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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: 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
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