whisper-small-mn-3
This model is a fine-tuned version of openai/whisper-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3277
- Wer: 30.3692
- Cer: 10.9030
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: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 15000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 0.3408 | 0.61 | 1000 | 0.4062 | 47.6841 | 17.3811 |
| 0.2261 | 1.22 | 2000 | 0.3262 | 37.8086 | 13.6466 |
| 0.2135 | 1.83 | 3000 | 0.2863 | 33.7175 | 12.2246 |
| 0.1643 | 2.43 | 4000 | 0.2803 | 32.5978 | 11.4526 |
| 0.1198 | 3.04 | 5000 | 0.2747 | 31.1121 | 11.0533 |
| 0.1279 | 3.65 | 6000 | 0.2757 | 30.7243 | 10.8927 |
| 0.0891 | 4.26 | 7000 | 0.2878 | 30.9209 | 11.0610 |
| 0.0899 | 4.87 | 8000 | 0.2906 | 30.6642 | 11.0799 |
| 0.0648 | 5.48 | 9000 | 0.3054 | 30.5986 | 10.9030 |
| 0.0436 | 6.09 | 10000 | 0.3184 | 30.5222 | 10.9434 |
| 0.0468 | 6.7 | 11000 | 0.3277 | 30.3692 | 10.9030 |
| 0.0291 | 7.3 | 12000 | 0.3411 | 30.9810 | 11.1572 |
| 0.0275 | 7.91 | 13000 | 0.3476 | 31.0684 | 11.1555 |
| 0.0196 | 8.52 | 14000 | 0.3572 | 30.9154 | 11.1065 |
| 0.0159 | 9.13 | 15000 | 0.3600 | 31.0356 | 11.2087 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2