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

face_poofing_detection

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: 1.6273
  • Accuracy: 0.9871

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: 10

Training results

Training Loss Epoch Step Validation Loss Accuracy
6.3243 0.9846 48 5.6154 0.8919
4.4794 1.9897 97 4.3516 0.9202
3.8293 2.9949 146 3.6687 0.9730
3.2121 4.0 195 3.1092 0.9820
2.733 4.9846 243 2.6919 0.9743
2.3114 5.9897 292 2.2633 0.9923
1.9962 6.9949 341 1.9594 0.9923
1.7789 8.0 390 1.7641 0.9897
1.6642 8.9846 438 1.6506 0.9910
1.6005 9.8462 480 1.6273 0.9871

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.5.0+cu121
  • Datasets 3.1.0
  • Tokenizers 0.19.1