--- license: apache-2.0 base_model: facebook/deit-tiny-patch16-224 tags: - generated_from_trainer datasets: - imagefolder metrics: - accuracy model-index: - name: hushem_1x_deit_rms_lr0001_fold3 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: 0.46511627906976744 --- # hushem_1x_deit_rms_lr0001_fold3 This model is a fine-tuned version of [facebook/deit-tiny-patch16-224](https://huggingface.co/facebook/deit-tiny-patch16-224) on the imagefolder dataset. It achieves the following results on the evaluation set: - Loss: 2.7920 - Accuracy: 0.4651 ## 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: 0.0001 - 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 | 1.3959 | 0.2558 | | 2.0191 | 2.0 | 12 | 1.4540 | 0.2791 | | 2.0191 | 3.0 | 18 | 1.5040 | 0.3721 | | 1.4688 | 4.0 | 24 | 1.3687 | 0.3256 | | 1.3397 | 5.0 | 30 | 1.3082 | 0.4186 | | 1.3397 | 6.0 | 36 | 1.3917 | 0.3256 | | 1.1986 | 7.0 | 42 | 1.4209 | 0.3256 | | 1.1986 | 8.0 | 48 | 1.4510 | 0.3721 | | 1.0698 | 9.0 | 54 | 1.4225 | 0.3023 | | 0.8214 | 10.0 | 60 | 1.5289 | 0.4186 | | 0.8214 | 11.0 | 66 | 1.4884 | 0.4419 | | 0.5823 | 12.0 | 72 | 2.0101 | 0.3256 | | 0.5823 | 13.0 | 78 | 1.6036 | 0.5349 | | 0.4001 | 14.0 | 84 | 1.6332 | 0.4186 | | 0.2362 | 15.0 | 90 | 2.0095 | 0.4884 | | 0.2362 | 16.0 | 96 | 1.8563 | 0.5581 | | 0.1078 | 17.0 | 102 | 2.1555 | 0.5116 | | 0.1078 | 18.0 | 108 | 2.0019 | 0.5581 | | 0.0769 | 19.0 | 114 | 2.3852 | 0.4884 | | 0.0351 | 20.0 | 120 | 2.4880 | 0.5349 | | 0.0351 | 21.0 | 126 | 2.5950 | 0.4884 | | 0.001 | 22.0 | 132 | 2.5992 | 0.4884 | | 0.001 | 23.0 | 138 | 2.6117 | 0.4884 | | 0.0006 | 24.0 | 144 | 2.6223 | 0.4884 | | 0.0005 | 25.0 | 150 | 2.6443 | 0.4884 | | 0.0005 | 26.0 | 156 | 2.6672 | 0.4884 | | 0.0004 | 27.0 | 162 | 2.6883 | 0.4884 | | 0.0004 | 28.0 | 168 | 2.6994 | 0.4884 | | 0.0003 | 29.0 | 174 | 2.7093 | 0.4884 | | 0.0003 | 30.0 | 180 | 2.7225 | 0.4884 | | 0.0003 | 31.0 | 186 | 2.7350 | 0.4884 | | 0.0003 | 32.0 | 192 | 2.7468 | 0.4651 | | 0.0003 | 33.0 | 198 | 2.7564 | 0.4651 | | 0.0003 | 34.0 | 204 | 2.7644 | 0.4651 | | 0.0002 | 35.0 | 210 | 2.7717 | 0.4651 | | 0.0002 | 36.0 | 216 | 2.7756 | 0.4651 | | 0.0002 | 37.0 | 222 | 2.7805 | 0.4651 | | 0.0002 | 38.0 | 228 | 2.7848 | 0.4651 | | 0.0002 | 39.0 | 234 | 2.7876 | 0.4651 | | 0.0002 | 40.0 | 240 | 2.7903 | 0.4651 | | 0.0002 | 41.0 | 246 | 2.7917 | 0.4651 | | 0.0002 | 42.0 | 252 | 2.7920 | 0.4651 | | 0.0002 | 43.0 | 258 | 2.7920 | 0.4651 | | 0.0002 | 44.0 | 264 | 2.7920 | 0.4651 | | 0.0002 | 45.0 | 270 | 2.7920 | 0.4651 | | 0.0002 | 46.0 | 276 | 2.7920 | 0.4651 | | 0.0002 | 47.0 | 282 | 2.7920 | 0.4651 | | 0.0002 | 48.0 | 288 | 2.7920 | 0.4651 | | 0.0002 | 49.0 | 294 | 2.7920 | 0.4651 | | 0.0002 | 50.0 | 300 | 2.7920 | 0.4651 | ### Framework versions - Transformers 4.35.0 - Pytorch 2.1.0+cu118 - Datasets 2.14.6 - Tokenizers 0.14.1