Whisper Base Thai
This model is a fine-tuned version of openai/whisper-base on the mozilla-foundation/common_voice_16_0 th dataset. It achieves the following results on the evaluation set:
- Loss: 0.4390
- Wer: 44.5601
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: 5e-07
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 10000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.8395 | 1.02 | 500 | 0.7280 | 60.6811 |
| 0.7819 | 2.03 | 1000 | 0.6414 | 56.1244 |
| 0.6456 | 4.01 | 1500 | 0.5940 | 53.4778 |
| 0.6091 | 5.03 | 2000 | 0.5633 | 52.0691 |
| 0.5465 | 7.01 | 2500 | 0.5383 | 50.4822 |
| 0.5406 | 8.02 | 3000 | 0.5200 | 49.5537 |
| 0.4863 | 10.01 | 3500 | 0.5047 | 48.9992 |
| 0.4691 | 11.02 | 4000 | 0.4919 | 47.9767 |
| 0.5183 | 13.0 | 4500 | 0.4823 | 47.6833 |
| 0.5025 | 14.02 | 5000 | 0.4730 | 46.7202 |
| 0.5426 | 15.03 | 5500 | 0.4661 | 46.3501 |
| 0.4713 | 17.01 | 6000 | 0.4594 | 45.9985 |
| 0.4274 | 18.03 | 6500 | 0.4546 | 45.6061 |
| 0.4248 | 20.01 | 7000 | 0.4500 | 45.3598 |
| 0.4404 | 21.03 | 7500 | 0.4467 | 45.1097 |
| 0.4144 | 23.01 | 8000 | 0.4438 | 44.8411 |
| 0.4004 | 24.02 | 8500 | 0.4416 | 44.6938 |
| 0.4165 | 26.0 | 9000 | 0.4403 | 44.6443 |
| 0.4218 | 27.02 | 9500 | 0.4393 | 44.5750 |
| 0.453 | 28.03 | 10000 | 0.4390 | 44.5601 |
Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0