whisper-small-clean-hi
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: 0.5136
- Wer: 28.2379
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: 48
- eval_batch_size: 24
- 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: 3000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.5251 | 0.46 | 50 | 1.2276 | 88.8034 |
| 0.7311 | 0.92 | 100 | 0.6706 | 50.3372 |
| 0.5582 | 1.38 | 150 | 0.5367 | 43.6798 |
| 0.4555 | 1.83 | 200 | 0.4448 | 43.1783 |
| 0.3326 | 2.29 | 250 | 0.3594 | 36.2182 |
| 0.2394 | 2.75 | 300 | 0.2507 | 33.5380 |
| 0.1449 | 3.21 | 350 | 0.2294 | 32.7252 |
| 0.1407 | 3.67 | 400 | 0.2144 | 30.6070 |
| 0.1048 | 4.13 | 450 | 0.2125 | 29.6299 |
| 0.0854 | 4.59 | 500 | 0.2085 | 29.1371 |
| 0.0762 | 5.05 | 550 | 0.2125 | 28.4109 |
| 0.0445 | 5.5 | 600 | 0.2168 | 28.4973 |
| 0.0474 | 5.96 | 650 | 0.2197 | 28.2725 |
| 0.0249 | 6.42 | 700 | 0.2324 | 28.2898 |
| 0.0267 | 6.88 | 750 | 0.2287 | 27.2696 |
| 0.0144 | 7.34 | 800 | 0.2440 | 27.2869 |
| 0.0154 | 7.8 | 850 | 0.2524 | 27.3733 |
| 0.008 | 8.26 | 900 | 0.2648 | 27.1312 |
| 0.0103 | 8.72 | 950 | 0.2602 | 27.9353 |
| 0.0066 | 9.17 | 1000 | 0.2718 | 28.3330 |
| 0.0073 | 9.63 | 1050 | 0.2705 | 27.4771 |
| 0.0053 | 10.09 | 1100 | 0.2828 | 27.5030 |
| 0.0044 | 10.55 | 1150 | 0.2882 | 27.2004 |
| 0.0045 | 11.01 | 1200 | 0.2892 | 27.5117 |
| 0.0037 | 11.47 | 1250 | 0.2961 | 27.3215 |
| 0.0031 | 11.93 | 1300 | 0.2934 | 27.0534 |
| 0.0022 | 12.39 | 1350 | 0.3014 | 27.1053 |
| 0.003 | 12.84 | 1400 | 0.3077 | 26.5779 |
| 0.0022 | 13.3 | 1450 | 0.3096 | 26.8373 |
| 0.002 | 13.76 | 1500 | 0.3123 | 26.5347 |
| 0.0017 | 14.22 | 1550 | 0.3186 | 26.8632 |
| 0.0016 | 14.68 | 1600 | 0.3255 | 26.6903 |
| 0.0012 | 15.14 | 1650 | 0.3329 | 26.4396 |
| 0.0015 | 15.6 | 1700 | 0.3336 | 27.0188 |
| 0.0009 | 16.06 | 1750 | 0.3361 | 26.4569 |
| 0.001 | 16.51 | 1800 | 0.3483 | 26.4655 |
| 0.0014 | 16.97 | 1850 | 0.3533 | 26.2666 |
| 0.0004 | 17.43 | 1900 | 0.3581 | 26.0678 |
| 0.0004 | 17.89 | 1950 | 0.3688 | 26.5087 |
| 0.0003 | 18.35 | 2000 | 0.3738 | 26.2148 |
| 0.0004 | 18.81 | 2050 | 0.3729 | 26.1197 |
| 0.0005 | 19.27 | 2100 | 0.3850 | 25.8776 |
| 0.0002 | 19.72 | 2150 | 0.3874 | 25.9900 |
| 0.0004 | 20.18 | 2200 | 0.3927 | 25.9727 |
| 0.0 | 20.64 | 2250 | 0.4037 | 25.9381 |
| 0.0 | 21.1 | 2300 | 0.4133 | 25.9208 |
| 0.0001 | 21.56 | 2350 | 0.4188 | 25.5836 |
| 0.0 | 22.02 | 2400 | 0.4266 | 25.8776 |
| 0.0 | 22.48 | 2450 | 0.4380 | 26.1715 |
| 0.0 | 22.94 | 2500 | 0.4473 | 25.6268 |
| 0.0 | 23.39 | 2550 | 0.4604 | 26.0418 |
| 0.0 | 23.85 | 2600 | 0.4681 | 26.1802 |
| 0.0 | 24.31 | 2650 | 0.4833 | 26.1197 |
| 0.0 | 24.77 | 2700 | 0.4883 | 26.2234 |
| 0.0 | 25.23 | 2750 | 0.4993 | 26.4914 |
| 0.0 | 25.69 | 2800 | 0.5031 | 26.7768 |
| 0.0 | 26.15 | 2850 | 0.5077 | 26.6211 |
| 0.0 | 26.61 | 2900 | 0.5102 | 27.1658 |
| 0.0 | 27.06 | 2950 | 0.5123 | 28.1688 |
| 0.0 | 27.52 | 3000 | 0.5136 | 28.2379 |
Framework versions
- Transformers 4.37.0.dev0
- Pytorch 1.12.1
- Datasets 2.16.1
- Tokenizers 0.15.0