README.md

metadata

license: apache-2.0
base_model: microsoft/swin-base-patch4-window7-224-in22k
tags:
  - generated_from_trainer
datasets:
  - imagefolder
metrics:
  - accuracy
model-index:
  - name: swin-base-patch4-window7-224-in22k-finetuned-CT-V2
    results:
      - task:
          name: Image Classification
          type: image-classification
        dataset:
          name: imagefolder
          type: imagefolder
          config: default
          split: Testing
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.7944162436548223

swin-base-patch4-window7-224-in22k-finetuned-CT-V2

This model is a fine-tuned version of microsoft/swin-base-patch4-window7-224-in22k on the imagefolder dataset. It achieves the following results on the evaluation set:

• Loss: 1.3847
• Accuracy: 0.7944

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-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	180	1.1743	0.6675
No log	2.0	360	0.6626	0.8223
No log	3.0	540	1.1876	0.7868
No log	4.0	720	1.2469	0.8274
0.2764	5.0	900	1.3847	0.7944

Framework versions

• Transformers 4.40.2
• Pytorch 2.3.0+cu118
• Datasets 2.19.1
• Tokenizers 0.19.1