dianavdavidson/wh_med_mucs_30_70_flattened_mucs_52553__val_finetune_trial

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whmedmucs3070flattenedmucs52553valfinetune_trial

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

• —Loss: 0.2779
• —Global Wer: 24.7920

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
• —trainbatchsize: 4
• —evalbatchsize: 4
• —seed: 42
• —optimizer: Use adamwtorchfused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• —lrschedulertype: constantwithwarmup
• —lrschedulerwarmup_steps: 50
• —training_steps: 500

Training results

Framework versions

• —Transformers 5.0.0.dev0
• —Pytorch 2.9.0+cu126
• —Datasets 3.6.0
• —Tokenizers 0.22.2