whisper-small-mn-6
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: 0.3296
- Wer: 35.8860
- Cer: 13.3108
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 |
|---|---|---|---|---|---|
| 0.3774 | 0.8 | 1000 | 0.4319 | 53.2773 | 19.6627 |
| 0.2926 | 1.61 | 2000 | 0.3493 | 40.4960 | 15.0214 |
| 0.2331 | 2.41 | 3000 | 0.3346 | 39.1741 | 14.7689 |
| 0.1636 | 3.22 | 4000 | 0.3287 | 36.9237 | 13.7943 |
| 0.1157 | 4.02 | 5000 | 0.3296 | 35.8860 | 13.3108 |
| 0.1271 | 4.82 | 6000 | 0.3422 | 36.0717 | 13.5702 |
| 0.0879 | 5.63 | 7000 | 0.3661 | 36.6943 | 13.7780 |
| 0.0574 | 6.43 | 8000 | 0.3884 | 36.4595 | 13.5015 |
| 0.036 | 7.23 | 9000 | 0.4128 | 37.1422 | 13.8424 |
| 0.0229 | 8.04 | 10000 | 0.4321 | 36.8582 | 13.8475 |
| 0.0241 | 8.84 | 11000 | 0.4530 | 37.1095 | 13.8673 |
| 0.0123 | 9.65 | 12000 | 0.4763 | 37.5956 | 13.9583 |
| 0.007 | 10.45 | 13000 | 0.4939 | 37.3116 | 13.9360 |
| 0.0047 | 11.25 | 14000 | 0.5054 | 37.1750 | 13.8106 |
| 0.0036 | 12.06 | 15000 | 0.5093 | 37.5082 | 13.8930 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2