--- license: apache-2.0 base_model: microsoft/beit-base-patch16-224 tags: - generated_from_trainer datasets: - imagefolder metrics: - accuracy model-index: - name: hushem_1x_beit_base_rms_0001_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: 0.6341463414634146 --- # hushem_1x_beit_base_rms_0001_fold5 This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on the imagefolder dataset. It achieves the following results on the evaluation set: - Loss: 1.7755 - Accuracy: 0.6341 ## 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 | 1.4246 | 0.2683 | | 1.7592 | 2.0 | 12 | 1.3851 | 0.2683 | | 1.7592 | 3.0 | 18 | 1.3804 | 0.2439 | | 1.4204 | 4.0 | 24 | 1.4010 | 0.2683 | | 1.3988 | 5.0 | 30 | 1.3776 | 0.2439 | | 1.3988 | 6.0 | 36 | 1.3196 | 0.3171 | | 1.3741 | 7.0 | 42 | 1.2653 | 0.3659 | | 1.3741 | 8.0 | 48 | 1.3284 | 0.3902 | | 1.3098 | 9.0 | 54 | 1.2504 | 0.4146 | | 1.2944 | 10.0 | 60 | 1.2840 | 0.2927 | | 1.2944 | 11.0 | 66 | 1.3400 | 0.3902 | | 1.3252 | 12.0 | 72 | 1.2889 | 0.3659 | | 1.3252 | 13.0 | 78 | 1.1547 | 0.4634 | | 1.2379 | 14.0 | 84 | 1.1463 | 0.3415 | | 1.1874 | 15.0 | 90 | 1.1230 | 0.5122 | | 1.1874 | 16.0 | 96 | 4.2155 | 0.3902 | | 1.374 | 17.0 | 102 | 0.9374 | 0.6098 | | 1.374 | 18.0 | 108 | 0.9748 | 0.6341 | | 1.0858 | 19.0 | 114 | 0.9498 | 0.5366 | | 0.9929 | 20.0 | 120 | 1.0346 | 0.4878 | | 0.9929 | 21.0 | 126 | 1.2495 | 0.4634 | | 0.9078 | 22.0 | 132 | 1.0142 | 0.5366 | | 0.9078 | 23.0 | 138 | 0.9571 | 0.6341 | | 0.8585 | 24.0 | 144 | 0.7607 | 0.7073 | | 0.9707 | 25.0 | 150 | 0.9749 | 0.4878 | | 0.9707 | 26.0 | 156 | 1.2739 | 0.6341 | | 0.8033 | 27.0 | 162 | 0.7831 | 0.6585 | | 0.8033 | 28.0 | 168 | 0.9134 | 0.5610 | | 0.8358 | 29.0 | 174 | 0.9940 | 0.6098 | | 0.7373 | 30.0 | 180 | 0.9448 | 0.6341 | | 0.7373 | 31.0 | 186 | 1.0065 | 0.6341 | | 0.693 | 32.0 | 192 | 1.2616 | 0.6585 | | 0.693 | 33.0 | 198 | 1.0510 | 0.6098 | | 0.6403 | 34.0 | 204 | 1.2334 | 0.6341 | | 0.6359 | 35.0 | 210 | 1.2865 | 0.6341 | | 0.6359 | 36.0 | 216 | 1.2812 | 0.6098 | | 0.5717 | 37.0 | 222 | 1.4784 | 0.6341 | | 0.5717 | 38.0 | 228 | 1.6714 | 0.6341 | | 0.5294 | 39.0 | 234 | 1.7953 | 0.5854 | | 0.5043 | 40.0 | 240 | 1.6946 | 0.6341 | | 0.5043 | 41.0 | 246 | 1.7411 | 0.6585 | | 0.4865 | 42.0 | 252 | 1.7755 | 0.6341 | | 0.4865 | 43.0 | 258 | 1.7755 | 0.6341 | | 0.4648 | 44.0 | 264 | 1.7755 | 0.6341 | | 0.4795 | 45.0 | 270 | 1.7755 | 0.6341 | | 0.4795 | 46.0 | 276 | 1.7755 | 0.6341 | | 0.4544 | 47.0 | 282 | 1.7755 | 0.6341 | | 0.4544 | 48.0 | 288 | 1.7755 | 0.6341 | | 0.519 | 49.0 | 294 | 1.7755 | 0.6341 | | 0.4907 | 50.0 | 300 | 1.7755 | 0.6341 | ### Framework versions - Transformers 4.35.2 - Pytorch 2.1.0+cu118 - Datasets 2.15.0 - Tokenizers 0.15.0