GogetaBlueMUI/whisper-medium-ur-v2-resumed

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:

• eval_loss: 0.3571
• eval_wer: 25.1658
• eval_runtime: 4297.3715
• eval_samples_per_second: 1.167
• eval_steps_per_second: 0.146
• epoch: 1.3108
• step: 1000

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: 3e-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: 100
• training_steps: 1000
• mixed_precision_training: Native AMP

Framework versions

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