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Baselhany/
fine_tune_Whisper_tiny2

Name: fine_tune_Whisper_tiny2
Availability: InStock

automatic-speech-recognition

generated_from_trainer

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Whisper tiny AR - BH

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

Loss: 0.0058
Wer: 0.0785
Cer: 0.0309

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: 5e-06
train_batch_size: 16
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 64
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 500
num_epochs: 25
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer	Cer
0.0067	1.0	273	0.0054	0.0757	0.0295
0.0057	2.0	546	0.0053	0.0702	0.0269
0.0044	3.0	819	0.0054	0.0710	0.0270
0.0031	4.0	1092	0.0056	0.0740	0.0270
0.0028	5.0	1365	0.0058	0.0778	0.0307
0.0024	6.0	1638	0.0061	0.0760	0.0282
0.0015	7.0	1911	0.0065	0.0733	0.0274

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0

Baselhany/fine_tune_Whisper_tiny2

Whisper tiny AR - BH

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Baselhany/
fine_tune_Whisper_tiny2