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whisper-small-tunisian-arabic
awaxsama/whisper-small-tunisian-arabic
whisper-small-tunisian-arabic is a automatic speech recognition model from awaxsama. Use it when you need speech turned into text. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Automatic Speech Recognition
- Library
- transformers
- License
- apache-2.0
- Model type
- whisper
- Access
- Public
- Created
- Aug 4, 2026
- Updated
- Aug 6, 2026
- SHA
- 102843a0
Base models
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Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
whisper-small-tunisian-arabic
This model is a fine-tuned version of openai/whisper-small on the linagora/linto-dataset-audio-ar-tn-augmented dataset. It achieves the following results on the evaluation set:
- Loss: 0.0041
- Wer: 0.0019
- Normalized Wer: 0.0019
- Normalized Cer: 0.0012
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
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 3.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Normalized Cer | Normalized Wer | Wer |
|---|---|---|---|---|---|---|
| 2.652 | 0.2705 | 500 | 0.5770 | 0.2520 | 0.4847 | 0.4879 |
| 1.6215 | 0.5411 | 1000 | 0.3265 | 0.1384 | 0.2841 | 0.2847 |
| 1.056 | 0.8116 | 1500 | 0.1732 | 0.0920 | 0.1790 | 0.1815 |
| 0.4798 | 1.0817 | 2000 | 0.0955 | 0.0476 | 0.1032 | 0.1064 |
| 0.2969 | 1.3522 | 2500 | 0.0571 | 0.0259 | 0.0586 | 0.0592 |
| 0.187 | 1.6228 | 3000 | 0.0334 | 0.0117 | 0.0280 | 0.0287 |
| 0.1178 | 1.8933 | 3500 | 0.0178 | 0.0053 | 0.0115 | 0.0115 |
| 0.0494 | 2.1634 | 4000 | 0.0101 | 0.0029 | 0.0045 | 0.0045 |
| 0.0381 | 2.4350 | 4500 | 0.0059 | 0.0019 | 0.0019 | 0.0012 |
| 0.0296 | 2.7055 | 5000 | 0.0049 | 0.0025 | 0.0025 | 0.0013 |
| 0.0246 | 2.9761 | 5500 | 0.0041 | 0.0019 | 0.0019 | 0.0012 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.4
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- whisper
- License
- apache-2.0
- Created
- Aug 4, 2026
- Updated
- Aug 6, 2026