Whisper Small Hi - Sanchit Gandhi
This model is a fine-tuned version of openai/whisper-small on the Common Voice alpha dataset. It achieves the following results on the evaluation set:
- Loss: 0.5294
- Wer: 17.4180
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: 360
- training_steps: 3600
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.061 | 2.0417 | 600 | 0.3876 | 16.0348 |
| 0.007 | 5.0208 | 1200 | 0.4369 | 16.2398 |
| 0.0012 | 7.0625 | 1800 | 0.4970 | 17.6742 |
| 0.0007 | 10.0417 | 2400 | 0.5139 | 17.5717 |
| 0.0005 | 13.0208 | 3000 | 0.5253 | 17.3668 |
| 0.0005 | 15.0625 | 3600 | 0.5294 | 17.4180 |
Framework versions
- Transformers 4.51.0
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1
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Model tree for xbilek25/whisper-small-cv_train-3600
Base model
openai/whisper-smallEvaluation results
- Wer on Common Voice alphavalidation set self-reported17.418