medsiglip-448-std-classification_2

This model is a fine-tuned version of google/medsiglip-448 on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.5210
• Roc Auc: 0.9582

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: 4
• eval_batch_size: 4
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 16
• optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: cosine
• lr_scheduler_warmup_steps: 5
• num_epochs: 7

Training results

Training Loss	Epoch	Step	Validation Loss	Roc Auc
3.654	1.9268	40	0.9041	0.9064
1.4687	3.8293	80	0.5170	0.9513
0.8319	5.7317	120	0.5210	0.9582

Framework versions

• Transformers 4.57.3
• Pytorch 2.9.0+cu128
• Datasets 4.4.1
• Tokenizers 0.22.1