openai/whisper-small
This model is a fine-tuned version of openai/whisper-small on the common_voice_17_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.1845
- Wer: 11.8381
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: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- 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 |
|---|---|---|---|---|
| 0.2458 | 1.0296 | 1000 | 0.2480 | 18.0723 |
| 0.1099 | 2.0592 | 2000 | 0.1976 | 13.6355 |
| 0.0403 | 3.0888 | 3000 | 0.2002 | 12.7249 |
| 0.0211 | 4.1184 | 4000 | 0.2101 | 12.4327 |
| 0.0609 | 5.148 | 5000 | 0.1845 | 11.8381 |
Framework versions
- Transformers 4.46.0.dev0
- Pytorch 2.4.1+cu121
- Datasets 3.0.2.dev0
- Tokenizers 0.20.0
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openai/whisper-small