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command: |
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- python3 |
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- ${program} |
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- --overwrite_output_dir |
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- --freeze_feature_encoder |
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- --gradient_checkpointing |
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- --fp16 |
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- --group_by_length |
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- --do_train |
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- --do_eval |
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- --load_best_model_at_end |
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- --push_to_hub |
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- --use_auth_token |
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- ${args} |
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method: random |
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metric: |
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goal: maximize |
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name: eval/bleu |
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parameters: |
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model_name_or_path: |
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value: ./ |
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task: |
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value: covost2 |
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language: |
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value: fr.en |
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eval_split_name: |
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value: test |
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output_dir: |
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value: ./output_dir |
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num_train_epochs: |
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value: 3 |
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per_device_train_batch_size: |
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value: 4 |
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per_device_eval_batch_size: |
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value: 4 |
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gradient_accumulation_steps: |
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value: 8 |
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generation_max_length: |
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value: 40 |
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generation_num_beams: |
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value: 1 |
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learning_rate: |
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distribution: log_uniform |
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max: -6.9 |
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min: -9.2 |
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hidden_dropout: |
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distribution: log_uniform |
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max: -1.6 |
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min: -3.4 |
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warmup_steps: |
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value: 500 |
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evaluation_strategy: |
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value: steps |
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max_duration_in_seconds: |
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value: 20 |
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save_steps: |
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value: 500 |
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eval_steps: |
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value: 500 |
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logging_steps: |
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value: 1 |
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metric_for_best_model: |
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value: bleu |
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greater_is_better: |
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value: True |
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program: run_xtreme_s.py |
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project: xtreme_s_xlsr_2_bart_covost2_fr_en |
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