openai/whisper-medium
This model is a fine-tuned version of openai/whisper-medium on the pphuc25/VietMed-split-8-2 dataset. It achieves the following results on the evaluation set:
- Loss: 0.9216
- Wer: 20.0549
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 |
|---|---|---|---|---|
| 0.5881 | 1.0 | 569 | 0.5795 | 27.0181 |
| 0.3919 | 2.0 | 1138 | 0.5413 | 21.8451 |
| 0.2496 | 3.0 | 1707 | 0.6104 | 22.6213 |
| 0.1324 | 4.0 | 2276 | 0.6854 | 23.5695 |
| 0.0898 | 5.0 | 2845 | 0.7554 | 22.0245 |
| 0.0642 | 6.0 | 3414 | 0.7739 | 21.6804 |
| 0.0366 | 7.0 | 3983 | 0.8119 | 21.2667 |
| 0.026 | 8.0 | 4552 | 0.8180 | 21.4058 |
| 0.0243 | 9.0 | 5121 | 0.8560 | 22.1893 |
| 0.0168 | 10.0 | 5690 | 0.8636 | 21.3326 |
| 0.0203 | 11.0 | 6259 | 0.8314 | 20.8091 |
| 0.0101 | 12.0 | 6828 | 0.8892 | 21.3106 |
| 0.0093 | 13.0 | 7397 | 0.8793 | 21.2594 |
| 0.0046 | 14.0 | 7966 | 0.8985 | 20.4613 |
| 0.0026 | 15.0 | 8535 | 0.8907 | 20.5272 |
| 0.0021 | 16.0 | 9104 | 0.9033 | 20.3807 |
| 0.0029 | 17.0 | 9673 | 0.9153 | 20.2014 |
| 0.0005 | 18.0 | 10242 | 0.9080 | 20.2746 |
| 0.0001 | 19.0 | 10811 | 0.9195 | 20.1135 |
| 0.0002 | 20.0 | 11380 | 0.9216 | 20.0549 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0
- Datasets 2.19.1
- Tokenizers 0.19.1