|
--- |
|
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: 45.33065557308851 |
|
--- |
|
|
|
<!-- 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: 1.3057 |
|
- Wer: 45.3307 |
|
|
|
## 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: 0.0001 |
|
- 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 | |
|
|:-------------:|:-------:|:----:|:---------------:|:-------:| |
|
| 0.3483 | 4.5045 | 500 | 1.0341 | 53.6221 | |
|
| 0.1138 | 9.0090 | 1000 | 1.1225 | 49.9641 | |
|
| 0.0476 | 13.5135 | 1500 | 1.1610 | 51.5278 | |
|
| 0.0238 | 18.0180 | 2000 | 1.2585 | 48.0993 | |
|
| 0.007 | 22.5225 | 2500 | 1.2873 | 51.6282 | |
|
| 0.0021 | 27.0270 | 3000 | 1.2722 | 46.8656 | |
|
| 0.0007 | 31.5315 | 3500 | 1.2998 | 43.5375 | |
|
| 0.0006 | 36.0360 | 4000 | 1.3057 | 45.3307 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.41.2 |
|
- Pytorch 2.3.1+cu121 |
|
- Datasets 2.20.0 |
|
- Tokenizers 0.19.1 |
|
|
