Whisper Tiny British English
This model is a fine-tuned version of openai/whisper-tiny on the British English dataset. It achieves the following results on the evaluation set:
- Loss: 0.2951
- Wer: 13.4421
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: 2
- eval_batch_size: 1
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 2000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.3268 | 0.9901 | 1000 | 0.3012 | 15.0463 |
| 0.1728 | 1.9802 | 2000 | 0.2951 | 13.4421 |
Framework versions
- Transformers 5.23.0.dev0
- Pytorch 2.11.0+cu130
- Datasets 5.1.0
- Tokenizers 0.23.3
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Model tree for AntonisAgp/whisper-tiny-british
Base model
openai/whisper-tinyDataset used to train AntonisAgp/whisper-tiny-british
Evaluation results
- Wer on British Englishself-reported13.442