whisper-small-final-v3 – AI Model by AsemBadr | AlphaNeural AI

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AsemBadr/
whisper-small-final-v3

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automatic-speech-recognition

hf-asr-leaderboard

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openai/whisper-small

endpoints_compatible

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Whisper Small for Quran Recognition

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

Loss: 0.0210
Wer: 3.2835

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: 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: 12000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0073	1.62	500	0.0249	5.0026
0.0014	3.24	1000	0.0214	4.1086
0.0008	4.85	1500	0.0221	3.9883
0.0	6.47	2000	0.0180	2.9740
0.0	8.09	2500	0.0177	3.0944
0.0	9.71	3000	0.0178	3.0944
0.0	11.33	3500	0.0179	3.1288
0.0	12.94	4000	0.0179	3.1288
0.0	14.56	4500	0.0181	2.8881
0.0	16.18	5000	0.0184	2.9225
0.0	17.8	5500	0.0186	3.0256
0.0	19.42	6000	0.0188	3.1803
0.0	21.04	6500	0.0190	3.1631
0.0	22.65	7000	0.0191	3.1631
0.0	24.27	7500	0.0192	3.1803
0.0	25.89	8000	0.0192	3.1631
0.0	27.51	8500	0.0196	3.2491
0.0	29.13	9000	0.0199	3.2491
0.0	30.74	9500	0.0202	3.2835
0.0	32.36	10000	0.0204	3.2319
0.0	33.98	10500	0.0207	3.2835
0.0	35.6	11000	0.0209	3.2663
0.0	37.22	11500	0.0210	3.2835
0.0	38.83	12000	0.0210	3.2835

Framework versions

Transformers 4.40.0.dev0
Pytorch 2.1.2
Datasets 2.17.1
Tokenizers 0.15.1