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whisper-large-odiya
This model is a fine-tuned version of openai/whisper-large-v2 on the Common Voice 13 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2808
- Wer Ortho: 45.8771
- Wer: 18.4527
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: 16
- 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: 1000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 0.0019 | 9.71 | 500 | 0.2362 | 45.4898 | 19.3002 |
| 0.0001 | 19.42 | 1000 | 0.2808 | 45.8771 | 18.4527 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
