Whisper Large V3 Vi - Prateek Jain
This model is a fine-tuned version of openai/whisper-large-v3 on the google/fleurs dataset. It achieves the following results on the evaluation set:
- Loss: 0.2355
- Wer: 218.8330
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: 250
- training_steps: 1500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0148 | 2.66 | 500 | 0.2193 | 80.1012 |
| 0.0014 | 5.32 | 1000 | 0.2275 | 247.5556 |
| 0.0004 | 7.98 | 1500 | 0.2355 | 218.8330 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1
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