---
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: 62.702625161382876
---

<!-- 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: 1.2386
- Wer: 62.7026

## 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: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 1.7779        | 4.5045  | 500  | 1.7860          | 89.0690 |
| 1.3825        | 9.0090  | 1000 | 1.4590          | 75.6419 |
| 1.2777        | 13.5135 | 1500 | 1.3650          | 72.4573 |
| 1.255         | 18.0180 | 2000 | 1.3039          | 68.0247 |
| 1.1248        | 22.5225 | 2500 | 1.2712          | 65.4139 |
| 1.0907        | 27.0270 | 3000 | 1.2522          | 62.5448 |
| 1.0969        | 31.5315 | 3500 | 1.2418          | 62.2579 |
| 1.111         | 36.0360 | 4000 | 1.2386          | 62.7026 |


### Framework versions

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