Whisper Base De - Krish Kalra
This model is a fine-tuned version of openai/whisper-base on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.4592
- Wer: 24.2481
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: 16
- eval_batch_size: 8
- 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: 5
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.4712 | 1.0 | 283 | 0.4442 | 26.1604 |
| 0.46 | 2.0 | 566 | 0.4376 | 23.1155 |
| 0.1985 | 3.0 | 849 | 0.4449 | 28.6669 |
| 0.1576 | 4.0 | 1132 | 0.4542 | 24.2852 |
| 0.0695 | 5.0 | 1415 | 0.4592 | 24.2481 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3
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Base model
openai/whisper-base