---
language:
- ar
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- Arbi-Houssem/Tunisian_dataset_STT-TTS15s_filtred1.0_Mixed
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_Mixed
      type: Arbi-Houssem/Tunisian_dataset_STT-TTS15s_filtred1.0_Mixed
      args: 'config: ar, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 90.7904174436953
---

<!-- 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_Mixed dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8540
- Wer: 90.7904

## 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-08
- 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: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer      |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 2.2076        | 4.5045  | 500  | 2.1992          | 120.4131 |
| 2.0416        | 9.0090  | 1000 | 2.0813          | 117.6732 |
| 1.9182        | 13.5135 | 1500 | 1.9770          | 119.2368 |
| 1.9273        | 18.0180 | 2000 | 1.9219          | 104.0023 |
| 1.8201        | 22.5225 | 2500 | 1.8901          | 94.8931  |
| 1.7708        | 27.0270 | 3000 | 1.8667          | 92.9709  |
| 1.7865        | 31.5315 | 3500 | 1.8565          | 90.8908  |
| 1.805         | 36.0360 | 4000 | 1.8540          | 90.7904  |


### Framework versions

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