Model reference · open weights

whisper-tiny-ar-quran

Audio tarteel-ai Speech→text 1 build Open weights 1k dl/mo

whisper-tiny-ar-quran is an open-weight audio or speech model from tarteel-ai. whisper-tiny-ar-quran (BF16) weighs 151 MB; the smallest configuration that runs it is RTX 3060 12 GB.

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  • whisper-tiny-ar-quran is an automatic speech recognition model developed by tarteel-ai.
  • It is a fine-tuned version of openai/whisper-tiny and is licensed under apache-2.0.
  • The model achieves a word error rate of 7.0535 on its evaluation set.

Summary of the tarteel-ai/whisper-tiny-ar-quran model card, 2026-10-01

What it is

Released bytarteel-ai
Released2022-12-08
VRAM151 MB for the weights

What it runs on

Memory and cards for whisper-tiny-ar-quran (BF16)

151 MBweights, file size
1.6 GBruntime overhead
CardOne streamMemory
RTX 3060 12 GBfits11.6 GB
RTX 4060 Ti 16 GBfits15.4 GB
RTX 3090 24 GBfits23.4 GB
RTX 4090 24 GBfits23.4 GB
RTX 5090 32 GBfits31.0 GB
L40S 48 GBfits44.0 GB
A100 80 GBfits78.2 GB
H100 80 GBfits78.1 GB
RTX PRO 6000 Blackwell 96 GBfits93.8 GB
DGX Spark (GB10) 128 GB unifiedfits107 GB
H200 141 GBfits138 GB
B200 180 GBfits176 GB

From the model card

What tarteel-ai says about whisper-tiny-ar-quran

Read the model card

This model is a fine-tuned version of openai/whisper-tiny on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0928
  • Wer: 7.0535

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: 8
  • 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: 5000
  • mixed_precision_training: Native AMP

Training results

Training LossEpochStepValidation LossWer
0.17660.055000.282920.0236
0.11290.0910000.198113.8364
0.07750.1415000.176312.5450
0.06780.1920000.148510.7302
0.04370.2325000.13369.6693
0.03410.2830000.12448.9602
0.03020.3335000.10598.2224
0.01890.3740000.10447.6902
0.01670.4245000.09667.2643
0.01510.4750000.09287.0535

Framework versions

  • Transformers 4.26.0.dev0
  • Pytorch 1.13.0+cu117
  • Datasets 2.7.1.dev0
  • Tokenizers 0.13.2

Quoted from the model card on Hugging Face. The full card is behind the Hugging Face link above.

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