Whisper Small sw - Arindam Bose
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: 0.4499
- Wer: 28.8790
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: 8000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.4791 | 0.4342 | 1000 | 0.5847 | 37.9256 |
| 0.396 | 0.8684 | 2000 | 0.4834 | 31.9206 |
| 0.2344 | 1.3026 | 3000 | 0.4631 | 31.2366 |
| 0.2237 | 1.7369 | 4000 | 0.4402 | 29.6515 |
| 0.1096 | 2.1711 | 5000 | 0.4468 | 29.0480 |
| 0.1219 | 2.6053 | 6000 | 0.4431 | 28.6169 |
| 0.0743 | 3.0395 | 7000 | 0.4428 | 28.3318 |
| 0.0691 | 3.4737 | 8000 | 0.4499 | 28.8790 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1
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Base model
openai/whisper-small