GogetaBlueMUI/whisper-medium-ur-v3

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