metadata
language:
- ar
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- ubulut/quran-verses
metrics:
- wer
model-index:
- name: Whisper Tiny AR - Quran
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: quran-whisper-dataset
type: ubulut/quran-verses
config: default
split: None
args: 'config: ar, split: test'
metrics:
- name: Wer
type: wer
value: 63.6986301369863
Whisper Tiny AR - Quran
This model is a fine-tuned version of openai/whisper-tiny on the quran-whisper-dataset dataset. It achieves the following results on the evaluation set:
- Loss: 1.7501
- Wer: 63.6986
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: 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 |
|---|---|---|---|---|
| 0.0 | 200.0 | 1000 | 1.4774 | 72.6027 |
| 0.0 | 400.0 | 2000 | 1.6503 | 61.6438 |
| 0.0 | 600.0 | 3000 | 1.7314 | 63.0137 |
| 0.0 | 800.0 | 4000 | 1.7501 | 63.6986 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1