chrisd108/whisper-small-smith-and-brock
04
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Whisper Small Smith & Brock
This model is a fine-tuned version of openai/whisper-small on the Whisper Smith & Brock dataset. It achieves the following results on the evaluation set:
- Loss: 0.0000
- Wer: 98.0392
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
- trainbatchsize: 16
- evalbatchsize: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lrschedulertype: linear
- lrschedulerwarmup_steps: 500
- training_steps: 4000
- mixedprecisiontraining: Native AMP
Training results
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1