whisper-medium-mn-4
This model is a fine-tuned version of openai/whisper-medium on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6015
- Wer: 33.0293
- Cer: 10.9236
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: 1e-05
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 15000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 0.0362 | 4.26 | 1000 | 0.4204 | 40.2720 | 13.8389 |
| 0.0087 | 8.51 | 2000 | 0.4712 | 37.4918 | 12.9175 |
| 0.0044 | 12.77 | 3000 | 0.4893 | 36.3393 | 12.4727 |
| 0.0033 | 17.02 | 4000 | 0.5159 | 35.8423 | 12.2933 |
| 0.0017 | 21.28 | 5000 | 0.5183 | 35.2797 | 12.1104 |
| 0.0016 | 25.53 | 6000 | 0.5422 | 35.4326 | 11.7454 |
| 0.0011 | 29.79 | 7000 | 0.5361 | 34.5314 | 11.5196 |
| 0.0004 | 34.04 | 8000 | 0.5406 | 34.0998 | 11.3650 |
| 0.0006 | 38.3 | 9000 | 0.5540 | 33.8650 | 11.2912 |
| 0.0002 | 42.55 | 10000 | 0.5748 | 34.0889 | 11.5333 |
| 0.0003 | 46.81 | 11000 | 0.5771 | 34.5641 | 11.4895 |
| 0.0 | 51.06 | 12000 | 0.5809 | 33.4335 | 11.2070 |
| 0.0 | 55.32 | 13000 | 0.5941 | 33.2095 | 11.0009 |
| 0.0 | 59.57 | 14000 | 0.6015 | 33.0293 | 10.9236 |
| 0.0 | 63.83 | 15000 | 0.6045 | 33.0347 | 10.9125 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2