Whisper Large V2
This model is a fine-tuned version of openai/whisper-large-v2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6750
- Wer: 28.0120
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: 3e-05
- train_batch_size: 12
- 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: 20
- num_epochs: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.0702 | 0.7895 | 15 | 0.5925 | 27.5691 |
0.0715 | 1.5789 | 30 | 0.6284 | 36.0383 |
0.0686 | 2.3684 | 45 | 0.6231 | 26.2580 |
0.0454 | 3.1579 | 60 | 0.6415 | 25.3721 |
0.0225 | 3.9474 | 75 | 0.6376 | 24.6102 |
0.011 | 4.7368 | 90 | 0.6750 | 28.0120 |
Framework versions
- Transformers 4.44.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Base model
openai/whisper-large-v2