Whisper Medium Hi - Amarjeet
This model is a fine-tuned version of openai/whisper-medium on the Common Voice 13.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3223
- Wer: 23.4875
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 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: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0546 | 2.3641 | 1000 | 0.2291 | 26.3406 |
| 0.0124 | 4.7281 | 2000 | 0.2662 | 24.4275 |
| 0.0007 | 7.0922 | 3000 | 0.3053 | 23.8147 |
| 0.0001 | 9.4563 | 4000 | 0.3223 | 23.4875 |
Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.21.0