YoussefAshmawy/Graduation_Project_Whisper_base

Whisper base AR - YA

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

• Loss: 0.0033
• Wer: 0.0497
• Cer: 0.0200

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: 8
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 16
• optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 500
• num_epochs: 25
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer	Cer
0.0024	1.0	320	0.0034	0.0440	0.0180
0.0014	2.0	640	0.0049	0.0653	0.0257
0.0013	3.0	960	0.0057	0.0766	0.0283
0.0007	4.0	1280	0.0057	0.0681	0.0290
0.0004	5.0	1600	0.0057	0.0617	0.0253
0.0002	6.0	1920	0.0060	0.0662	0.0244
0.0002	7.0	2240	0.0068	0.0624	0.0237
0.0003	8.0	2560	0.0061	0.0652	0.0259
0.0003	9.0	2880	0.0067	0.0648	0.0252
0.0004	10.0	3200	0.0062	0.0670	0.0259
0.0002	11.0	3520	0.0061	0.0610	0.0230
0.0001	12.0	3840	0.0064	0.0581	0.0217
0.0001	13.0	4160	0.0061	0.0576	0.0217
0.0	14.0	4480	0.0062	0.0594	0.0235
0.0	15.0	4800	0.0066	0.0630	0.0251
0.0	16.0	5120	0.0069	0.0581	0.0240
0.0	17.0	5440	0.0070	0.0579	0.0228
0.0	18.0	5760	0.0071	0.0586	0.0232
0.0	19.0	6080	0.0072	0.0590	0.0239
0.0	20.0	6400	0.0072	0.0576	0.0234
0.0	21.0	6720	0.0073	0.0574	0.0239
0.0	22.0	7040	0.0073	0.0577	0.0240
0.0	23.0	7360	0.0074	0.0577	0.0240
0.0	24.0	7680	0.0076	0.0613	0.0246
0.0	25.0	8000	0.0074	0.0581	0.0244

Framework versions

• Transformers 4.46.3
• Pytorch 2.4.0
• Datasets 3.1.0
• Tokenizers 0.20.3