whisper-small-enhanced-hindi
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: 2.3627
- Wer: 95.1323
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 |
|---|---|---|---|---|
| 3.0111 | 0.61 | 50 | 2.6830 | 173.1800 |
| 2.1003 | 1.22 | 100 | 2.0362 | 114.2054 |
| 1.884 | 1.83 | 150 | 1.8518 | 196.2390 |
| 1.7085 | 2.44 | 200 | 1.7161 | 104.2625 |
| 1.5726 | 3.05 | 250 | 1.5840 | 99.8011 |
| 1.3908 | 3.66 | 300 | 1.4421 | 98.4524 |
| 1.2463 | 4.27 | 350 | 1.3700 | 95.3484 |
| 1.2047 | 4.88 | 400 | 1.3240 | 97.6050 |
| 1.069 | 5.49 | 450 | 1.2952 | 96.8442 |
| 1.0265 | 6.1 | 500 | 1.2916 | 95.0026 |
| 0.9474 | 6.71 | 550 | 1.2525 | 94.6222 |
| 0.8052 | 7.32 | 600 | 1.2687 | 94.3109 |
| 0.7971 | 7.93 | 650 | 1.2595 | 92.5990 |
| 0.6551 | 8.54 | 700 | 1.2944 | 93.0140 |
| 0.6156 | 9.15 | 750 | 1.3545 | 93.7749 |
| 0.5445 | 9.76 | 800 | 1.3548 | 93.5328 |
| 0.4183 | 10.37 | 850 | 1.4263 | 93.6798 |
| 0.4311 | 10.98 | 900 | 1.4321 | 94.1726 |
| 0.3244 | 11.59 | 950 | 1.4985 | 94.0169 |
| 0.2604 | 12.2 | 1000 | 1.6052 | 93.9997 |
| 0.2403 | 12.8 | 1050 | 1.6366 | 94.4665 |
| 0.1669 | 13.41 | 1100 | 1.7287 | 94.4752 |
| 0.1648 | 14.02 | 1150 | 1.7606 | 96.0661 |
| 0.1184 | 14.63 | 1200 | 1.8454 | 94.9507 |
| 0.086 | 15.24 | 1250 | 1.9234 | 94.8037 |
| 0.0845 | 15.85 | 1300 | 1.9631 | 94.7000 |
| 0.0504 | 16.46 | 1350 | 2.0461 | 94.1121 |
| 0.0525 | 17.07 | 1400 | 2.1092 | 93.9478 |
| 0.0381 | 17.68 | 1450 | 2.1563 | 95.0718 |
| 0.0261 | 18.29 | 1500 | 2.2302 | 94.3109 |
| 0.0282 | 18.9 | 1550 | 2.2574 | 94.0775 |
| 0.0209 | 19.51 | 1600 | 2.2939 | 94.7432 |
| 0.0187 | 20.12 | 1650 | 2.3627 | 95.1323 |
Framework versions
- Transformers 4.37.0.dev0
- Pytorch 1.12.1
- Datasets 2.16.1
- Tokenizers 0.15.0