---
language:
- ar
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- Arbi-Houssem/Tunisian_dataset_STT-TTS15s_filtred1.0
metrics:
- wer
model-index:
- name: Whisper Tunisien
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Tunisian_dataset_STT-TTS15s_filtred1.0
      type: Arbi-Houssem/Tunisian_dataset_STT-TTS15s_filtred1.0
      args: 'config: ar, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 109.99324780553681
---

<!-- 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-TTS15s_filtred1.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 3.0846
- Wer: 109.9932

## 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-07
- 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: 3000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer      |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 1.6852        | 3.8760  | 500  | 3.5237          | 148.8184 |
| 1.2494        | 7.7519  | 1000 | 3.2200          | 121.6070 |
| 1.2202        | 11.6279 | 1500 | 3.1493          | 125.3883 |
| 1.0905        | 15.5039 | 2000 | 3.1099          | 113.9095 |
| 1.0606        | 19.3798 | 2500 | 3.0905          | 110.1958 |
| 1.0858        | 23.2558 | 3000 | 3.0846          | 109.9932 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1