Whisper Tunisien
This model is a fine-tuned version of openai/whisper-medium on the comondov dataset. It achieves the following results on the evaluation set:
- Loss: 1.7085
- Wer: 62.7119
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: 500
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1296 | 50.0 | 200 | 1.5371 | 63.0200 |
| 0.0012 | 100.0 | 400 | 1.6181 | 61.4792 |
| 0.0005 | 150.0 | 600 | 1.6781 | 63.3282 |
| 0.0004 | 200.0 | 800 | 1.7005 | 61.9414 |
| 0.0003 | 250.0 | 1000 | 1.7085 | 62.7119 |
Framework versions
- Transformers 4.41.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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