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Whisper Small Te - Bharat Ramanathan
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: 0.1863
- Wer: 31.6456
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: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1637 | 0.1 | 500 | 0.2092 | 42.9406 |
| 0.1459 | 0.2 | 1000 | 0.2025 | 35.9299 |
| 0.1348 | 0.3 | 1500 | 0.1990 | 35.4917 |
| 0.1309 | 0.4 | 2000 | 0.1974 | 33.7390 |
| 0.1253 | 0.5 | 2500 | 0.1974 | 34.0312 |
| 0.1209 | 0.6 | 3000 | 0.1909 | 32.4732 |
| 0.1139 | 1.05 | 3500 | 0.1899 | 31.7916 |
| 0.1043 | 1.15 | 4000 | 0.1868 | 31.6456 |
| 0.0996 | 1.25 | 4500 | 0.1874 | 31.6943 |
| 0.1002 | 1.35 | 5000 | 0.1863 | 31.6456 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
