--- license: apache-2.0 base_model: facebook/deit-tiny-patch16-224 tags: - generated_from_trainer datasets: - imagefolder metrics: - accuracy model-index: - name: hushem_1x_deit_tiny_rms_lr0001_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: 0.7619047619047619 --- # hushem_1x_deit_tiny_rms_lr0001_fold4 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: 1.2563 - Accuracy: 0.7619 ## 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 | 1.5375 | 0.2619 | | 2.1724 | 2.0 | 12 | 2.0732 | 0.2381 | | 2.1724 | 3.0 | 18 | 1.4131 | 0.2619 | | 1.6782 | 4.0 | 24 | 1.3425 | 0.4524 | | 1.4417 | 5.0 | 30 | 1.3458 | 0.2857 | | 1.4417 | 6.0 | 36 | 1.2594 | 0.6429 | | 1.3676 | 7.0 | 42 | 1.1740 | 0.4762 | | 1.3676 | 8.0 | 48 | 1.2511 | 0.3571 | | 1.2512 | 9.0 | 54 | 0.8438 | 0.6190 | | 0.8279 | 10.0 | 60 | 1.0096 | 0.5 | | 0.8279 | 11.0 | 66 | 0.7631 | 0.6667 | | 0.5322 | 12.0 | 72 | 0.6526 | 0.7857 | | 0.5322 | 13.0 | 78 | 0.6963 | 0.7143 | | 0.257 | 14.0 | 84 | 0.7429 | 0.7619 | | 0.1198 | 15.0 | 90 | 0.9632 | 0.6905 | | 0.1198 | 16.0 | 96 | 1.2325 | 0.7143 | | 0.0178 | 17.0 | 102 | 1.2090 | 0.7381 | | 0.0178 | 18.0 | 108 | 1.1054 | 0.7619 | | 0.0016 | 19.0 | 114 | 1.2184 | 0.7143 | | 0.0009 | 20.0 | 120 | 1.1716 | 0.7619 | | 0.0009 | 21.0 | 126 | 1.1784 | 0.7619 | | 0.0004 | 22.0 | 132 | 1.1866 | 0.7619 | | 0.0004 | 23.0 | 138 | 1.1935 | 0.7619 | | 0.0003 | 24.0 | 144 | 1.1995 | 0.7619 | | 0.0003 | 25.0 | 150 | 1.2046 | 0.7619 | | 0.0003 | 26.0 | 156 | 1.2111 | 0.7619 | | 0.0003 | 27.0 | 162 | 1.2169 | 0.7619 | | 0.0003 | 28.0 | 168 | 1.2218 | 0.7619 | | 0.0002 | 29.0 | 174 | 1.2261 | 0.7619 | | 0.0002 | 30.0 | 180 | 1.2318 | 0.7619 | | 0.0002 | 31.0 | 186 | 1.2354 | 0.7619 | | 0.0002 | 32.0 | 192 | 1.2392 | 0.7619 | | 0.0002 | 33.0 | 198 | 1.2423 | 0.7619 | | 0.0002 | 34.0 | 204 | 1.2453 | 0.7619 | | 0.0002 | 35.0 | 210 | 1.2477 | 0.7619 | | 0.0002 | 36.0 | 216 | 1.2499 | 0.7619 | | 0.0002 | 37.0 | 222 | 1.2519 | 0.7619 | | 0.0002 | 38.0 | 228 | 1.2534 | 0.7619 | | 0.0002 | 39.0 | 234 | 1.2547 | 0.7619 | | 0.0002 | 40.0 | 240 | 1.2556 | 0.7619 | | 0.0002 | 41.0 | 246 | 1.2562 | 0.7619 | | 0.0002 | 42.0 | 252 | 1.2563 | 0.7619 | | 0.0002 | 43.0 | 258 | 1.2563 | 0.7619 | | 0.0002 | 44.0 | 264 | 1.2563 | 0.7619 | | 0.0002 | 45.0 | 270 | 1.2563 | 0.7619 | | 0.0002 | 46.0 | 276 | 1.2563 | 0.7619 | | 0.0002 | 47.0 | 282 | 1.2563 | 0.7619 | | 0.0002 | 48.0 | 288 | 1.2563 | 0.7619 | | 0.0002 | 49.0 | 294 | 1.2563 | 0.7619 | | 0.0002 | 50.0 | 300 | 1.2563 | 0.7619 | ### Framework versions - Transformers 4.35.0 - Pytorch 2.1.0+cu118 - Datasets 2.14.6 - Tokenizers 0.14.1