy': np.float64(2.07647), 'val_avg_loss_std': np.float64(49.111579), 'val_avg_loss_bottom_decile': np.float64(26.396308), 'val_avg_loss_top_decile': np.float64(161.359076), 'val_avg_loss_min': np.float64(25.376707), 'val_avg_loss_max': np.float64(161.359076), 'val_avg_loss_bottom10%': np.float64(25.376707), 'val_avg_loss_top10%': np.float64(161.359076), 'val_avg_loss_cos1': np.float64(0.815944), 'val_avg_loss_entropy': np.float64(2.07183)}}}
|
|
2024-11-13 22:00:51,909 (server:565) INFO: {'Role': 'Client #1', 'Round': 70, 'Results_raw': {'test_total': 3520, 'test_avg_loss': 10.195647, 'test_loss': 35888.678284, 'val_total': 3520, 'val_avg_loss': 9.983412, 'val_loss': 35141.609589}}
|
|
2024-11-13 22:00:51,910 (server:565) INFO: {'Role': 'Client #2', 'Round': 70, 'Results_raw': {'test_total': 3520, 'test_avg_loss': 17.938441, 'test_loss': 63143.311523, 'val_total': 3520, 'val_avg_loss': 19.00294, 'val_loss': 66890.34906}}
|
|
2024-11-13 22:00:51,910 (server:565) INFO: {'Role': 'Client #3', 'Round': 70, 'Results_raw': {'test_total': 3520, 'test_avg_loss': 10.927747, 'test_loss': 38465.670227, 'val_total': 3520, 'val_avg_loss': 10.558732, 'val_loss': 37166.737915}}
|
|
2024-11-13 22:00:51,910 (server:565) INFO: {'Role': 'Client #4', 'Round': 70, 'Results_raw': {'test_total': 3520, 'test_avg_loss': 8.343513, 'test_loss': 29369.166534, 'val_total': 3520, 'val_avg_loss': 8.456885, 'val_loss': 29768.234924}}
|
|
2024-11-13 22:00:51,911 (server:565) INFO: {'Role': 'Client #5', 'Round': 70, 'Results_raw': {'test_total': 3520, 'test_avg_loss': 8.268829, 'test_loss': 29106.276886, 'val_total': 3520, 'val_avg_loss': 8.60725, 'val_loss': 30297.519104}}
|
|
2024-11-13 22:00:51,911 (server:565) INFO: {'Role': 'Client #6', 'Round': 70, 'Results_raw': {'test_total': 3520, 'test_avg_loss': 14.366938, 'test_loss': 50571.622375, 'val_total': 3520, 'val_avg_loss': 14.993554, 'val_loss': 52777.309052}}
|
|
2024-11-13 22:00:51,911 (server:565) INFO: {'Role': 'Client #7', 'Round': 70, 'Results_raw': {'test_total': 3520, 'test_avg_loss': 19.60264, 'test_loss': 69001.292603, 'val_total': 3520, 'val_avg_loss': 20.694646, 'val_loss': 72845.155457}}
|
|
2024-11-13 22:00:51,911 (server:565) INFO: {'Role': 'Client #8', 'Round': 70, 'Results_raw': {'test_total': 3520, 'test_avg_loss': 10.301649, 'test_loss': 36261.803741, 'val_total': 3520, 'val_avg_loss': 17.589685, 'val_loss': 61915.689789}}
|
|
2024-11-13 22:00:51,912 (server:565) INFO: {'Role': 'Client #9', 'Round': 70, 'Results_raw': {'test_total': 3520, 'test_avg_loss': 28.511574, 'test_loss': 100360.739563, 'val_total': 3520, 'val_avg_loss': 32.32784, 'val_loss': 113793.997192}}
|
|
2024-11-13 22:00:51,912 (server:565) INFO: {'Role': 'Client #10', 'Round': 70, 'Results_raw': {'test_total': 3520, 'test_avg_loss': 31.055774, 'test_loss': 109316.324219, 'val_total': 3520, 'val_avg_loss': 31.432726, 'val_loss': 110643.194031}}
|
|
2024-11-13 22:00:51,913 (monitor:173) INFO: In worker #0, the system-related metrics are: {'id': 0, 'fl_end_time_minutes': 626.63965, 'total_model_size': 0, 'total_flops': 0, 'total_upload_bytes': 0, 'total_download_bytes': 11787256, 'global_convergence_round': 0, 'local_convergence_round': 0, 'global_convergence_time_minutes': 0, 'local_convergence_time_minutes': 0}
