whisper-small-yue
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: 0.3647
- Wer: 73.2309
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: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 2.9266 | 0.15 | 50 | 2.6136 | 142.9438 |
| 1.0635 | 0.3 | 100 | 0.5730 | 216.4982 |
| 0.373 | 0.45 | 150 | 0.3679 | 319.4501 |
| 0.3004 | 0.6 | 200 | 0.3362 | 170.2386 |
| 0.3078 | 0.76 | 250 | 0.3206 | 118.7626 |
| 0.2687 | 0.91 | 300 | 0.3075 | 93.4897 |
| 0.204 | 1.06 | 350 | 0.3017 | 74.0801 |
| 0.1954 | 1.21 | 400 | 0.3015 | 77.5981 |
| 0.1857 | 1.36 | 450 | 0.2981 | 76.9106 |
| 0.1833 | 1.51 | 500 | 0.3029 | 75.3336 |
| 0.198 | 1.66 | 550 | 0.2972 | 76.8702 |
| 0.1902 | 1.81 | 600 | 0.2883 | 68.8233 |
| 0.196 | 1.96 | 650 | 0.2854 | 68.7829 |
| 0.0732 | 2.11 | 700 | 0.2895 | 69.9151 |
| 0.07 | 2.27 | 750 | 0.2939 | 72.2604 |
| 0.0853 | 2.42 | 800 | 0.3137 | 74.4440 |
| 0.0788 | 2.57 | 850 | 0.3133 | 71.3304 |
| 0.0713 | 2.72 | 900 | 0.2974 | 70.6025 |
| 0.0773 | 2.87 | 950 | 0.2884 | 75.2527 |
| 0.072 | 3.02 | 1000 | 0.2923 | 69.8342 |
| 0.0418 | 3.17 | 1050 | 0.2948 | 73.5544 |
| 0.0318 | 3.32 | 1100 | 0.2965 | 74.2822 |
| 0.0298 | 3.47 | 1150 | 0.3002 | 69.4703 |
| 0.036 | 3.63 | 1200 | 0.3004 | 70.1577 |
| 0.0307 | 3.78 | 1250 | 0.3015 | 74.3631 |
| 0.0403 | 3.93 | 1300 | 0.3000 | 71.4517 |
| 0.0152 | 4.08 | 1350 | 0.3117 | 68.7829 |
| 0.0168 | 4.23 | 1400 | 0.3140 | 71.3708 |
| 0.0136 | 4.38 | 1450 | 0.3225 | 68.1359 |
| 0.0145 | 4.53 | 1500 | 0.3244 | 70.6025 |
| 0.0188 | 4.68 | 1550 | 0.3217 | 72.0178 |
| 0.0202 | 4.83 | 1600 | 0.3087 | 70.8047 |
| 0.0184 | 4.98 | 1650 | 0.3225 | 72.6648 |
| 0.0082 | 5.14 | 1700 | 0.3285 | 70.2386 |
| 0.0066 | 5.29 | 1750 | 0.3288 | 71.0473 |
| 0.0091 | 5.44 | 1800 | 0.3370 | 68.2572 |
| 0.0063 | 5.59 | 1850 | 0.3299 | 71.5730 |
| 0.0093 | 5.74 | 1900 | 0.3311 | 69.3490 |
| 0.0079 | 5.89 | 1950 | 0.3456 | 75.4953 |
| 0.0087 | 6.04 | 2000 | 0.3357 | 77.5576 |
| 0.0052 | 6.19 | 2050 | 0.3364 | 79.6199 |
| 0.005 | 6.34 | 2100 | 0.3376 | 75.1314 |
| 0.0032 | 6.5 | 2150 | 0.3336 | 75.3740 |
| 0.004 | 6.65 | 2200 | 0.3441 | 74.7271 |
| 0.003 | 6.8 | 2250 | 0.3446 | 72.8265 |
| 0.0029 | 6.95 | 2300 | 0.3483 | 70.5216 |
| 0.002 | 7.1 | 2350 | 0.3532 | 74.2822 |
| 0.0014 | 7.25 | 2400 | 0.3469 | 73.5948 |
| 0.0015 | 7.4 | 2450 | 0.3494 | 75.9806 |
| 0.001 | 7.55 | 2500 | 0.3549 | 75.1314 |
| 0.0053 | 7.7 | 2550 | 0.3545 | 73.2309 |
| 0.0025 | 7.85 | 2600 | 0.3563 | 72.7457 |
| 0.001 | 8.01 | 2650 | 0.3562 | 73.5140 |
| 0.001 | 8.16 | 2700 | 0.3594 | 75.1719 |
| 0.0012 | 8.31 | 2750 | 0.3610 | 72.7052 |
| 0.0007 | 8.46 | 2800 | 0.3611 | 72.9478 |
| 0.0016 | 8.61 | 2850 | 0.3629 | 72.8265 |
| 0.0007 | 8.76 | 2900 | 0.3633 | 73.7161 |
| 0.0015 | 8.91 | 2950 | 0.3647 | 73.2309 |
Framework versions
- Transformers 4.37.0.dev0
- Pytorch 1.12.1
- Datasets 2.15.0
- Tokenizers 0.15.0