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a130531
metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - imagefolder
metrics:
  - accuracy
model-index:
  - name: >-
      convnextv2-large-1k-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: 0.9900990099009901

convnextv2-large-1k-224-finetuned-BreastCancer-Classification-BreakHis-AH-60-20-20

This model is a fine-tuned version of facebook/convnextv2-large-1k-224 on the imagefolder dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0353
  • Accuracy: 0.9901

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
  • 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
0.5207 1.0 199 0.4745 0.8887
0.2029 2.0 398 0.2072 0.9401
0.1615 3.0 597 0.1489 0.9547
0.1662 4.0 796 0.1312 0.9562
0.1986 5.0 995 0.1026 0.9698
0.0854 6.0 1194 0.0583 0.9802
0.0538 7.0 1393 0.0568 0.9835
0.0977 8.0 1592 0.0654 0.9793
0.6971 9.0 1791 0.6821 0.5450
0.211 10.0 1990 0.1654 0.9326
0.1775 11.0 2189 0.0859 0.9665
0.0042 12.0 2388 0.0353 0.9901

Framework versions

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