Whisper Small Mar - Harpreet Singh Anand
This model is a fine-tuned version of openai/whisper-small on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.4596
- Wer: 43.3628
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: 16
- eval_batch_size: 8
- 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: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0658 | 4.07 | 1000 | 0.2928 | 46.3542 |
| 0.004 | 8.13 | 2000 | 0.3973 | 44.7295 |
| 0.0004 | 12.2 | 3000 | 0.4406 | 43.5046 |
| 0.0002 | 16.26 | 4000 | 0.4596 | 43.3628 |
Framework versions
- Transformers 4.39.2
- Pytorch 2.1.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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Base model
openai/whisper-small