Whisper Small 200 Sep 6 speedy es - Jessica Martinez
This model is a fine-tuned version of openai/whisper-small on the procesar-videos2024rdm200speedy dataset. It achieves the following results on the evaluation set:
- Loss: 0.5645
- Wer: 24.7788
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: 25
- training_steps: 200
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.3473 | 4.1667 | 50 | 0.5393 | 26.8538 |
| 0.0903 | 8.3333 | 100 | 0.5190 | 29.6308 |
| 0.018 | 12.5 | 150 | 0.5598 | 24.8398 |
| 0.0082 | 16.6667 | 200 | 0.5645 | 24.7788 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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openai/whisper-small