Whisper largev2 amitabha
This model is a fine-tuned version of openai/whisper-large_v2 on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.0000
- Cer: 3.0142
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- 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 | Cer |
|---|---|---|---|---|
| 0.0121 | 9.1743 | 1000 | 0.0062 | 4.9920 |
| 0.0002 | 18.3486 | 2000 | 0.0002 | 3.0260 |
| 0.0 | 27.5229 | 3000 | 0.0001 | 3.0142 |
| 0.0001 | 36.6972 | 4000 | 0.0000 | 3.0142 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
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