---
language:
- ar
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- Arbi-Houssem/Tunisian_dataset_STT-TTS1
metrics:
- wer
model-index:
- name: Whisper Tunisien
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Tunisian_dataset_STT-TTS1
      type: Arbi-Houssem/Tunisian_dataset_STT-TTS1
      args: 'config: ar, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 99.41634241245137
---

<!-- 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 Tunisien

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Tunisian_dataset_STT-TTS1 dataset.
It achieves the following results on the evaluation set:
- Loss: 2.9262
- Wer: 99.4163

## 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-06
- train_batch_size: 8
- 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: 500
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer      |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 0.565         | 10.3093 | 1000 | 2.7181          | 99.5460  |
| 0.2875        | 20.6186 | 2000 | 2.7486          | 106.3554 |
| 0.1701        | 30.9278 | 3000 | 2.8744          | 103.2425 |
| 0.1375        | 41.2371 | 4000 | 2.9262          | 99.4163  |


### Framework versions

- Transformers 4.42.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1