--- license: apache-2.0 base_model: facebook/deit-tiny-patch16-224 tags: - generated_from_trainer datasets: - imagefolder metrics: - accuracy model-index: - name: hushem_5x_deit_tiny_adamax_00001_fold2 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: 0.5777777777777777 --- # hushem_5x_deit_tiny_adamax_00001_fold2 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: 1.6641 - Accuracy: 0.5778 ## 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: 1e-05 - 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 | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 1.3635 | 1.0 | 27 | 1.4130 | 0.2667 | | 1.0042 | 2.0 | 54 | 1.4711 | 0.2222 | | 0.8161 | 3.0 | 81 | 1.3782 | 0.2667 | | 0.718 | 4.0 | 108 | 1.4066 | 0.3778 | | 0.5558 | 5.0 | 135 | 1.3265 | 0.4444 | | 0.4509 | 6.0 | 162 | 1.2556 | 0.5111 | | 0.3768 | 7.0 | 189 | 1.2546 | 0.5333 | | 0.3011 | 8.0 | 216 | 1.2575 | 0.5333 | | 0.2105 | 9.0 | 243 | 1.2766 | 0.5111 | | 0.1649 | 10.0 | 270 | 1.2667 | 0.5333 | | 0.1073 | 11.0 | 297 | 1.2756 | 0.5333 | | 0.09 | 12.0 | 324 | 1.2325 | 0.5333 | | 0.0621 | 13.0 | 351 | 1.3118 | 0.5111 | | 0.0505 | 14.0 | 378 | 1.2588 | 0.5111 | | 0.0376 | 15.0 | 405 | 1.2895 | 0.5111 | | 0.0263 | 16.0 | 432 | 1.3784 | 0.5333 | | 0.0213 | 17.0 | 459 | 1.3797 | 0.5556 | | 0.0147 | 18.0 | 486 | 1.3696 | 0.5556 | | 0.0099 | 19.0 | 513 | 1.4119 | 0.5778 | | 0.0067 | 20.0 | 540 | 1.4307 | 0.5333 | | 0.0051 | 21.0 | 567 | 1.4626 | 0.5556 | | 0.0036 | 22.0 | 594 | 1.4677 | 0.5778 | | 0.0029 | 23.0 | 621 | 1.5080 | 0.5778 | | 0.0025 | 24.0 | 648 | 1.5082 | 0.5778 | | 0.002 | 25.0 | 675 | 1.5166 | 0.5556 | | 0.0019 | 26.0 | 702 | 1.5536 | 0.5556 | | 0.0018 | 27.0 | 729 | 1.5513 | 0.5556 | | 0.0016 | 28.0 | 756 | 1.5675 | 0.5556 | | 0.0015 | 29.0 | 783 | 1.5750 | 0.5778 | | 0.0014 | 30.0 | 810 | 1.5873 | 0.5778 | | 0.0012 | 31.0 | 837 | 1.5953 | 0.6 | | 0.0013 | 32.0 | 864 | 1.6002 | 0.6 | | 0.001 | 33.0 | 891 | 1.6127 | 0.6 | | 0.0011 | 34.0 | 918 | 1.6173 | 0.6 | | 0.0009 | 35.0 | 945 | 1.6219 | 0.5778 | | 0.001 | 36.0 | 972 | 1.6280 | 0.6 | | 0.0009 | 37.0 | 999 | 1.6357 | 0.6 | | 0.0009 | 38.0 | 1026 | 1.6422 | 0.6 | | 0.0009 | 39.0 | 1053 | 1.6437 | 0.6 | | 0.0008 | 40.0 | 1080 | 1.6487 | 0.6 | | 0.0008 | 41.0 | 1107 | 1.6556 | 0.5778 | | 0.0007 | 42.0 | 1134 | 1.6560 | 0.6 | | 0.0008 | 43.0 | 1161 | 1.6560 | 0.6 | | 0.0007 | 44.0 | 1188 | 1.6595 | 0.6 | | 0.0007 | 45.0 | 1215 | 1.6630 | 0.5778 | | 0.0007 | 46.0 | 1242 | 1.6626 | 0.6 | | 0.0007 | 47.0 | 1269 | 1.6639 | 0.5778 | | 0.0008 | 48.0 | 1296 | 1.6641 | 0.5778 | | 0.0008 | 49.0 | 1323 | 1.6641 | 0.5778 | | 0.0007 | 50.0 | 1350 | 1.6641 | 0.5778 | ### Framework versions - Transformers 4.35.2 - Pytorch 2.1.0+cu118 - Datasets 2.15.0 - Tokenizers 0.15.0