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arab
This model is a fine-tuned version of openai/whisper-large-v2 on the common_voice_16_1 dataset. It achieves the following results on the evaluation set:
- Loss: 0.4437
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: 0.001
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 25
- training_steps: 50
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 0.0267 | 10 | 0.4333 |
| No log | 0.0533 | 20 | 0.4281 |
| 0.141 | 0.08 | 30 | 0.4360 |
| 0.141 | 0.1067 | 40 | 0.4509 |
| 0.1724 | 0.1333 | 50 | 0.4437 |
Framework versions
- PEFT 0.11.2.dev0
- Transformers 4.42.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
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Base model
openai/whisper-large-v2