Whisper Medium Tr Can
This model is a fine-tuned version of openai/whisper-medium on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.1694
- Wer: 14.5329
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: 8
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 250
- training_steps: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1912 | 0.3448 | 1000 | 0.2200 | 18.9662 |
| 0.1469 | 0.6895 | 2000 | 0.1978 | 16.9565 |
| 0.0666 | 1.0343 | 3000 | 0.1821 | 15.6791 |
| 0.0571 | 1.3791 | 4000 | 0.1778 | 15.0915 |
| 0.0502 | 1.7238 | 5000 | 0.1694 | 14.5329 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Base model
openai/whisper-medium