|
|
2024-11-13 22:00:51,916 (client:582) INFO: ================= client 1 received finish message =================
|
|
2024-11-13 22:00:51,919 (monitor:173) INFO: In worker #1, the system-related metrics are: {'id': 1, 'fl_end_time_minutes': 626.639442, 'total_model_size': 563454, 'total_flops': 11319874399680.0, 'total_upload_bytes': 0, 'total_download_bytes': 2595040, 'global_convergence_round': 0, 'local_convergence_round': 0, 'global_convergence_time_minutes': 0, 'local_convergence_time_minutes': 0}
|
|
2024-11-13 22:00:51,919 (client:582) INFO: ================= client 2 received finish message =================
|
|
2024-11-13 22:00:51,921 (monitor:173) INFO: In worker #2, the system-related metrics are: {'id': 2, 'fl_end_time_minutes': 626.639025, 'total_model_size': 563454, 'total_flops': 11319874399680.0, 'total_upload_bytes': 0, 'total_download_bytes': 2595040, 'global_convergence_round': 0, 'local_convergence_round': 0, 'global_convergence_time_minutes': 0, 'local_convergence_time_minutes': 0}
|
|
2024-11-13 22:00:51,921 (client:582) INFO: ================= client 3 received finish message =================
|
|
2024-11-13 22:00:51,923 (monitor:173) INFO: In worker #3, the system-related metrics are: {'id': 3, 'fl_end_time_minutes': 626.638704, 'total_model_size': 563454, 'total_flops': 11319874399680.0, 'total_upload_bytes': 0, 'total_download_bytes': 2595040, 'global_convergence_round': 0, 'local_convergence_round': 0, 'global_convergence_time_minutes': 0, 'local_convergence_time_minutes': 0}
|
|
2024-11-13 22:00:51,924 (client:582) INFO: ================= client 4 received finish message =================
|
|
2024-11-13 22:00:51,926 (monitor:173) INFO: In worker #4, the system-related metrics are: {'id': 4, 'fl_end_time_minutes': 626.638465, 'total_model_size': 563454, 'total_flops': 11319874399680.0, 'total_upload_bytes': 0, 'total_download_bytes': 2595040, 'global_convergence_round': 0, 'local_convergence_round': 0, 'global_convergence_time_minutes': 0, 'local_convergence_time_minutes': 0}
|
|
2024-11-13 22:00:51,926 (client:582) INFO: ================= client 5 received finish message =================
|
|
2024-11-13 22:00:51,928 (monitor:173) INFO: In worker #5, the system-related metrics are: {'id': 5, 'fl_end_time_minutes': 626.638205, 'total_model_size': 563454, 'total_flops': 11319874399680.0, 'total_upload_bytes': 0, 'total_download_bytes': 2595040, 'global_convergence_round': 0, 'local_convergence_round': 0, 'global_convergence_time_minutes': 0, 'local_convergence_time_minutes': 0}
|
|
2024-11-13 22:00:51,928 (client:582) INFO: ================= client 6 received finish message =================
|
|
2024-11-13 22:00:51,930 (monitor:173) INFO: In worker #6, the system-related metrics are: {'id': 6, 'fl_end_time_minutes': 626.637895, 'total_model_size': 563454, 'total_flops': 11319874399680.0, 'total_upload_bytes': 0, 'total_download_bytes': 2595040, 'global_convergence_round': 0, 'local_convergence_round': 0, 'global_convergence_time_minutes': 0, 'local_convergence_time_minutes': 0}
|
|
2024-11-13 22:00:51,930 (client:582) INFO: ================= client 7 received finish message =================
