--- 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_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: 0.4523809523809524 --- # hushem_1x_beit_base_rms_001_fold4 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: 1.1403 - Accuracy: 0.4524 ## 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 | |:-------------:|:-----:|:----:|:---------------:|:--------:| | No log | 1.0 | 6 | 2.4924 | 0.2619 | | 4.2258 | 2.0 | 12 | 2.2430 | 0.2381 | | 4.2258 | 3.0 | 18 | 1.7745 | 0.2619 | | 1.6665 | 4.0 | 24 | 1.4260 | 0.2381 | | 1.4856 | 5.0 | 30 | 1.3866 | 0.2619 | | 1.4856 | 6.0 | 36 | 1.4278 | 0.2619 | | 1.4454 | 7.0 | 42 | 1.4079 | 0.2381 | | 1.4454 | 8.0 | 48 | 1.4268 | 0.2381 | | 1.408 | 9.0 | 54 | 1.3464 | 0.3095 | | 1.4164 | 10.0 | 60 | 1.3818 | 0.2619 | | 1.4164 | 11.0 | 66 | 1.3229 | 0.4048 | | 1.3723 | 12.0 | 72 | 1.2005 | 0.4286 | | 1.3723 | 13.0 | 78 | 1.3168 | 0.3333 | | 1.3294 | 14.0 | 84 | 1.3652 | 0.2857 | | 1.3514 | 15.0 | 90 | 1.2992 | 0.3095 | | 1.3514 | 16.0 | 96 | 1.2709 | 0.3095 | | 1.2833 | 17.0 | 102 | 1.0901 | 0.5714 | | 1.2833 | 18.0 | 108 | 1.2138 | 0.4286 | | 1.2546 | 19.0 | 114 | 1.2470 | 0.3810 | | 1.2893 | 20.0 | 120 | 1.2665 | 0.4048 | | 1.2893 | 21.0 | 126 | 1.1295 | 0.5476 | | 1.2456 | 22.0 | 132 | 1.1935 | 0.4762 | | 1.2456 | 23.0 | 138 | 1.1859 | 0.2857 | | 1.2107 | 24.0 | 144 | 1.2333 | 0.3095 | | 1.211 | 25.0 | 150 | 1.1492 | 0.5 | | 1.211 | 26.0 | 156 | 1.1293 | 0.3810 | | 1.2139 | 27.0 | 162 | 1.1301 | 0.4048 | | 1.2139 | 28.0 | 168 | 1.2567 | 0.2857 | | 1.1599 | 29.0 | 174 | 1.1146 | 0.4524 | | 1.1826 | 30.0 | 180 | 1.1895 | 0.4524 | | 1.1826 | 31.0 | 186 | 1.1803 | 0.4286 | | 1.1665 | 32.0 | 192 | 1.1331 | 0.4524 | | 1.1665 | 33.0 | 198 | 1.2501 | 0.2619 | | 1.1881 | 34.0 | 204 | 1.1720 | 0.3571 | | 1.1428 | 35.0 | 210 | 1.1303 | 0.3810 | | 1.1428 | 36.0 | 216 | 1.0467 | 0.4524 | | 1.1325 | 37.0 | 222 | 1.1840 | 0.3095 | | 1.1325 | 38.0 | 228 | 1.1537 | 0.3571 | | 1.0868 | 39.0 | 234 | 1.1576 | 0.3571 | | 1.0845 | 40.0 | 240 | 1.1445 | 0.4524 | | 1.0845 | 41.0 | 246 | 1.1472 | 0.4524 | | 1.0808 | 42.0 | 252 | 1.1403 | 0.4524 | | 1.0808 | 43.0 | 258 | 1.1403 | 0.4524 | | 1.0575 | 44.0 | 264 | 1.1403 | 0.4524 | | 1.0837 | 45.0 | 270 | 1.1403 | 0.4524 | | 1.0837 | 46.0 | 276 | 1.1403 | 0.4524 | | 1.0819 | 47.0 | 282 | 1.1403 | 0.4524 | | 1.0819 | 48.0 | 288 | 1.1403 | 0.4524 | | 1.0729 | 49.0 | 294 | 1.1403 | 0.4524 | | 1.0942 | 50.0 | 300 | 1.1403 | 0.4524 | ### Framework versions - Transformers 4.35.2 - Pytorch 2.1.0+cu118 - Datasets 2.15.0 - Tokenizers 0.15.0