metadata
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: 44.46994692296657
Whisper Tunisien
This model is a fine-tuned version of openai/whisper-small on the Tunisian_dataset_STT-TTS15s_filtred1.0_Mixed dataset. It achieves the following results on the evaluation set:
- Loss: 1.1841
- Wer: 44.4699
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: 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 |
|---|---|---|---|---|
| 0.3626 | 4.5045 | 500 | 0.8379 | 53.0340 |
| 0.0527 | 9.0090 | 1000 | 0.9350 | 48.5440 |
| 0.0111 | 13.5135 | 1500 | 1.0400 | 49.4907 |
| 0.0049 | 18.0180 | 2000 | 1.1030 | 44.6564 |
| 0.0017 | 22.5225 | 2500 | 1.1338 | 44.7568 |
| 0.0014 | 27.0270 | 3000 | 1.1618 | 44.8142 |
| 0.0009 | 31.5315 | 3500 | 1.1784 | 44.8429 |
| 0.0009 | 36.0360 | 4000 | 1.1841 | 44.4699 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1