whisper-large-marathi
This model is a fine-tuned version of openai/whisper-large on the Common Voice 17 dataset. It achieves the following results on the evaluation set:
- Loss: 0.1845
- Wer Ortho: 32.4713
- Wer: 11.9958
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: 12
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 20
- training_steps: 500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 0.1771 | 1.0 | 250 | 0.2041 | 36.0371 | 13.7851 |
| 0.0806 | 2.0 | 500 | 0.1845 | 32.4713 | 11.9958 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1