deepdml/whisper-base-ar-quran-mix

Whisper Base ar-quran

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

• Loss: 0.0129
• Wer: 16.1651

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: 64
• eval_batch_size: 64
• 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: 20905

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.1147	0.0478	1000	0.1044	46.2933
0.0414	0.0957	2000	0.0608	56.1421
0.0888	0.1435	3000	0.0417	38.5954
0.0238	0.1913	4000	0.0383	24.4833
0.0171	0.2392	5000	0.0216	17.2703
0.0166	0.2870	6000	0.0228	24.1871
0.0243	0.3348	7000	0.0302	40.0101
0.0307	0.3827	8000	0.0200	23.0494
0.0081	0.4305	9000	0.0198	13.9295
0.01	1.0071	10000	0.0226	25.6162
0.0169	1.0550	11000	0.0146	13.7364
0.0148	1.1028	12000	0.0189	32.5028
0.0137	1.1506	13000	0.0308	68.5616
0.012	1.1985	14000	0.0176	17.1361
0.0116	1.2463	15000	0.0128	17.6105
0.0098	1.2941	16000	0.0221	31.6383
0.0124	1.3420	17000	0.0180	26.3024
0.0067	1.3898	18000	0.0188	36.3544
0.0166	1.4376	19000	0.0138	26.3494
0.0154	2.0148	20000	0.0129	16.1651

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