--- license: apache-2.0 base_model: microsoft/beit-base-patch16-224 tags: - generated_from_trainer datasets: - imagefolder metrics: - accuracy model-index: - name: hushem_5x_beit_base_rms_0001_fold1 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: 0.35555555555555557 --- # hushem_5x_beit_base_rms_0001_fold1 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: 3.6811 - Accuracy: 0.3556 ## 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 | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 1.4287 | 1.0 | 27 | 1.3926 | 0.2222 | | 1.3907 | 2.0 | 54 | 1.3975 | 0.2667 | | 1.358 | 3.0 | 81 | 1.5093 | 0.2444 | | 1.3416 | 4.0 | 108 | 1.5118 | 0.2444 | | 1.2056 | 5.0 | 135 | 1.4928 | 0.2444 | | 1.1299 | 6.0 | 162 | 1.6562 | 0.2222 | | 1.1641 | 7.0 | 189 | 1.5947 | 0.2444 | | 1.1473 | 8.0 | 216 | 1.5964 | 0.2444 | | 1.1298 | 9.0 | 243 | 1.7663 | 0.2444 | | 1.1045 | 10.0 | 270 | 1.6309 | 0.3778 | | 0.8985 | 11.0 | 297 | 1.6908 | 0.4 | | 0.7744 | 12.0 | 324 | 1.3949 | 0.3556 | | 0.7617 | 13.0 | 351 | 1.4646 | 0.3778 | | 0.6843 | 14.0 | 378 | 1.5910 | 0.3778 | | 0.6647 | 15.0 | 405 | 1.8050 | 0.4 | | 0.6363 | 16.0 | 432 | 1.7016 | 0.3333 | | 0.6362 | 17.0 | 459 | 1.8539 | 0.3778 | | 0.6858 | 18.0 | 486 | 1.8678 | 0.3556 | | 0.7039 | 19.0 | 513 | 1.5776 | 0.3556 | | 0.6292 | 20.0 | 540 | 1.8552 | 0.3111 | | 0.4567 | 21.0 | 567 | 1.7854 | 0.3556 | | 0.5954 | 22.0 | 594 | 2.4822 | 0.3556 | | 0.5737 | 23.0 | 621 | 2.0564 | 0.4 | | 0.4941 | 24.0 | 648 | 1.9451 | 0.3111 | | 0.523 | 25.0 | 675 | 2.0359 | 0.3778 | | 0.5221 | 26.0 | 702 | 2.1184 | 0.4 | | 0.4589 | 27.0 | 729 | 2.0471 | 0.3556 | | 0.4473 | 28.0 | 756 | 2.5353 | 0.3556 | | 0.4328 | 29.0 | 783 | 2.7479 | 0.3556 | | 0.4259 | 30.0 | 810 | 2.2239 | 0.3778 | | 0.3698 | 31.0 | 837 | 2.5363 | 0.3556 | | 0.3577 | 32.0 | 864 | 2.5264 | 0.3556 | | 0.3882 | 33.0 | 891 | 2.2649 | 0.3333 | | 0.3526 | 34.0 | 918 | 2.6438 | 0.3556 | | 0.2747 | 35.0 | 945 | 2.3584 | 0.3778 | | 0.2842 | 36.0 | 972 | 2.8515 | 0.3556 | | 0.2603 | 37.0 | 999 | 2.3416 | 0.3778 | | 0.2268 | 38.0 | 1026 | 2.7485 | 0.3778 | | 0.2 | 39.0 | 1053 | 3.3636 | 0.3333 | | 0.2049 | 40.0 | 1080 | 3.1692 | 0.3333 | | 0.1369 | 41.0 | 1107 | 3.3885 | 0.3556 | | 0.1813 | 42.0 | 1134 | 3.3020 | 0.3333 | | 0.1518 | 43.0 | 1161 | 2.8618 | 0.4 | | 0.0986 | 44.0 | 1188 | 3.2902 | 0.3778 | | 0.131 | 45.0 | 1215 | 3.3898 | 0.3333 | | 0.0809 | 46.0 | 1242 | 3.5629 | 0.3333 | | 0.048 | 47.0 | 1269 | 3.7516 | 0.3333 | | 0.038 | 48.0 | 1296 | 3.6814 | 0.3556 | | 0.0465 | 49.0 | 1323 | 3.6811 | 0.3556 | | 0.0644 | 50.0 | 1350 | 3.6811 | 0.3556 | ### Framework versions - Transformers 4.35.2 - Pytorch 2.1.0+cu118 - Datasets 2.15.0 - Tokenizers 0.15.0