whisper-medium-medical

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: 0.2889
• Wer: 0.1281

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: 1e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 32
• optimizer: Use OptimizerNames.ADAMW_BNB 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
• num_epochs: 5
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
2.4747	1.0	102	0.3153	0.1621
1.4045	2.0	204	0.2641	0.1341
0.6465	3.0	306	0.2671	0.1321
0.2759	4.0	408	0.2727	0.1278
0.1574	5.0	510	0.2889	0.1281

Framework versions

• Transformers 5.0.0
• Pytorch 2.10.0+cu128
• Datasets 2.19.0
• Tokenizers 0.22.2