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| # Experiment Config for each experiment | |
| output_dir: /output | |
| logging_dir: runs/tb_log | |
| logging_steps: 10 | |
| seed: 1115 | |
| train_file: /csv/clotho/train.csv | |
| validation_file: /csv/clotho/valid.csv | |
| encodec_base_path: /data/clotho/encodec | |
| clap_base_path: /data/clotho/clap | |
| tokenizer_name: facebook/bart-large | |
| config_name_or_path: facebook/bart-large | |
| model_name_or_path: facebook/bart-large | |
| eval_num_captions: 5 | |
| overwrite_output_dir: False | |
| # Basic Config | |
| encodec_masking_prob: 0.15 | |
| encodec_masking_span: 10 | |
| num_train_epochs: 15 | |
| max_train_steps: null | |
| gradient_accumulation_steps: 1 | |
| per_device_train_batch_size: 64 | |
| per_device_eval_batch_size: 64 | |
| split_batches: true | |
| checkpointing_steps: epoch # 'epoch' to save for each epoch, or number of steps | |
| resume_from_checkpoint: null | |
| # Generation Config | |
| max_target_length: 128 | |
| val_max_target_length: 50 | |
| # Training Hyperparameters | |
| # "lr_schedulre_type" should be one of "linear", "cosine", "cosine_with_restarts", "polynomial", | |
| # "constant", "constant_with_warmpup", "inverse_sqrt", "reduce_lr_on_plateau", "two_stage_inverse_sqrt" | |
| lr_scheduler_type: inverse_sqrt | |
| learning_rate: 2.5e-5 # peak lr | |
| num_warmup_steps: 1000 | |
| weight_decay: 0.01 | |
| max_grad_norm: 1.0 | |
| # Others | |
| with_tracking: true | |
| report_to: tensorboard | |
| ignore_pad_token_for_loss: true | |
| preprocessing_num_workers: 32 | |
| use_slow_tokenizer: false | |
| overwrite_cache: false | |
| pad_to_max_length: false | |