multilabel_classification

This model is a fine-tuned version of microsoft/swin-base-patch4-window7-224 on the pascal_voc dataset. It achieves the following results on the evaluation set:

• Loss: 0.2309
• Roc Auc: 0.7662

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: 0.0001
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 3.0

Training results

Training Loss	Epoch	Step	Validation Loss	Roc Auc
0.4603	1.0	157	0.3015	0.6697
0.2922	2.0	314	0.2428	0.7435
0.2561	3.0	471	0.2309	0.7662

Framework versions

• Transformers 4.55.3
• Pytorch 2.8.0+cu128
• Datasets 3.6.0
• Tokenizers 0.21.2