Whisper Large v2 TR
This model is a fine-tuned version of openai/whisper-large-v2 on the Common Voice 17 dataset. It achieves the following results on the evaluation set:
- Loss: 0.1533
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: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.0 | 328 | 0.1528 |
| 0.3309 | 2.0 | 656 | 0.1451 |
| 0.3309 | 3.0 | 984 | 0.1533 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for tgrhn/whisper-large-v2-tr-cv13-2
Base model
openai/whisper-large-v2