salmon-whisper-large-smj-lr5e-5
This model is a fine-tuned version of openai/whisper-large-v2 on the NbAiLab/salmon-asr-smj dataset.
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- lr_scheduler_type: linear
- per_device_train_batch_size: 6
- total_train_batch_size_per_node: 48
- total_train_batch_size: 48
- total_optimization_steps: 100,000
- starting_optimization_step: None
- finishing_optimization_step: 100,000
- num_train_dataset_workers: 32
- num_hosts: 1
- total_num_training_examples: 4,800,000
- steps_per_epoch: 385
- num_beams: None
- weight_decay: 0.01
- adam_beta1: 0.9
- adam_beta2: 0.98
- adam_epsilon: 1e-06
- dropout: True
- bpe_dropout_probability: 0.2
- activation_dropout_probability: 0.1
Training results
| step | validation_loss | train_loss | validation_wer | validation_cer | validation_exact_wer | validation_exact_cer |
|---|---|---|---|---|---|---|
| 0 | 4.2254 | 4.6413 | 112.7660 | 59.8700 | 108.1117 | 62.0594 |
| 10000 | 0.8720 | 0.3747 | 18.2181 | 5.2803 | 21.4096 | 5.6762 |
| 20000 | 1.1365 | 0.2741 | 15.2926 | 4.6304 | 18.0851 | 5.0588 |
| 30000 | 1.2561 | 0.2111 | 14.6277 | 4.0617 | 17.9521 | 4.5011 |
Framework versions
- Transformers 4.35.0
- Datasets 2.14.6
- Tokenizers 0.14.1
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