--- license: apache-2.0 base_model: facebook/deit-small-patch16-224 tags: - generated_from_trainer datasets: - imagefolder metrics: - accuracy model-index: - name: hushem_1x_deit_small_adamax_00001_fold5 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: 0.6585365853658537 --- # hushem_1x_deit_small_adamax_00001_fold5 This model is a fine-tuned version of [facebook/deit-small-patch16-224](https://huggingface.co/facebook/deit-small-patch16-224) on the imagefolder dataset. It achieves the following results on the evaluation set: - Loss: 0.7730 - Accuracy: 0.6585 ## 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: 1e-05 - 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 | |:-------------:|:-----:|:----:|:---------------:|:--------:| | No log | 1.0 | 6 | 1.3080 | 0.3171 | | 1.348 | 2.0 | 12 | 1.2421 | 0.3659 | | 1.348 | 3.0 | 18 | 1.1840 | 0.4634 | | 1.1221 | 4.0 | 24 | 1.1443 | 0.4634 | | 0.9962 | 5.0 | 30 | 1.1209 | 0.4634 | | 0.9962 | 6.0 | 36 | 1.0884 | 0.5366 | | 0.8532 | 7.0 | 42 | 1.0512 | 0.5122 | | 0.8532 | 8.0 | 48 | 1.0147 | 0.5366 | | 0.73 | 9.0 | 54 | 0.9886 | 0.5366 | | 0.61 | 10.0 | 60 | 0.9683 | 0.5610 | | 0.61 | 11.0 | 66 | 0.9452 | 0.5854 | | 0.5241 | 12.0 | 72 | 0.9201 | 0.6341 | | 0.5241 | 13.0 | 78 | 0.9013 | 0.6341 | | 0.4293 | 14.0 | 84 | 0.8851 | 0.6341 | | 0.3674 | 15.0 | 90 | 0.8707 | 0.6341 | | 0.3674 | 16.0 | 96 | 0.8542 | 0.6341 | | 0.304 | 17.0 | 102 | 0.8474 | 0.6341 | | 0.304 | 18.0 | 108 | 0.8370 | 0.6341 | | 0.2449 | 19.0 | 114 | 0.8233 | 0.6341 | | 0.2119 | 20.0 | 120 | 0.8193 | 0.6341 | | 0.2119 | 21.0 | 126 | 0.8116 | 0.6341 | | 0.1788 | 22.0 | 132 | 0.8051 | 0.6341 | | 0.1788 | 23.0 | 138 | 0.7954 | 0.6341 | | 0.1445 | 24.0 | 144 | 0.7897 | 0.6341 | | 0.1262 | 25.0 | 150 | 0.7881 | 0.6829 | | 0.1262 | 26.0 | 156 | 0.7818 | 0.6585 | | 0.1066 | 27.0 | 162 | 0.7872 | 0.6829 | | 0.1066 | 28.0 | 168 | 0.7762 | 0.6585 | | 0.0891 | 29.0 | 174 | 0.7687 | 0.6585 | | 0.0806 | 30.0 | 180 | 0.7658 | 0.6829 | | 0.0806 | 31.0 | 186 | 0.7688 | 0.6829 | | 0.0692 | 32.0 | 192 | 0.7732 | 0.6829 | | 0.0692 | 33.0 | 198 | 0.7763 | 0.6585 | | 0.0592 | 34.0 | 204 | 0.7749 | 0.6585 | | 0.0587 | 35.0 | 210 | 0.7694 | 0.6829 | | 0.0587 | 36.0 | 216 | 0.7701 | 0.6829 | | 0.0549 | 37.0 | 222 | 0.7733 | 0.6585 | | 0.0549 | 38.0 | 228 | 0.7741 | 0.6585 | | 0.0463 | 39.0 | 234 | 0.7744 | 0.6585 | | 0.0481 | 40.0 | 240 | 0.7732 | 0.6585 | | 0.0481 | 41.0 | 246 | 0.7732 | 0.6585 | | 0.0468 | 42.0 | 252 | 0.7730 | 0.6585 | | 0.0468 | 43.0 | 258 | 0.7730 | 0.6585 | | 0.0455 | 44.0 | 264 | 0.7730 | 0.6585 | | 0.0473 | 45.0 | 270 | 0.7730 | 0.6585 | | 0.0473 | 46.0 | 276 | 0.7730 | 0.6585 | | 0.0444 | 47.0 | 282 | 0.7730 | 0.6585 | | 0.0444 | 48.0 | 288 | 0.7730 | 0.6585 | | 0.048 | 49.0 | 294 | 0.7730 | 0.6585 | | 0.0476 | 50.0 | 300 | 0.7730 | 0.6585 | ### Framework versions - Transformers 4.35.0 - Pytorch 2.1.0+cu118 - Datasets 2.14.6 - Tokenizers 0.14.1