51 lines
1.1 KiB
YAML
51 lines
1.1 KiB
YAML
use_gpu: True
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device: 0
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seed: 12345
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outdir: exp/
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federate:
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mode: standalone
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method: fedavg
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total_round_num: 100
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client_num: 18
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data:
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type: hetero_nlp_tasks
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root: datasets/
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hetero_data_name: ['imdb', 'agnews', 'squad', 'newsqa', 'cnndm', 'msqg']
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num_of_client_for_data: [1, 3, 3, 2, 5, 4]
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num_workers: 0
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cache_dir: cache/
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hetero_synth_batch_size: 32
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hetero_synth_prim_weight: 0.5
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hetero_synth_feat_dim: 128
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num_contrast: 20000
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model:
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type: atc_model
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model_type: google/bert_uncased_L-2_H-128_A-2
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stage: contrast
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use_contrastive_loss: True
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contrast_topk: 20
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contrast_temp: 1.0
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aggregator:
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num_agg_topk: [16, 16, 16, 16, 8, 8]
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inside_weight: 1.0
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outside_weight: 0.0
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personalization:
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local_param: ['classifier', 'encoder.pooler', 'decoder', 'contrast_head']
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trainer:
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type: atc_trainer
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train:
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batch_or_epoch: batch
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optimizer:
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type: AdamW
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lr: 5e-4
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weight_decay: 0.01
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scheduler:
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type: warmup_step
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warmup_ratio: 0.1
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grad:
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grad_clip: 1.0
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eval:
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split: ['test']
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report: ['group_avg']
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freq: 100000000 # eval freq across rounds
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