--- license: apache-2.0 base_model: facebook/deit-base-patch16-224 tags: - generated_from_trainer datasets: - imagefolder metrics: - accuracy model-index: - name: hushem_40x_deit_base_sgd_001_fold4 results: - task: name: Image Classification type: image-classification dataset: name: imagefolder type: imagefolder config: default split: test args: default metrics: - name: Accuracy type: accuracy value: 0.9285714285714286 --- # hushem_40x_deit_base_sgd_001_fold4 This model is a fine-tuned version of [facebook/deit-base-patch16-224](https://huggingface.co/facebook/deit-base-patch16-224) on the imagefolder dataset. It achieves the following results on the evaluation set: - Loss: 0.2186 - Accuracy: 0.9286 ## 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: 0.001 - train_batch_size: 32 - eval_batch_size: 32 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 50 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:-----:|:---------------:|:--------:| | 1.2742 | 1.0 | 219 | 1.3421 | 0.4286 | | 1.1364 | 2.0 | 438 | 1.2693 | 0.4048 | | 0.9912 | 3.0 | 657 | 1.1701 | 0.5238 | | 0.8292 | 4.0 | 876 | 1.0493 | 0.6429 | | 0.7771 | 5.0 | 1095 | 0.9148 | 0.7143 | | 0.6956 | 6.0 | 1314 | 0.8048 | 0.7381 | | 0.519 | 7.0 | 1533 | 0.7062 | 0.8095 | | 0.5042 | 8.0 | 1752 | 0.6401 | 0.7857 | | 0.4397 | 9.0 | 1971 | 0.5785 | 0.8333 | | 0.3933 | 10.0 | 2190 | 0.5338 | 0.8571 | | 0.341 | 11.0 | 2409 | 0.4959 | 0.8810 | | 0.3345 | 12.0 | 2628 | 0.4569 | 0.8810 | | 0.2949 | 13.0 | 2847 | 0.4265 | 0.9048 | | 0.2608 | 14.0 | 3066 | 0.3999 | 0.9286 | | 0.2368 | 15.0 | 3285 | 0.3796 | 0.9286 | | 0.2257 | 16.0 | 3504 | 0.3614 | 0.9286 | | 0.232 | 17.0 | 3723 | 0.3430 | 0.9286 | | 0.1928 | 18.0 | 3942 | 0.3249 | 0.9286 | | 0.1804 | 19.0 | 4161 | 0.3144 | 0.9286 | | 0.1542 | 20.0 | 4380 | 0.3019 | 0.9048 | | 0.1333 | 21.0 | 4599 | 0.2915 | 0.9286 | | 0.1333 | 22.0 | 4818 | 0.2894 | 0.9048 | | 0.1178 | 23.0 | 5037 | 0.2746 | 0.9286 | | 0.1098 | 24.0 | 5256 | 0.2771 | 0.9048 | | 0.1099 | 25.0 | 5475 | 0.2649 | 0.9048 | | 0.0836 | 26.0 | 5694 | 0.2732 | 0.9048 | | 0.0751 | 27.0 | 5913 | 0.2625 | 0.9048 | | 0.0745 | 28.0 | 6132 | 0.2608 | 0.9048 | | 0.0826 | 29.0 | 6351 | 0.2526 | 0.9048 | | 0.079 | 30.0 | 6570 | 0.2463 | 0.9286 | | 0.0659 | 31.0 | 6789 | 0.2439 | 0.9048 | | 0.0738 | 32.0 | 7008 | 0.2422 | 0.9286 | | 0.0683 | 33.0 | 7227 | 0.2335 | 0.9286 | | 0.0674 | 34.0 | 7446 | 0.2343 | 0.9048 | | 0.0633 | 35.0 | 7665 | 0.2311 | 0.9048 | | 0.0608 | 36.0 | 7884 | 0.2259 | 0.9286 | | 0.0543 | 37.0 | 8103 | 0.2239 | 0.9286 | | 0.0444 | 38.0 | 8322 | 0.2256 | 0.9286 | | 0.0496 | 39.0 | 8541 | 0.2255 | 0.9286 | | 0.0513 | 40.0 | 8760 | 0.2253 | 0.9286 | | 0.0449 | 41.0 | 8979 | 0.2226 | 0.9286 | | 0.0449 | 42.0 | 9198 | 0.2216 | 0.9286 | | 0.0549 | 43.0 | 9417 | 0.2202 | 0.9286 | | 0.0488 | 44.0 | 9636 | 0.2213 | 0.9286 | | 0.0437 | 45.0 | 9855 | 0.2208 | 0.9286 | | 0.0362 | 46.0 | 10074 | 0.2201 | 0.9286 | | 0.0622 | 47.0 | 10293 | 0.2188 | 0.9286 | | 0.0546 | 48.0 | 10512 | 0.2185 | 0.9286 | | 0.0472 | 49.0 | 10731 | 0.2186 | 0.9286 | | 0.0581 | 50.0 | 10950 | 0.2186 | 0.9286 | ### Framework versions - Transformers 4.32.1 - Pytorch 2.1.0+cu121 - Datasets 2.12.0 - Tokenizers 0.13.2