whisper-small-noisy-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: 1.6842
- Wer: 76.4655
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 |
|---|---|---|---|---|
| 2.5492 | 0.61 | 50 | 2.2588 | 122.9379 |
| 1.6655 | 1.22 | 100 | 1.6099 | 92.4434 |
| 1.4463 | 1.83 | 150 | 1.4333 | 89.4086 |
| 1.2723 | 2.44 | 200 | 1.3012 | 90.1954 |
| 1.1433 | 3.05 | 250 | 1.1803 | 84.7052 |
| 0.9489 | 3.66 | 300 | 1.0427 | 82.0768 |
| 0.8082 | 4.27 | 350 | 0.9796 | 81.3246 |
| 0.7696 | 4.88 | 400 | 0.9372 | 78.6962 |
| 0.631 | 5.49 | 450 | 0.9229 | 78.2898 |
| 0.5784 | 6.1 | 500 | 0.9306 | 76.3790 |
| 0.5112 | 6.71 | 550 | 0.9158 | 76.3963 |
| 0.3738 | 7.32 | 600 | 0.9585 | 75.7652 |
| 0.3762 | 7.93 | 650 | 0.9530 | 75.5490 |
| 0.2647 | 8.54 | 700 | 1.0094 | 76.1975 |
| 0.2282 | 9.15 | 750 | 1.0548 | 76.8632 |
| 0.1865 | 9.76 | 800 | 1.0789 | 76.4482 |
| 0.1172 | 10.37 | 850 | 1.1491 | 78.1688 |
| 0.1181 | 10.98 | 900 | 1.1769 | 76.5520 |
| 0.0778 | 11.59 | 950 | 1.2255 | 77.5117 |
| 0.0579 | 12.2 | 1000 | 1.3021 | 76.0246 |
| 0.0515 | 12.8 | 1050 | 1.3064 | 76.8546 |
| 0.0324 | 13.41 | 1100 | 1.3766 | 77.1140 |
| 0.0317 | 14.02 | 1150 | 1.4044 | 78.2206 |
| 0.0227 | 14.63 | 1200 | 1.4420 | 77.9353 |
| 0.0174 | 15.24 | 1250 | 1.4780 | 76.4482 |
| 0.0164 | 15.85 | 1300 | 1.5044 | 76.2494 |
| 0.0121 | 16.46 | 1350 | 1.5338 | 76.7595 |
| 0.0128 | 17.07 | 1400 | 1.5588 | 76.9410 |
| 0.0108 | 17.68 | 1450 | 1.5688 | 76.4482 |
| 0.0085 | 18.29 | 1500 | 1.6060 | 76.6903 |
| 0.0082 | 18.9 | 1550 | 1.6368 | 76.5606 |
| 0.0065 | 19.51 | 1600 | 1.6483 | 76.5520 |
| 0.0062 | 20.12 | 1650 | 1.6842 | 76.4655 |
Framework versions
- Transformers 4.37.0.dev0
- Pytorch 1.12.1
- Datasets 2.16.1
- Tokenizers 0.15.0