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: 6.9324
- Wer: 100.4052
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: 2000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.5017 | 100.0 | 300 | 6.1135 | 163.5332 |
| 0.0224 | 200.0 | 600 | 6.5103 | 105.8347 |
| 0.0101 | 300.0 | 900 | 6.8122 | 105.8347 |
| 0.0095 | 400.0 | 1200 | 6.8766 | 100.0 |
| 0.0093 | 500.0 | 1500 | 6.9174 | 100.0 |
| 0.0091 | 600.0 | 1800 | 6.9324 | 100.4052 |
Framework versions
- Transformers 4.41.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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