whisper-base-ar-quran – AI Model by tarteel-ai | AlphaNeural AI

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whisper-base-ar-quran

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whisper-base-ar-quran

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

Loss: 0.0839
Wer: 5.7544

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
distributed_type: multi-GPU
num_devices: 8
total_train_batch_size: 128
total_eval_batch_size: 64
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 Loss	Epoch	Step	Validation Loss	Wer
0.1092	0.05	250	0.1969	13.3890
0.0361	0.1	500	0.1583	10.6375
0.0192	0.15	750	0.1109	8.8468
0.0144	0.2	1000	0.1157	7.9754
0.008	0.25	1250	0.1000	7.5360
0.0048	1.03	1500	0.0933	6.8227
0.0113	1.08	1750	0.0955	6.9638
0.0209	1.13	2000	0.0824	6.3586
0.0043	1.18	2250	0.0830	6.3444
0.002	1.23	2500	0.1015	6.3025
0.0013	2.01	2750	0.0863	6.0639
0.0014	2.06	3000	0.0905	6.0213
0.0018	2.11	3250	0.0864	6.0293
0.0008	2.16	3500	0.0887	5.9308
0.0029	2.21	3750	0.0777	5.9159
0.0022	2.26	4000	0.0847	5.8749
0.0005	3.05	4250	0.0827	5.8352
0.0003	3.1	4500	0.0826	5.7800
0.0006	3.15	4750	0.0833	5.7625
0.0003	3.2	5000	0.0839	5.7544

Framework versions

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