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swinv2-base-patch4-window12-192-22k-finetuned-lora-ISIC-2019
TriDat/swinv2-base-patch4-window12-192-22k-finetuned-lora-ISIC-2019
swinv2-base-patch4-window12-192-22k-finetuned-lora-ISIC-2019 is a image classification model from TriDat. Use it when you need a label for an image. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Image Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- swinv2
- Access
- Public
- Created
- Apr 8, 2024
- Updated
- Jul 1, 2025
- SHA
- 3796af3d
Base models
Datasets
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
swinv2-base-patch4-window12-192-22k-finetuned-lora-ISIC-2019
This model is a fine-tuned version of microsoft/swinv2-base-patch4-window12-192-22k on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.4329
- Accuracy: 0.9160
- Precision: 0.9157
- Recall: 0.9160
- F1: 0.9156
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: 0.001
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 100
Training results
Framework versions
- Transformers 4.32.1
- Pytorch 2.0.1
- Datasets 2.12.0
- Tokenizers 0.13.2
- Task
- Image Classification
- Library
- transformers
- Type
- swinv2
- License
- apache-2.0
- Created
- Apr 8, 2024
- Updated
- Jul 1, 2025