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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_Mixed
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_Mixed
type: Arbi-Houssem/Tunisian_dataset_STT-TTS15s_filtred1.0_Mixed
args: 'config: ar, split: test'
metrics:
- name: Wer
type: wer
value: 62.702625161382876
---
<!-- 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_Mixed dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2386
- Wer: 62.7026
## 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: 4000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 1.7779 | 4.5045 | 500 | 1.7860 | 89.0690 |
| 1.3825 | 9.0090 | 1000 | 1.4590 | 75.6419 |
| 1.2777 | 13.5135 | 1500 | 1.3650 | 72.4573 |
| 1.255 | 18.0180 | 2000 | 1.3039 | 68.0247 |
| 1.1248 | 22.5225 | 2500 | 1.2712 | 65.4139 |
| 1.0907 | 27.0270 | 3000 | 1.2522 | 62.5448 |
| 1.0969 | 31.5315 | 3500 | 1.2418 | 62.2579 |
| 1.111 | 36.0360 | 4000 | 1.2386 | 62.7026 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1