Whisper Small Mr - Amit Rai
This model is a fine-tuned version of openai/whisper-small on the Common Voice mr 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.4063
- Wer: 47.5340
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: 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
- training_steps: 2000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0469 | 3.5587 | 1000 | 0.3397 | 48.4430 |
| 0.0027 | 7.1174 | 2000 | 0.4063 | 47.5340 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.5.1+cu124
- Datasets 3.5.0
- Tokenizers 0.21.0
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Model tree for Amit65/whisper-small-hi-V2.1
Base model
openai/whisper-smallEvaluation results
- Wer on Common Voice mr 11.0self-reported47.534