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metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - imagefolder
metrics:
  - accuracy
model-index:
  - name: >-
      swinv2-large-patch4-window12to16-192to256-22kto1k-ft-finetuned-BreastCancer-BreakHis-AH-60-20-20
    results:
      - task:
          name: Image Classification
          type: image-classification
        dataset:
          name: imagefolder
          type: imagefolder
          config: Splitted-Resized
          split: train
          args: Splitted-Resized
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9943422913719944

swinv2-large-patch4-window12to16-192to256-22kto1k-ft-finetuned-BreastCancer-BreakHis-AH-60-20-20

This model is a fine-tuned version of microsoft/swinv2-large-patch4-window12to16-192to256-22kto1k-ft on the imagefolder dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0229
  • Accuracy: 0.9943

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: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.5
  • num_epochs: 7

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.2053 1.0 199 0.1227 0.9496
0.1302 2.0 398 0.0665 0.9736
0.0784 3.0 597 0.0600 0.9778
0.1181 4.0 796 0.0449 0.9849
0.208 5.0 995 0.0393 0.9887
0.0057 6.0 1194 0.0229 0.9943
0.0017 7.0 1393 0.0263 0.9939

Framework versions

  • Transformers 4.30.2
  • Pytorch 2.0.1+cu118
  • Datasets 2.13.1
  • Tokenizers 0.13.3