---
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: 104.92910195813639
---

<!-- 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: 2.9037
- Wer: 104.9291

## 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: 15000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch    | Step  | Validation Loss | Wer      |
|:-------------:|:--------:|:-----:|:---------------:|:--------:|
| 1.2369        | 7.7519   | 1000  | 3.2094          | 117.6907 |
| 1.0283        | 15.5039  | 2000  | 3.0674          | 110.6685 |
| 0.9629        | 23.2558  | 3000  | 3.0180          | 130.3174 |
| 0.893         | 31.0078  | 4000  | 2.9887          | 126.7387 |
| 0.835         | 38.7597  | 5000  | 2.9676          | 103.5111 |
| 0.7907        | 46.5116  | 6000  | 2.9500          | 107.2248 |
| 0.7624        | 54.2636  | 7000  | 2.9370          | 107.5625 |
| 0.7624        | 62.0155  | 8000  | 2.9270          | 104.4564 |
| 0.7198        | 69.7674  | 9000  | 2.9200          | 104.3889 |
| 0.6818        | 77.5194  | 10000 | 2.9143          | 111.6138 |
| 0.7245        | 85.2713  | 11000 | 2.9099          | 104.5240 |
| 0.6762        | 93.0233  | 12000 | 2.9071          | 104.5915 |
| 0.6691        | 100.7752 | 13000 | 2.9052          | 104.8616 |
| 0.6366        | 108.5271 | 14000 | 2.9040          | 104.2539 |
| 0.6801        | 116.2791 | 15000 | 2.9037          | 104.9291 |


### Framework versions

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