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metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - imagefolder
metrics:
  - accuracy
model-index:
  - name: convnext-tiny-224-drfx-CT-classifier
    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: 0.7647058823529411

convnext-tiny-224-drfx-CT-classifier

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

  • Loss: 0.6452
  • Accuracy: 0.7647

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: 4
  • eval_batch_size: 4
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 15

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 4 0.7084 0.5882
No log 2.0 8 0.7021 0.5294
0.6143 3.0 12 0.7024 0.4118
0.6143 4.0 16 0.6856 0.5294
0.6154 5.0 20 0.6955 0.5294
0.6154 6.0 24 0.7119 0.5294
0.6154 7.0 28 0.7086 0.5882
0.5786 8.0 32 0.6967 0.5882
0.5786 9.0 36 0.6773 0.6471
0.5026 10.0 40 0.6537 0.7647
0.5026 11.0 44 0.6439 0.7647
0.5026 12.0 48 0.6390 0.7647
0.5086 13.0 52 0.6434 0.7647
0.5086 14.0 56 0.6425 0.7647
0.448 15.0 60 0.6452 0.7647

Framework versions

  • Transformers 4.28.0
  • Pytorch 2.0.1+cu118
  • Datasets 2.12.0
  • Tokenizers 0.13.3