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---
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: 102.70087778528021
---
<!-- 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: 6.8348
- Wer: 102.7009
## 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: 0.0005
- 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: 3000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 1.1414 | 3.8760 | 500 | 4.1822 | 181.0263 |
| 0.4667 | 7.7519 | 1000 | 5.0049 | 108.1702 |
| 0.1821 | 11.6279 | 1500 | 5.5927 | 102.7684 |
| 0.068 | 15.5039 | 2000 | 6.2194 | 106.2120 |
| 0.011 | 19.3798 | 2500 | 6.3815 | 103.0385 |
| 0.0003 | 23.2558 | 3000 | 6.8348 | 102.7009 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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