openai/whisper-large-v3
This model is a fine-tuned version of openai/whisper-large-v3 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1283
- Wer: 0.0789
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: 62
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- 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 |
|---|---|---|---|---|
| 0.0138 | 2.24 | 1000 | 0.0962 | 0.0863 |
| 0.004 | 4.48 | 2000 | 0.1117 | 0.0844 |
| 0.0015 | 6.73 | 3000 | 0.1178 | 0.0807 |
| 0.0004 | 8.97 | 4000 | 0.1219 | 0.0792 |
| 0.0002 | 11.21 | 5000 | 0.1283 | 0.0789 |
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.0.0+cu117
- Datasets 2.14.6
- Tokenizers 0.14.1
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Base model
openai/whisper-large-v3