Whisper Small EN - erenozaltun-common1
This model is a fine-tuned version of openai/whisper-small on the Common Voice 1.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3868
- Wer: 21.9771
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: 2000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1749 | 0.6588 | 500 | 0.3715 | 21.4957 |
| 0.0885 | 1.3175 | 1000 | 0.3665 | 21.5340 |
| 0.0905 | 1.9763 | 1500 | 0.3668 | 21.8322 |
| 0.0387 | 2.6350 | 2000 | 0.3868 | 21.9771 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.1.2+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1
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Base model
openai/whisper-small