Whisper Medium
This model is a fine-tuned version of openai/whisper-medium on the b-brave-clean dataset. It achieves the following results on the evaluation set:
- Loss: 0.6398
- Wer: 41.8338
- Cer: 30.4702
- Lr: 0.0000
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: 0.0003
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.3
- num_epochs: 12
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer | Lr |
|---|---|---|---|---|---|---|
| 3.6633 | 1.0 | 168 | 1.8570 | 149.4269 | 97.5309 | 0.0001 |
| 1.2316 | 2.0 | 336 | 0.9484 | 66.4756 | 45.5477 | 0.0002 |
| 0.8773 | 3.0 | 504 | 0.8240 | 117.3352 | 102.2590 | 0.0002 |
| 0.5747 | 4.0 | 672 | 0.7314 | 76.3610 | 56.0809 | 0.0003 |
| 0.3652 | 5.0 | 840 | 0.6545 | 104.1547 | 90.4124 | 0.0002 |
| 0.2632 | 6.0 | 1008 | 0.6305 | 50.5731 | 34.6467 | 0.0002 |
| 0.1568 | 7.0 | 1176 | 0.5926 | 90.1146 | 80.4833 | 0.0002 |
| 0.104 | 8.0 | 1344 | 0.6388 | 47.5645 | 33.4121 | 0.0001 |
| 0.0356 | 9.0 | 1512 | 0.6073 | 42.8367 | 46.9398 | 0.0001 |
| 0.0189 | 10.0 | 1680 | 0.6361 | 42.5501 | 47.1500 | 0.0001 |
| 0.0089 | 11.0 | 1848 | 0.6385 | 41.9771 | 30.4965 | 0.0000 |
| 0.0108 | 11.9313 | 2004 | 0.6398 | 41.8338 | 30.4702 | 0.0000 |
Framework versions
- PEFT 0.14.0
- Transformers 4.48.3
- Pytorch 2.2.0
- Datasets 3.2.0
- Tokenizers 0.21.0