|
|
2024-11-13 22:00:51,932 (monitor:173) INFO: In worker #7, the system-related metrics are: {'id': 7, 'fl_end_time_minutes': 626.637544, 'total_model_size': 563454, 'total_flops': 11319874399680.0, 'total_upload_bytes': 0, 'total_download_bytes': 2595040, 'global_convergence_round': 0, 'local_convergence_round': 0, 'global_convergence_time_minutes': 0, 'local_convergence_time_minutes': 0}
|
|
2024-11-13 22:00:51,933 (client:582) INFO: ================= client 8 received finish message =================
|
|
2024-11-13 22:00:51,934 (monitor:173) INFO: In worker #8, the system-related metrics are: {'id': 8, 'fl_end_time_minutes': 626.637198, 'total_model_size': 563454, 'total_flops': 11319874399680.0, 'total_upload_bytes': 0, 'total_download_bytes': 2595040, 'global_convergence_round': 0, 'local_convergence_round': 0, 'global_convergence_time_minutes': 0, 'local_convergence_time_minutes': 0}
|
|
2024-11-13 22:00:51,935 (client:582) INFO: ================= client 9 received finish message =================
|
|
2024-11-13 22:00:51,937 (monitor:173) INFO: In worker #9, the system-related metrics are: {'id': 9, 'fl_end_time_minutes': 626.636871, 'total_model_size': 563454, 'total_flops': 11319874399680.0, 'total_upload_bytes': 0, 'total_download_bytes': 2595040, 'global_convergence_round': 0, 'local_convergence_round': 0, 'global_convergence_time_minutes': 0, 'local_convergence_time_minutes': 0}
|
|
2024-11-13 22:00:51,937 (client:582) INFO: ================= client 10 received finish message =================
|
|
2024-11-13 22:00:51,939 (monitor:173) INFO: In worker #10, the system-related metrics are: {'id': 10, 'fl_end_time_minutes': 626.636566, 'total_model_size': 563454, 'total_flops': 11319874399680.0, 'total_upload_bytes': 0, 'total_download_bytes': 2595040, 'global_convergence_round': 0, 'local_convergence_round': 0, 'global_convergence_time_minutes': 0, 'local_convergence_time_minutes': 0}
|
|
2024-11-13 22:00:51,939 (monitor:338) INFO: We will compress the file eval_results.raw into a .gz file, and delete the old one
|
|
2024-11-13 22:00:51,972 (monitor:246) INFO: After merging the system metrics from all works, we got avg: defaultdict(None, {'id': 'sys_avg', 'sys_avg/fl_end_time_minutes': np.float64(626.638142), 'sys_avg/total_model_size': '500.23K', 'sys_avg/total_flops': '9.36T', 'sys_avg/total_upload_bytes': '0.0', 'sys_avg/total_download_bytes': '3.27M', 'sys_avg/global_convergence_round': np.float64(0.0), 'sys_avg/local_convergence_round': np.float64(0.0), 'sys_avg/global_convergence_time_minutes': np.float64(0.0), 'sys_avg/local_convergence_time_minutes': np.float64(0.0)})
|
|
2024-11-13 22:00:51,973 (monitor:249) INFO: After merging the system metrics from all works, we got std: defaultdict(None, {'id': 'sys_std', 'sys_std/fl_end_time_minutes': np.float64(0.000981), 'sys_std/total_model_size': '158.19K', 'sys_std/total_flops': '2.96T', 'sys_std/total_upload_bytes': '0.0', 'sys_std/total_download_bytes': '2.52M', 'sys_std/global_convergence_round': np.float64(0.0), 'sys_std/local_convergence_round': np.float64(0.0), 'sys_std/global_convergence_time_minutes': np.float64(0.0), 'sys_std/local_convergence_time_minutes': np.float64(0.0)})
|