whisper-medium-ur-v3 – AI Model by abdullah090809 | AlphaNeural AI

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abdullah090809/
whisper-medium-ur-v3

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automatic-speech-recognition

generated_from_trainer

mirfan899/jalandhary_asr

abdullah090809/whisper-medium-ur-v2-resumed

endpoints_compatible

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whisper-medium-v3

This model is a fine-tuned version of GogetaBlueMUI/whisper-medium-ur-v2-resumed on the jalandhary_asr dataset. It achieves the following results on the evaluation set:

Loss: 0.1647
Wer: 22.1497

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: 8
eval_batch_size: 8
seed: 42
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: 110
training_steps: 1050
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.1884	0.3401	350	0.1993	24.2099
0.187	0.6803	700	0.1758	23.0122
0.1198	1.0204	1050	0.1647	22.1497

Framework versions

Transformers 4.49.0
Pytorch 2.5.1+cu121
Datasets 3.4.1
Tokenizers 0.21.0