Diabetic_RetinoPathy_detection

This model is a fine-tuned version of facebook/dinov2-base on the imagefolder dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2262
  • Accuracy: 0.968
  • F1: 0.9678

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: 2e-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: 10

Training results

Training Loss Epoch Step Validation Loss Accuracy F1
0.3853 1.0 250 0.4918 0.874 0.8729
0.5345 2.0 500 0.4390 0.878 0.8771
0.4693 3.0 750 0.3857 0.88 0.8796
0.1933 4.0 1000 0.3444 0.894 0.8948
0.3146 5.0 1250 0.2456 0.936 0.9362
0.1832 6.0 1500 0.3369 0.924 0.9229
0.1407 7.0 1750 0.3425 0.946 0.9454
0.1462 8.0 2000 0.2864 0.948 0.9476
0.0905 9.0 2250 0.2177 0.956 0.9560
0.0859 10.0 2500 0.2262 0.968 0.9678

Framework versions

  • Transformers 4.45.1
  • Pytorch 2.4.0
  • Datasets 3.0.1
  • Tokenizers 0.20.0
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Evaluation results