openai/whisper-medium
This model is a fine-tuned version of openai/whisper-medium on the Hanhpt23/ChineseMed dataset. It achieves the following results on the evaluation set:
- Loss: 5.2602
- Wer: 128.5060
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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 3.1376 | 1.0 | 2222 | 3.0423 | 114.8827 |
| 2.4455 | 2.0 | 4444 | 3.0159 | 122.3240 |
| 1.5794 | 3.0 | 6666 | 3.4702 | 109.4448 |
| 0.885 | 4.0 | 8888 | 4.0015 | 122.7247 |
| 0.6963 | 5.0 | 11110 | 4.3781 | 109.8454 |
| 0.4926 | 6.0 | 13332 | 4.5503 | 105.9531 |
| 0.4615 | 7.0 | 15554 | 4.6635 | 108.9296 |
| 0.3744 | 8.0 | 17776 | 4.8384 | 113.3371 |
| 0.395 | 9.0 | 19998 | 4.9563 | 113.7378 |
| 0.3312 | 10.0 | 22220 | 4.9508 | 109.5592 |
| 0.3324 | 11.0 | 24442 | 5.0560 | 120.2633 |
| 0.3027 | 12.0 | 26664 | 4.9751 | 117.0006 |
| 0.3127 | 13.0 | 28886 | 5.1136 | 124.7853 |
| 0.2792 | 14.0 | 31108 | 5.1324 | 111.6772 |
| 0.3383 | 15.0 | 33330 | 5.1389 | 110.5896 |
| 0.2695 | 16.0 | 35552 | 5.1925 | 111.6199 |
| 0.2773 | 17.0 | 37774 | 5.1852 | 111.9061 |
| 0.2829 | 18.0 | 39996 | 5.2192 | 121.5226 |
| 0.2195 | 19.0 | 42218 | 5.2098 | 126.5598 |
| 0.2254 | 20.0 | 44440 | 5.2602 | 128.5060 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0
- Datasets 2.19.1
- Tokenizers 0.19.1