whisper-medium-en-cv-6.1
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: 1.1564
- Wer: 35.3644
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: 3e-05
- 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: 210
- training_steps: 2100
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| No log | 0 | 0 | 2.4185 | 46.5401 |
| 0.8149 | 0.1429 | 300 | 1.0591 | 38.1506 |
| 0.2115 | 1.1429 | 600 | 1.0779 | 40.8757 |
| 0.0598 | 2.1429 | 900 | 1.1087 | 36.4666 |
| 0.0216 | 3.1429 | 1200 | 1.1280 | 35.9155 |
| 0.0089 | 4.1429 | 1500 | 1.1617 | 35.1806 |
| 0.0024 | 5.1429 | 1800 | 1.1517 | 34.9357 |
| 0.0012 | 6.1429 | 2100 | 1.1564 | 35.3644 |
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-6.1
Base model
openai/whisper-medium.enDataset used to train xbilek25/whisper-medium-en-cv-6.1
Evaluation results
- Wer on Common Voice 17.0self-reported35.364