| language: es | |
| license: apache-2.0 | |
| library_name: transformers | |
| pipeline_tag: image-classification | |
| tags: | |
| - vision-transformer | |
| - image-classification | |
| - binary-classification | |
| - deepfake-detection | |
| datasets: | |
| - djramirezp/face-classification-dataset | |
| metrics: | |
| - accuracy | |
| - precision | |
| - recall | |
| - f1 | |
| # ViT fine-tuned para clasificacion FAKE/REAL | |
| ## Resumen metodologico | |
| Se utilizo el modelo base `google/vit-base-patch16-224-in21k` y se realizo fine-tuning con `Trainer` de Hugging Face. | |
| Las imagenes se preprocesaron con `AutoImageProcessor` y el entrenamiento se ejecuto con early stopping. | |
| La seleccion del mejor checkpoint se hizo con base en la metrica F1 de validacion. | |
| ## Hiperparametros principales | |
| - learning_rate: 2e-05 | |
| - batch_size: 16 | |
| - num_train_epochs: 8 | |
| - weight_decay: 0.01 | |
| - warmup_ratio: 0.1 | |
| - early_stopping_patience: 2 | |
| - early_stopping_threshold: 0.001 | |
| ## Resultados | |
| ### Validacion | |
| - loss: 0.013790015131235123 | |
| - accuracy: 0.9981718464351006 | |
| - precision: 0.9981786173742297 | |
| - recall: 0.9981718464351006 | |
| - f1: 0.998171895325199 | |
| ### Test | |
| - loss: 0.02344433404505253 | |
| - accuracy: 0.9928952042628775 | |
| - precision: 0.9929184199081565 | |
| - recall: 0.9928952042628775 | |
| - f1: 0.9928942615297829 | |