Whisper Tiny ar-quran

This model is a fine-tuned version of openai/whisper-tiny on the Quran dataset. It achieves the following results on the evaluation set:

Loss: 0.0188
Wer: 1.9035
Cer: 0.6582

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: 128
eval_batch_size: 128
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.04
training_steps: 10452

Training results

Training Loss	Epoch	Step	Validation Loss	Wer	Cer
0.1204	0.0957	1000	0.1922	19.2088	6.2785
0.0939	0.1914	2000	0.0947	9.7640	3.1603
0.0229	0.2870	3000	0.0615	6.4970	2.1582
0.0345	0.3827	4000	0.0447	4.6754	1.5399
0.0222	1.0071	5000	0.0353	3.6451	1.2228
0.0165	1.1028	6000	0.0302	3.2147	1.0847
0.0148	1.1984	7000	0.0252	2.6315	0.9019
0.006	1.2941	8000	0.0222	2.3478	0.7940
0.0121	1.3898	9000	0.0200	2.0813	0.7232
0.0078	2.0147	10000	0.0188	1.9035	0.6582

Framework versions

Transformers 4.42.0.dev0
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.19.1

Citation

Please cite the model using the following BibTeX entry:

@misc{deepdml/whisper-tiny-ar-quran-mix-norm,
      title={Fine-tuned Whisper tiny ASR model for speech recognition in Arabic},
      author={Jimenez, David},
      howpublished={\url{https://huggingface.co/deepdml/whisper-tiny-ar-quran-mix-norm}},
      year={2025}
    }