metadata
language:
- ar
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- ubulut/quran-verses-lite
metrics:
- wer
model-index:
- name: Whisper Tiny AR - Quran
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: quran-whisper-dataset-lite
type: ubulut/quran-verses-lite
config: default
split: None
args: 'config: ar, split: test'
metrics:
- name: Wer
type: wer
value: 85.44520547945206
Whisper Tiny AR - Quran
This model is a fine-tuned version of openai/whisper-tiny on the quran-whisper-dataset-lite dataset. It achieves the following results on the evaluation set:
- Loss: 2.6327
- Wer: 85.4452
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: 16
- eval_batch_size: 16
- 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 |
|---|---|---|---|---|
| 0.0003 | 17.2414 | 1000 | 2.5428 | 86.8579 |
| 0.0001 | 34.4828 | 2000 | 2.5570 | 85.6164 |
| 0.0 | 51.7241 | 3000 | 2.6121 | 85.8305 |
| 0.0 | 68.9655 | 4000 | 2.6327 | 85.4452 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1