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Whisper Small Odia 10k steps
This model is a fine-tuned version of openai/whisper-small on the Ranjit/or_in_dataset dataset. It achieves the following results on the evaluation set:
- Loss: 0.2806
- Wer: 19.7720
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-06
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- training_steps: 10000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0384 | 0.49 | 1000 | 0.1349 | 40.3740 |
| 0.0175 | 0.98 | 2000 | 0.1601 | 22.6468 |
| 0.0091 | 1.46 | 3000 | 0.1817 | 23.1515 |
| 0.0082 | 1.95 | 4000 | 0.2125 | 23.9139 |
| 0.0048 | 2.44 | 5000 | 0.2110 | 20.2522 |
| 0.0037 | 2.93 | 6000 | 0.2270 | 21.4855 |
| 0.0017 | 3.42 | 7000 | 0.2534 | 20.2399 |
| 0.0018 | 3.9 | 8000 | 0.2706 | 20.7277 |
| 0.0005 | 4.39 | 9000 | 0.2806 | 19.7720 |
| 0.0006 | 4.88 | 10000 | 0.2929 | 20.9747 |
<!-- ### Framework versions
- Transformers 4.28.0.dev0
- Pytorch 1.11.0+cu113
- Datasets 2.10.1
- Tokenizers 0.13.2 -->
