---
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: 53.55042318175298
---

<!-- 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: 0.9262
- Wer: 53.5504

## 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: 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     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 1.0933        | 4.5045  | 500  | 1.1956          | 61.0242 |
| 0.7416        | 9.0090  | 1000 | 0.9971          | 56.0895 |
| 0.5403        | 13.5135 | 1500 | 0.9140          | 53.4644 |
| 0.4315        | 18.0180 | 2000 | 0.8778          | 53.3783 |
| 0.2836        | 22.5225 | 2500 | 0.8948          | 53.0627 |
| 0.2513        | 27.0270 | 3000 | 0.9099          | 53.5074 |
| 0.2196        | 31.5315 | 3500 | 0.9215          | 53.6365 |
| 0.2199        | 36.0360 | 4000 | 0.9262          | 53.5504 |


### Framework versions

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