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---
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: 94.30650684931507
---
<!-- 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 Tiny AR - Quran
This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the quran-whisper-dataset-lite dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2877
- Wer: 94.3065
## 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 |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 0.0026 | 17.2414 | 1000 | 2.0479 | 100.2997 |
| 0.0004 | 34.4828 | 2000 | 2.1836 | 94.0925 |
| 0.0002 | 51.7241 | 3000 | 2.2654 | 94.7346 |
| 0.0001 | 68.9655 | 4000 | 2.2877 | 94.3065 |
### Framework versions
- Transformers 4.42.3
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
|