---
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: 44.46994692296657
---

<!-- 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: 1.1841
- Wer: 44.4699

## 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
- 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     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 0.3626        | 4.5045  | 500  | 0.8379          | 53.0340 |
| 0.0527        | 9.0090  | 1000 | 0.9350          | 48.5440 |
| 0.0111        | 13.5135 | 1500 | 1.0400          | 49.4907 |
| 0.0049        | 18.0180 | 2000 | 1.1030          | 44.6564 |
| 0.0017        | 22.5225 | 2500 | 1.1338          | 44.7568 |
| 0.0014        | 27.0270 | 3000 | 1.1618          | 44.8142 |
| 0.0009        | 31.5315 | 3500 | 1.1784          | 44.8429 |
| 0.0009        | 36.0360 | 4000 | 1.1841          | 44.4699 |


### Framework versions

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