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metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - imagefolder
metrics:
  - accuracy
model-index:
  - name: >-
      beit-large-patch16-224-finetuned-BreastCancer-Classification-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: 0.9938708156529938

beit-large-patch16-224-finetuned-BreastCancer-Classification-BreakHis-AH-60-20-20

This model is a fine-tuned version of microsoft/beit-large-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0275
  • Accuracy: 0.9939

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-06
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • gradient_accumulation_steps: 2
  • 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: 0.9
  • num_epochs: 12

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.46 1.0 199 0.3950 0.8482
0.2048 2.0 398 0.1886 0.9189
0.182 3.0 597 0.1382 0.9481
0.0826 4.0 796 0.0760 0.9694
0.0886 5.0 995 0.0600 0.9788
0.0896 6.0 1194 0.0523 0.9802
0.0774 7.0 1393 0.0482 0.9826
0.0876 8.0 1592 0.0289 0.9877
0.1105 9.0 1791 0.0580 0.9821
0.0289 10.0 1990 0.0294 0.9925
0.0594 11.0 2189 0.0331 0.9906
0.0011 12.0 2388 0.0275 0.9939

Framework versions

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