openai/whisper-base
This model is a fine-tuned version of openai/whisper-base on the pphuc25/VietMed-split-8-2 dataset. It achieves the following results on the evaluation set:
- Loss: 1.0352
- Wer: 27.1975
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 |
|---|---|---|---|---|
| 0.7081 | 1.0 | 569 | 0.7147 | 32.6304 |
| 0.5097 | 2.0 | 1138 | 0.6779 | 30.7670 |
| 0.3642 | 3.0 | 1707 | 0.6890 | 30.5144 |
| 0.2242 | 4.0 | 2276 | 0.7389 | 31.4662 |
| 0.1221 | 5.0 | 2845 | 0.7970 | 32.5828 |
| 0.07 | 6.0 | 3414 | 0.8480 | 30.3240 |
| 0.0411 | 7.0 | 3983 | 0.8862 | 29.4380 |
| 0.0288 | 8.0 | 4552 | 0.9171 | 29.9066 |
| 0.0199 | 9.0 | 5121 | 0.9572 | 29.6321 |
| 0.0105 | 10.0 | 5690 | 0.9698 | 28.6473 |
| 0.0068 | 11.0 | 6259 | 0.9811 | 29.5881 |
| 0.0084 | 12.0 | 6828 | 0.9985 | 28.7424 |
| 0.0024 | 13.0 | 7397 | 0.9903 | 29.3355 |
| 0.003 | 14.0 | 7966 | 1.0112 | 27.6588 |
| 0.0017 | 15.0 | 8535 | 1.0137 | 28.7205 |
| 0.0004 | 16.0 | 9104 | 1.0185 | 27.2305 |
| 0.0002 | 17.0 | 9673 | 1.0257 | 27.2964 |
| 0.0006 | 18.0 | 10242 | 1.0282 | 27.2817 |
| 0.0002 | 19.0 | 10811 | 1.0336 | 27.1609 |
| 0.0001 | 20.0 | 11380 | 1.0352 | 27.1975 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0
- Datasets 2.19.1
- Tokenizers 0.19.1