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ktp-spoof-clip

This model is a fine-tuned version of openai/clip-vit-base-patch32 on the imagefolder dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0740
  • Accuracy: 0.9853

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: 15

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 0.8889 4 0.5501 0.8088
No log 2.0 9 0.3671 0.8529
0.5611 2.8889 13 0.3852 0.8235
0.5611 4.0 18 0.2422 0.9118
0.4558 4.8889 22 0.3534 0.8824
0.4558 6.0 27 0.1137 0.9412
0.3562 6.8889 31 0.5266 0.7941
0.3562 8.0 36 0.1918 0.9118
0.1201 8.8889 40 0.0301 1.0
0.1201 10.0 45 0.0450 0.9853
0.1201 10.8889 49 0.0327 0.9853
0.0604 12.0 54 0.0898 0.9706
0.0604 12.8889 58 0.0789 0.9853
0.0322 13.3333 60 0.0740 0.9853

Framework versions

  • Transformers 4.41.2
  • Pytorch 2.1.2
  • Datasets 2.19.2
  • Tokenizers 0.19.1
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F32
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Evaluation results