Whisper Tunisien
This model is a fine-tuned version of openai/whisper-small on the Tunisian_dataset_STT-TTS30s_filtred1.0 dataset. It achieves the following results on the evaluation set:
- Loss: 3.7250
- Wer: 103.1746
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: 8
- 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 |
|---|---|---|---|---|
| 0.1045 | 8.4746 | 500 | 3.3315 | 102.7898 |
| 0.0043 | 16.9492 | 1000 | 3.7250 | 103.1746 |
Framework versions
- Transformers 4.42.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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Dataset used to train Arbi-Houssem/TunLangModel_test30s
Evaluation results
- Wer on Tunisian_dataset_STT-TTS30s_filtred1.0self-reported103.175