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metadata
license: apache-2.0
base_model: google/vit-large-patch16-224-in21k
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: Psoriasis-Aug-M2-vit-large-patch16-224-in21k
    results: []

Psoriasis-Aug-M2-vit-large-patch16-224-in21k

This model is a fine-tuned version of google/vit-large-patch16-224-in21k on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0268
  • Accuracy: 0.9792

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: 4
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 5

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.4421 0.99 36 0.2504 0.8958
0.0968 1.99 72 0.0631 0.9583
0.0321 2.98 108 0.0639 0.9792
0.0065 4.0 145 0.0234 1.0
0.0067 4.97 180 0.0268 0.9792

Test results

Classes precision recall f1-score support
Erythromelal 1.00 1.00 1.00 5
Guttate 1.00 1.00 1.00 7
Inverse 1.00 1.00 1.00 4
Nail 1.00 1.00 1.00 10
Normal 1.00 1.00 1.00 11
Plaque 1.00 1.00 1.00 10
Psoriatic Arthritis 1.00 1.00 1.00 6
Pustular 1.00 1.00 1.00 6
accuracy 1.00 59
macro avg 1.00 1.00 1.00 59
weighted avg 1.00 1.00 1.00 59

confusion Matrix results

image/png

Framework versions

  • Transformers 4.39.3
  • Pytorch 2.1.2
  • Datasets 2.18.0
  • Tokenizers 0.15.2