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Baselhany/
Graduation_Project_Whisper_base_s5621

Name: Graduation_Project_Whisper_base_s5621
Availability: InStock

automatic-speech-recognition

generated_from_trainer

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Whisper base AR - BA

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: 0.0112
Wer: 0.0623
Cer: 0.0276

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: 16
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 32
optimizer: Use OptimizerNames.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: 5
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer	Cer
0.0009	1.0	1340	0.0072	0.0666	0.0296
0.0007	2.0	2680	0.0068	0.0655	0.0289
0.0005	3.0	4020	0.0079	0.0608	0.0280
0.0003	4.0	5360	0.0097	0.0632	0.0290
0.0001	4.9966	6695	0.0113	0.0559	0.0259

Framework versions

Transformers 4.51.1
Pytorch 2.5.1+cu124
Datasets 3.5.0
Tokenizers 0.21.0

Baselhany/Graduation_Project_Whisper_base_s5621

Whisper base AR - BA

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Baselhany/
Graduation_Project_Whisper_base_s5621