metadata
language:
- ar
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- Arbi-Houssem/Tunisian_dataset_STT-TTS
metrics:
- wer
model-index:
- name: Whisper Tunisien
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Tunisian_dataset_STT-TTS
type: Arbi-Houssem/Tunisian_dataset_STT-TTS
args: 'config: ar, split: test'
metrics:
- name: Wer
type: wer
value: 111.1901681759379
Whisper Tunisien
This model is a fine-tuned version of openai/whisper-small on the Tunisian_dataset_STT-TTS dataset. It achieves the following results on the evaluation set:
- Loss: 3.9898
- Wer: 111.1902
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: 12
- 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 |
|---|---|---|---|---|
| 0.2639 | 5.7471 | 500 | 2.8790 | 103.3635 |
| 0.0292 | 11.4943 | 1000 | 3.4175 | 131.9534 |
| 0.0045 | 17.2414 | 1500 | 3.7135 | 106.2743 |
| 0.0021 | 22.9885 | 2000 | 3.7732 | 119.7930 |
| 0.0012 | 28.7356 | 2500 | 3.8911 | 124.9677 |
| 0.0004 | 34.4828 | 3000 | 3.9580 | 130.2717 |
| 0.0003 | 40.2299 | 3500 | 3.9781 | 108.7969 |
| 0.0003 | 45.9770 | 4000 | 3.9898 | 111.1902 |
Framework versions
- Transformers 4.42.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1