--- license: apache-2.0 base_model: facebook/deit-base-patch16-224 tags: - generated_from_trainer datasets: - imagefolder metrics: - accuracy model-index: - name: hushem_40x_deit_base_rms_001_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: 0.5581395348837209 --- # hushem_40x_deit_base_rms_001_fold3 This model is a fine-tuned version of [facebook/deit-base-patch16-224](https://huggingface.co/facebook/deit-base-patch16-224) on the imagefolder dataset. It achieves the following results on the evaluation set: - Loss: 4.0356 - Accuracy: 0.5581 ## 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 | |:-------------:|:-----:|:-----:|:---------------:|:--------:| | 1.1943 | 1.0 | 217 | 1.3862 | 0.3488 | | 1.2108 | 2.0 | 434 | 1.3456 | 0.3721 | | 0.8764 | 3.0 | 651 | 1.3683 | 0.4884 | | 0.7995 | 4.0 | 868 | 0.8441 | 0.5814 | | 0.8665 | 5.0 | 1085 | 1.2083 | 0.5116 | | 0.7433 | 6.0 | 1302 | 0.7858 | 0.7209 | | 0.7205 | 7.0 | 1519 | 0.8439 | 0.6744 | | 0.6415 | 8.0 | 1736 | 0.6198 | 0.6512 | | 0.6773 | 9.0 | 1953 | 0.8169 | 0.6744 | | 0.5449 | 10.0 | 2170 | 0.8224 | 0.6512 | | 0.5225 | 11.0 | 2387 | 0.7556 | 0.7209 | | 0.5268 | 12.0 | 2604 | 0.8703 | 0.6744 | | 0.41 | 13.0 | 2821 | 0.7919 | 0.6512 | | 0.4695 | 14.0 | 3038 | 0.9473 | 0.6744 | | 0.3173 | 15.0 | 3255 | 1.2235 | 0.6512 | | 0.3283 | 16.0 | 3472 | 1.3091 | 0.6512 | | 0.3212 | 17.0 | 3689 | 1.0773 | 0.6047 | | 0.3662 | 18.0 | 3906 | 0.9193 | 0.6279 | | 0.3712 | 19.0 | 4123 | 0.9811 | 0.6744 | | 0.3483 | 20.0 | 4340 | 1.5620 | 0.5814 | | 0.2594 | 21.0 | 4557 | 1.8035 | 0.5814 | | 0.3019 | 22.0 | 4774 | 1.3880 | 0.6744 | | 0.2498 | 23.0 | 4991 | 1.6113 | 0.5814 | | 0.2349 | 24.0 | 5208 | 1.2780 | 0.6047 | | 0.1589 | 25.0 | 5425 | 1.6674 | 0.6512 | | 0.2341 | 26.0 | 5642 | 1.6966 | 0.6512 | | 0.1986 | 27.0 | 5859 | 1.4673 | 0.6047 | | 0.1141 | 28.0 | 6076 | 1.6993 | 0.6512 | | 0.1291 | 29.0 | 6293 | 2.0265 | 0.5581 | | 0.1273 | 30.0 | 6510 | 1.8689 | 0.6279 | | 0.0887 | 31.0 | 6727 | 1.4863 | 0.6977 | | 0.101 | 32.0 | 6944 | 2.2258 | 0.6279 | | 0.09 | 33.0 | 7161 | 1.6918 | 0.5814 | | 0.063 | 34.0 | 7378 | 2.4040 | 0.5349 | | 0.0263 | 35.0 | 7595 | 2.2869 | 0.5814 | | 0.0357 | 36.0 | 7812 | 2.0118 | 0.6047 | | 0.033 | 37.0 | 8029 | 2.5046 | 0.6279 | | 0.0417 | 38.0 | 8246 | 2.0462 | 0.6512 | | 0.0049 | 39.0 | 8463 | 3.1349 | 0.5814 | | 0.0034 | 40.0 | 8680 | 2.4922 | 0.6279 | | 0.0115 | 41.0 | 8897 | 2.7021 | 0.5581 | | 0.0248 | 42.0 | 9114 | 3.1496 | 0.5116 | | 0.0078 | 43.0 | 9331 | 2.6336 | 0.6279 | | 0.0022 | 44.0 | 9548 | 3.2458 | 0.5349 | | 0.0015 | 45.0 | 9765 | 3.3966 | 0.5349 | | 0.0031 | 46.0 | 9982 | 4.1353 | 0.5116 | | 0.0 | 47.0 | 10199 | 3.5481 | 0.5814 | | 0.0002 | 48.0 | 10416 | 3.8712 | 0.5349 | | 0.0 | 49.0 | 10633 | 4.0305 | 0.5581 | | 0.0 | 50.0 | 10850 | 4.0356 | 0.5581 | ### Framework versions - Transformers 4.32.1 - Pytorch 2.1.0+cu121 - Datasets 2.12.0 - Tokenizers 0.13.2