deit-base-mri / README.md
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metadata
license: apache-2.0
tags:
  - image-classification
  - generated_from_trainer
datasets:
  - imagefolder
metrics:
  - accuracy
model-index:
  - name: deit-base-mri
    results:
      - task:
          name: Image Classification
          type: image-classification
        dataset:
          name: mriDataSet
          type: imagefolder
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9900709219858156

deit-base-mri

This model is a fine-tuned version of facebook/deit-base-distilled-patch16-224 on the mriDataSet dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0657
  • 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: 32
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 2
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.0107 0.8 500 0.0782 0.9887
0.0065 1.6 1000 0.0657 0.9901

Framework versions

  • Transformers 4.20.1
  • Pytorch 1.11.0+cu113
  • Datasets 2.3.2
  • Tokenizers 0.12.1