---
language:
- ar
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- Arbi-Houssem/datasetSTT-TTS
metrics:
- wer
model-index:
- name: Whisper Tunisien
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: datasetSTT-TTS
      type: Arbi-Houssem/datasetSTT-TTS
      args: 'config: ar, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 69.09469302809573
---

<!-- 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 datasetSTT-TTS dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1002
- Wer: 69.0947

## 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
- 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: 7000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 1.2207        | 62.5  | 500  | 2.2689          | 90.9469 |
| 0.8267        | 125.0 | 1000 | 2.0114          | 80.4370 |
| 0.6297        | 187.5 | 1500 | 1.9396          | 73.5692 |
| 0.5283        | 250.0 | 2000 | 1.9364          | 70.5515 |
| 0.4231        | 312.5 | 2500 | 1.9509          | 70.4475 |
| 0.3683        | 375.0 | 3000 | 1.9729          | 74.2976 |
| 0.319         | 437.5 | 3500 | 1.9950          | 73.2570 |
| 0.2884        | 500.0 | 4000 | 2.0182          | 72.6327 |
| 0.259         | 562.5 | 4500 | 2.0410          | 72.5286 |
| 0.2364        | 625.0 | 5000 | 2.0619          | 69.0947 |
| 0.2181        | 687.5 | 5500 | 2.0780          | 69.0947 |
| 0.2133        | 750.0 | 6000 | 2.0901          | 68.8866 |
| 0.201         | 812.5 | 6500 | 2.0979          | 68.8866 |
| 0.2033        | 875.0 | 7000 | 2.1002          | 69.0947 |


### Framework versions

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