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metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - imagefolder
metrics:
  - accuracy
model-index:
  - name: 3-classifier-finetuned-padchest
    results:
      - task:
          name: Image Classification
          type: image-classification
        dataset:
          name: imagefolder
          type: imagefolder
          config: default
          split: train
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.7250755287009063

3-classifier-finetuned-padchest

This model is a fine-tuned version of nickmuchi/vit-finetuned-chest-xray-pneumonia on the imagefolder dataset. It achieves the following results on the evaluation set:

  • Loss: 0.8505
  • Accuracy: 0.7251

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: 32
  • eval_batch_size: 32
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 128
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss Accuracy
2.0499 1.0 16 1.8761 0.3686
1.704 2.0 32 1.5961 0.4955
1.5393 3.0 48 1.3570 0.5770
1.3161 4.0 64 1.2687 0.5770
1.1991 5.0 80 1.1740 0.6073
1.1459 6.0 96 1.1388 0.6073
1.071 7.0 112 1.0763 0.6405
0.9948 8.0 128 1.0419 0.6526
0.9902 9.0 144 0.9869 0.6979
0.9515 10.0 160 0.9825 0.6767
0.9277 11.0 176 0.9645 0.6858
0.9182 12.0 192 0.9264 0.7009
0.895 13.0 208 0.9138 0.6979
0.8765 14.0 224 0.9089 0.7100
0.8536 15.0 240 0.8941 0.7009
0.8385 16.0 256 0.8764 0.7221
0.8187 17.0 272 0.8659 0.7160
0.8172 18.0 288 0.8673 0.7069
0.8101 19.0 304 0.8530 0.7341
0.8127 20.0 320 0.8505 0.7251

Framework versions

  • Transformers 4.28.0.dev0
  • Pytorch 2.0.0+cu117
  • Datasets 2.18.0
  • Tokenizers 0.13.3