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Running
on
A10G
Running
on
A10G
| task_name: AudioSep | |
| data: | |
| datafiles: | |
| - 'datafiles/template.json' | |
| sampling_rate: 32000 | |
| segment_seconds: 5 | |
| loudness_norm: | |
| lower_db: -10 | |
| higher_db: 10 | |
| max_mix_num: 2 | |
| model: | |
| query_net: CLAP | |
| condition_size: 512 | |
| model_type: ResUNet30 | |
| input_channels: 1 | |
| output_channels: 1 | |
| resume_checkpoint: "" | |
| use_text_ratio: 1.0 | |
| train: | |
| optimizer: | |
| optimizer_type: AdamW | |
| learning_rate: 1e-3 | |
| warm_up_steps: 10000 | |
| reduce_lr_steps: 1000000 | |
| lr_lambda_type: constant_warm_up | |
| num_nodes: 1 | |
| num_workers: 6 | |
| loss_type: l1_wav | |
| sync_batchnorm: True | |
| batch_size_per_device: 12 | |
| steps_per_epoch: 10000 # Every 10000 steps is called an `epoch`. | |
| evaluate_step_frequency: 10000 # Evaluate every #evaluate_step_frequency steps. | |
| save_step_frequency: 20000 # Save every #save_step_frequency steps. | |
| early_stop_steps: 10000001 | |
| random_seed: 1234 | |