whisper-small-enhanced-hindi-10dB
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: 1.5528
- Wer: 57.6431
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: 64
- 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: 3000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 2.3087 | 0.61 | 50 | 1.9565 | 101.3315 |
| 1.3628 | 1.22 | 100 | 1.2862 | 83.4083 |
| 1.1319 | 1.83 | 150 | 1.0950 | 79.0334 |
| 0.9559 | 2.44 | 200 | 0.9573 | 74.3905 |
| 0.807 | 3.05 | 250 | 0.8252 | 71.1655 |
| 0.6268 | 3.66 | 300 | 0.6903 | 67.2488 |
| 0.5039 | 4.27 | 350 | 0.6466 | 64.4907 |
| 0.4738 | 4.88 | 400 | 0.6077 | 62.8566 |
| 0.3599 | 5.49 | 450 | 0.5964 | 60.7902 |
| 0.3225 | 6.1 | 500 | 0.6001 | 59.4761 |
| 0.2599 | 6.71 | 550 | 0.5930 | 58.5509 |
| 0.1658 | 7.32 | 600 | 0.6158 | 58.4731 |
| 0.1666 | 7.93 | 650 | 0.6172 | 58.0581 |
| 0.1032 | 8.54 | 700 | 0.6521 | 58.7152 |
| 0.081 | 9.15 | 750 | 0.6857 | 58.7930 |
| 0.0606 | 9.76 | 800 | 0.7020 | 57.9457 |
| 0.0345 | 10.37 | 850 | 0.7422 | 57.9284 |
| 0.0342 | 10.98 | 900 | 0.7622 | 57.5826 |
| 0.023 | 11.59 | 950 | 0.7787 | 57.8074 |
| 0.017 | 12.2 | 1000 | 0.8223 | 58.4299 |
| 0.0159 | 12.8 | 1050 | 0.8384 | 57.6604 |
| 0.0101 | 13.41 | 1100 | 0.8538 | 58.3607 |
| 0.012 | 14.02 | 1150 | 0.8634 | 57.8765 |
| 0.0092 | 14.63 | 1200 | 0.8762 | 57.5134 |
| 0.0077 | 15.24 | 1250 | 0.9077 | 58.6201 |
| 0.007 | 15.85 | 1300 | 0.9194 | 58.2310 |
| 0.006 | 16.46 | 1350 | 0.9194 | 57.1935 |
| 0.0051 | 17.07 | 1400 | 0.9427 | 57.4788 |
| 0.0044 | 17.68 | 1450 | 0.9613 | 57.5307 |
| 0.0037 | 18.29 | 1500 | 0.9750 | 57.3578 |
| 0.0038 | 18.9 | 1550 | 0.9620 | 57.1070 |
| 0.0037 | 19.51 | 1600 | 0.9793 | 57.2021 |
| 0.0028 | 20.12 | 1650 | 1.0002 | 57.6690 |
| 0.0023 | 20.73 | 1700 | 1.0171 | 57.0465 |
| 0.0023 | 21.34 | 1750 | 1.0344 | 56.4499 |
| 0.0024 | 21.95 | 1800 | 1.0231 | 56.9168 |
| 0.0017 | 22.56 | 1850 | 1.0420 | 56.6229 |
| 0.0016 | 23.17 | 1900 | 1.0599 | 57.6690 |
| 0.001 | 23.78 | 1950 | 1.0659 | 57.7641 |
| 0.0012 | 24.39 | 2000 | 1.0818 | 56.7093 |
| 0.001 | 25.0 | 2050 | 1.0874 | 57.0984 |
| 0.0008 | 25.61 | 2100 | 1.1034 | 57.5220 |
| 0.0006 | 26.22 | 2150 | 1.1275 | 56.7353 |
| 0.0004 | 26.83 | 2200 | 1.1528 | 57.1330 |
| 0.0002 | 27.44 | 2250 | 1.1668 | 56.5537 |
| 0.0001 | 28.05 | 2300 | 1.1935 | 56.6142 |
| 0.0001 | 28.66 | 2350 | 1.2282 | 56.3289 |
| 0.0001 | 29.27 | 2400 | 1.2547 | 56.7266 |
| 0.0001 | 29.88 | 2450 | 1.2814 | 56.4413 |
| 0.0001 | 30.49 | 2500 | 1.3142 | 56.8822 |
| 0.0 | 31.1 | 2550 | 1.3535 | 56.8995 |
| 0.0 | 31.71 | 2600 | 1.3759 | 57.0033 |
| 0.0 | 32.32 | 2650 | 1.4102 | 57.2454 |
| 0.0 | 32.93 | 2700 | 1.4299 | 56.8044 |
| 0.0 | 33.54 | 2750 | 1.4650 | 57.2886 |
| 0.0 | 34.15 | 2800 | 1.4906 | 57.3405 |
| 0.0 | 34.76 | 2850 | 1.5145 | 57.5739 |
| 0.0 | 35.37 | 2900 | 1.5377 | 57.5480 |
| 0.0 | 35.98 | 2950 | 1.5461 | 57.5480 |
| 0.0 | 36.59 | 3000 | 1.5528 | 57.6431 |
Framework versions
- Transformers 4.37.0.dev0
- Pytorch 1.12.1
- Datasets 2.16.1
- Tokenizers 0.15.0