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metadata
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: Wound-classification
    results: []

Wound-classification

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

  • Loss: 0.1836
  • Accuracy: 0.9575

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: 0.0002
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 8
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.01
  • num_epochs: 16

Training results

Training Loss Epoch Step Validation Loss Accuracy
1.1241 1.0 200 0.7452 0.765
0.5854 2.0 400 0.4880 0.835
0.4279 3.0 600 0.5049 0.8375
0.4041 4.0 800 0.3321 0.8975
0.2805 5.0 1000 0.4105 0.895
0.279 6.0 1200 0.4269 0.8825
0.1782 7.0 1400 0.3583 0.905
0.1834 8.0 1600 0.3009 0.925
0.1197 9.0 1800 0.3020 0.93
0.1231 10.0 2000 0.3352 0.9225
0.1273 11.0 2200 0.2908 0.91
0.1019 12.0 2400 0.2528 0.94
0.0951 13.0 2600 0.2989 0.9325
0.0957 14.0 2800 0.3189 0.9325
0.0618 15.0 3000 0.1973 0.9475
0.0583 16.0 3200 0.1836 0.9575

Framework versions

  • Transformers 4.38.2
  • Pytorch 2.2.1+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2