---
language:
- ar
license: apache-2.0
base_model: openai/whisper-base
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: 117.69074949358543
---

<!-- 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-base](https://huggingface.co/openai/whisper-base) on the Tunisian_dataset_STT-TTS15s_filtred1.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 4.7577
- Wer: 117.6907

## 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
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- 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      |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 0.5147        | 7.7519  | 500  | 3.1417          | 128.5618 |
| 0.0559        | 15.5039 | 1000 | 3.8111          | 132.5456 |
| 0.01          | 23.2558 | 1500 | 4.2115          | 120.1891 |
| 0.0029        | 31.0078 | 2000 | 4.4628          | 120.3916 |
| 0.0017        | 38.7597 | 2500 | 4.6127          | 111.2086 |
| 0.0011        | 46.5116 | 3000 | 4.6945          | 124.6455 |
| 0.0009        | 54.2636 | 3500 | 4.7426          | 113.3018 |
| 0.0009        | 62.0155 | 4000 | 4.7577          | 117.6907 |


### Framework versions

- Transformers 4.42.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1