openai/whisper-base
This model is a fine-tuned version of openai/whisper-base on the pphuc25/ChiMed dataset. It achieves the following results on the evaluation set:
- Loss: 1.2560
- Wer: 85.6582
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 |
|---|---|---|---|---|
| 0.7187 | 1.0 | 161 | 0.9482 | 110.4126 |
| 0.4241 | 2.0 | 322 | 0.9742 | 94.1061 |
| 0.2284 | 3.0 | 483 | 1.0348 | 100.9823 |
| 0.1019 | 4.0 | 644 | 1.0740 | 89.9804 |
| 0.0663 | 5.0 | 805 | 1.1215 | 87.4263 |
| 0.0473 | 6.0 | 966 | 1.1625 | 88.4086 |
| 0.0354 | 7.0 | 1127 | 1.1645 | 89.5874 |
| 0.0288 | 8.0 | 1288 | 1.1893 | 105.6974 |
| 0.0194 | 9.0 | 1449 | 1.1955 | 88.0157 |
| 0.0144 | 10.0 | 1610 | 1.1969 | 123.5756 |
| 0.011 | 11.0 | 1771 | 1.2305 | 90.3733 |
| 0.005 | 12.0 | 1932 | 1.2550 | 88.8016 |
| 0.0058 | 13.0 | 2093 | 1.2345 | 87.8193 |
| 0.0018 | 14.0 | 2254 | 1.2281 | 86.8369 |
| 0.0006 | 15.0 | 2415 | 1.2489 | 85.8546 |
| 0.0012 | 16.0 | 2576 | 1.2419 | 86.8369 |
| 0.0005 | 17.0 | 2737 | 1.2564 | 85.6582 |
| 0.0004 | 18.0 | 2898 | 1.2542 | 85.6582 |
| 0.0004 | 19.0 | 3059 | 1.2548 | 85.8546 |
| 0.0004 | 20.0 | 3220 | 1.2560 | 85.6582 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0
- Datasets 2.19.1
- Tokenizers 0.19.1