whisper-small-mn-2
This model is a fine-tuned version of openai/whisper-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7259
- Wer: 40.8783
- Cer: 13.9617
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 |
|---|---|---|---|---|---|
| 0.0839 | 4.26 | 1000 | 0.4647 | 45.7286 | 16.0020 |
| 0.0093 | 8.51 | 2000 | 0.5434 | 43.9753 | 15.2446 |
| 0.0044 | 12.77 | 3000 | 0.6009 | 43.6257 | 15.1717 |
| 0.0029 | 17.02 | 4000 | 0.6166 | 43.0031 | 14.7578 |
| 0.002 | 21.28 | 5000 | 0.6390 | 42.6098 | 14.7286 |
| 0.001 | 25.53 | 6000 | 0.6558 | 41.7468 | 14.3516 |
| 0.0021 | 29.79 | 7000 | 0.6714 | 42.3039 | 14.4589 |
| 0.0003 | 34.04 | 8000 | 0.6791 | 41.0586 | 13.9506 |
| 0.0001 | 38.3 | 9000 | 0.6949 | 41.3808 | 14.1670 |
| 0.0013 | 42.55 | 10000 | 0.6875 | 41.4682 | 14.2983 |
| 0.0001 | 46.81 | 11000 | 0.6937 | 40.9165 | 13.9549 |
| 0.0001 | 51.06 | 12000 | 0.7092 | 40.9275 | 13.9549 |
| 0.0 | 55.32 | 13000 | 0.7190 | 40.9657 | 13.9703 |
| 0.0 | 59.57 | 14000 | 0.7259 | 40.8783 | 13.9617 |
| 0.0 | 63.83 | 15000 | 0.7292 | 40.8838 | 13.9274 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2