Whisper Tiny Gu - V1
This model is a fine-tuned version of openai/whisper-tiny on the ai4bharat/IndicVoices dataset. It achieves the following results on the evaluation set:
- Loss: 0.2995
- Wer: 58.8371
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: 5e-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: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2832 | 0.9042 | 500 | 0.3072 | 75.1796 |
| 0.1942 | 1.8083 | 1000 | 0.2364 | 67.4873 |
| 0.1301 | 2.7125 | 1500 | 0.2086 | 62.7551 |
| 0.0974 | 3.6166 | 2000 | 0.2098 | 60.8008 |
| 0.0688 | 4.5208 | 2500 | 0.2155 | 60.7146 |
| 0.0412 | 5.4250 | 3000 | 0.2278 | 59.9387 |
| 0.0254 | 6.3291 | 3500 | 0.2493 | 59.2107 |
| 0.0138 | 7.2333 | 4000 | 0.2765 | 58.8658 |
| 0.0061 | 8.1374 | 4500 | 0.2924 | 59.2394 |
| 0.0034 | 9.0416 | 5000 | 0.2995 | 58.8371 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.1
- Tokenizers 0.21.0