GogetaBlueMUI/whisper-medium-ur

Whisper Medium Ur - Your Name

This model is a fine-tuned version of openai/whisper-medium on the Common Voice 19.0 dataset. It achieves the following results on the evaluation set:

• Loss: 0.3392
• Wer: 26.7354

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
• 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: 150
• training_steps: 1500
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.3835	0.6557	500	0.3813	27.1418
0.2643	1.3108	1000	0.3522	26.4809
0.2424	1.9666	1500	0.3392	26.7354

Framework versions

• Transformers 4.49.0
• Pytorch 2.5.1+cu121
• Datasets 3.4.1
• Tokenizers 0.21.0