Whisper Small Vietnamese
This model is a fine-tuned version of openai/whisper-small on the Vietnamese ASR Custom Corpus with 1 audiobook dataset. It achieves the following results on the evaluation set:
- Loss: 0.6499
- Wer: 78.4463
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: 16
- 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: 8
- training_steps: 80
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 5.0759 | 0.03 | 2 | 4.3984 | 33.2959 |
| 3.8512 | 0.05 | 4 | 3.7516 | 31.7467 |
| 3.1744 | 0.07 | 6 | 2.9537 | 31.2528 |
| 2.7374 | 0.1 | 8 | 2.4814 | 32.4427 |
| 2.3471 | 0.12 | 10 | 2.1517 | 72.1374 |
| 2.018 | 0.15 | 12 | 1.8614 | 127.7279 |
| 1.5275 | 0.17 | 14 | 1.5862 | 118.3431 |
| 1.4899 | 0.2 | 16 | 1.3252 | 127.5932 |
| 1.2433 | 0.23 | 18 | 1.1108 | 120.5433 |
| 1.0353 | 0.25 | 20 | 1.0291 | 112.0790 |
| 1.1132 | 0.28 | 22 | 0.9825 | 93.9156 |
| 1.0524 | 0.3 | 24 | 0.9412 | 87.9883 |
| 0.8907 | 0.33 | 26 | 0.9065 | 72.9232 |
| 0.8172 | 0.35 | 28 | 0.8786 | 64.9753 |
| 0.8563 | 0.38 | 30 | 0.8584 | 62.3934 |
| 1.0131 | 0.4 | 32 | 1.0352 | 56.7131 |
| 0.752 | 0.42 | 34 | 0.8189 | 62.1015 |
| 0.7312 | 0.45 | 36 | 0.8031 | 57.0723 |
| 0.8391 | 0.47 | 38 | 0.7888 | 63.4710 |
| 0.8875 | 0.5 | 40 | 0.7756 | 60.8217 |
| 0.7641 | 0.53 | 42 | 0.7633 | 61.7647 |
| 0.737 | 0.55 | 44 | 0.7519 | 61.2259 |
| 0.7782 | 0.57 | 46 | 0.7417 | 63.5384 |
| 0.6495 | 0.6 | 48 | 0.7318 | 67.0409 |
| 0.7102 | 0.62 | 50 | 0.7219 | 67.2205 |
| 0.7225 | 0.65 | 52 | 0.7132 | 72.9232 |
| 0.6752 | 0.68 | 54 | 0.7053 | 71.7782 |
| 0.679 | 0.7 | 56 | 0.6978 | 72.0476 |
| 0.6642 | 0.72 | 58 | 0.6906 | 72.8334 |
| 0.7048 | 0.75 | 60 | 0.6836 | 72.5191 |
| 0.6554 | 0.78 | 62 | 0.6773 | 72.4742 |
| 0.7454 | 0.8 | 64 | 0.6714 | 72.5415 |
| 0.6286 | 0.82 | 66 | 0.6663 | 74.7643 |
| 0.7423 | 0.85 | 68 | 0.6620 | 72.9681 |
| 0.8805 | 0.88 | 70 | 0.6584 | 77.0094 |
| 0.5701 | 0.9 | 72 | 0.6554 | 80.0404 |
| 0.5509 | 0.93 | 74 | 0.6531 | 80.0180 |
| 0.7618 | 0.95 | 76 | 0.6514 | 80.3996 |
| 0.6455 | 0.97 | 78 | 0.6503 | 79.8383 |
| 0.6748 | 1.0 | 80 | 0.6499 | 78.4463 |
Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.0.0+cu117
- Datasets 2.15.0
- Tokenizers 0.15.0