whisper-medium-en-cv-4.9
This model is a fine-tuned version of openai/whisper-medium.en on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3508
- Wer: 11.3793
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: 6e-06
- train_batch_size: 48
- eval_batch_size: 4
- 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: 150
- training_steps: 1500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| No log | 0 | 0 | 1.5197 | 12.4138 |
| 0.2355 | 0.2 | 300 | 0.3713 | 11.3793 |
| 0.3136 | 0.4 | 600 | 0.3537 | 11.2069 |
| 0.1076 | 1.1 | 900 | 0.3551 | 11.8103 |
| 0.1079 | 1.3 | 1200 | 0.3570 | 11.3793 |
| 0.1715 | 1.5 | 1500 | 0.3508 | 11.3793 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.1
- Tokenizers 0.21.1
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Model tree for xbilek25/whisper-medium-en-cv-4.9
Base model
openai/whisper-medium.enDataset used to train xbilek25/whisper-medium-en-cv-4.9
Evaluation results
- Wer on Common Voice 17.0test set self-reported11.379