--- license: apache-2.0 base_model: facebook/deit-base-distilled-patch16-224 tags: - generated_from_trainer datasets: - imagefolder metrics: - accuracy model-index: - name: deit-base-distilled-patch16-224-65-fold5 results: - task: name: Image Classification type: image-classification dataset: name: imagefolder type: imagefolder config: default split: train args: default metrics: - name: Accuracy type: accuracy value: 0.8732394366197183 --- # deit-base-distilled-patch16-224-65-fold5 This model is a fine-tuned version of [facebook/deit-base-distilled-patch16-224](https://huggingface.co/facebook/deit-base-distilled-patch16-224) on the imagefolder dataset. It achieves the following results on the evaluation set: - Loss: 0.5156 - Accuracy: 0.8732 ## 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: 5e-05 - train_batch_size: 32 - eval_batch_size: 32 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 128 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 100 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-------:|:----:|:---------------:|:--------:| | No log | 0.9231 | 3 | 0.7425 | 0.4930 | | No log | 1.8462 | 6 | 0.7193 | 0.5634 | | No log | 2.7692 | 9 | 0.6808 | 0.5915 | | 0.7309 | 4.0 | 13 | 0.6253 | 0.5915 | | 0.7309 | 4.9231 | 16 | 0.6022 | 0.6761 | | 0.7309 | 5.8462 | 19 | 0.5589 | 0.6479 | | 0.6449 | 6.7692 | 22 | 0.5559 | 0.7183 | | 0.6449 | 8.0 | 26 | 0.4910 | 0.7183 | | 0.6449 | 8.9231 | 29 | 0.4996 | 0.7606 | | 0.5494 | 9.8462 | 32 | 0.4903 | 0.7324 | | 0.5494 | 10.7692 | 35 | 0.7331 | 0.6620 | | 0.5494 | 12.0 | 39 | 0.5053 | 0.6901 | | 0.4793 | 12.9231 | 42 | 0.4781 | 0.7324 | | 0.4793 | 13.8462 | 45 | 0.4997 | 0.7465 | | 0.4793 | 14.7692 | 48 | 0.5197 | 0.7465 | | 0.4327 | 16.0 | 52 | 0.5339 | 0.7606 | | 0.4327 | 16.9231 | 55 | 0.4475 | 0.7606 | | 0.4327 | 17.8462 | 58 | 0.4808 | 0.7887 | | 0.3747 | 18.7692 | 61 | 0.4868 | 0.7465 | | 0.3747 | 20.0 | 65 | 0.6206 | 0.7042 | | 0.3747 | 20.9231 | 68 | 0.5271 | 0.7324 | | 0.3474 | 21.8462 | 71 | 0.5227 | 0.6901 | | 0.3474 | 22.7692 | 74 | 0.5078 | 0.7465 | | 0.3474 | 24.0 | 78 | 0.5842 | 0.6901 | | 0.267 | 24.9231 | 81 | 0.6015 | 0.7183 | | 0.267 | 25.8462 | 84 | 0.6533 | 0.7606 | | 0.267 | 26.7692 | 87 | 0.5764 | 0.7324 | | 0.2333 | 28.0 | 91 | 0.4862 | 0.8028 | | 0.2333 | 28.9231 | 94 | 0.6233 | 0.7183 | | 0.2333 | 29.8462 | 97 | 0.7549 | 0.7465 | | 0.2635 | 30.7692 | 100 | 0.4890 | 0.8028 | | 0.2635 | 32.0 | 104 | 0.5616 | 0.8028 | | 0.2635 | 32.9231 | 107 | 0.5501 | 0.7606 | | 0.192 | 33.8462 | 110 | 0.4845 | 0.8169 | | 0.192 | 34.7692 | 113 | 0.5116 | 0.7887 | | 0.192 | 36.0 | 117 | 0.5017 | 0.8169 | | 0.1763 | 36.9231 | 120 | 0.4798 | 0.7887 | | 0.1763 | 37.8462 | 123 | 0.5328 | 0.7746 | | 0.1763 | 38.7692 | 126 | 0.6393 | 0.7606 | | 0.172 | 40.0 | 130 | 0.5481 | 0.7887 | | 0.172 | 40.9231 | 133 | 0.5867 | 0.7887 | | 0.172 | 41.8462 | 136 | 0.9223 | 0.7042 | | 0.172 | 42.7692 | 139 | 0.6262 | 0.8028 | | 0.1832 | 44.0 | 143 | 0.6091 | 0.7746 | | 0.1832 | 44.9231 | 146 | 0.5837 | 0.7606 | | 0.1832 | 45.8462 | 149 | 0.5465 | 0.7606 | | 0.1641 | 46.7692 | 152 | 0.6745 | 0.7746 | | 0.1641 | 48.0 | 156 | 0.5398 | 0.7887 | | 0.1641 | 48.9231 | 159 | 0.5387 | 0.8169 | | 0.1366 | 49.8462 | 162 | 0.5737 | 0.8028 | | 0.1366 | 50.7692 | 165 | 0.5255 | 0.8310 | | 0.1366 | 52.0 | 169 | 0.6486 | 0.7887 | | 0.149 | 52.9231 | 172 | 0.5404 | 0.8169 | | 0.149 | 53.8462 | 175 | 0.5655 | 0.8169 | | 0.149 | 54.7692 | 178 | 0.6121 | 0.8028 | | 0.1196 | 56.0 | 182 | 0.6182 | 0.8310 | | 0.1196 | 56.9231 | 185 | 0.6175 | 0.8028 | | 0.1196 | 57.8462 | 188 | 0.5921 | 0.8310 | | 0.1202 | 58.7692 | 191 | 0.5953 | 0.8169 | | 0.1202 | 60.0 | 195 | 0.6065 | 0.8028 | | 0.1202 | 60.9231 | 198 | 0.5448 | 0.8310 | | 0.1289 | 61.8462 | 201 | 0.5258 | 0.8451 | | 0.1289 | 62.7692 | 204 | 0.5440 | 0.8310 | | 0.1289 | 64.0 | 208 | 0.6082 | 0.8169 | | 0.1262 | 64.9231 | 211 | 0.6358 | 0.8169 | | 0.1262 | 65.8462 | 214 | 0.5982 | 0.8169 | | 0.1262 | 66.7692 | 217 | 0.5850 | 0.8451 | | 0.124 | 68.0 | 221 | 0.5733 | 0.8169 | | 0.124 | 68.9231 | 224 | 0.5631 | 0.8028 | | 0.124 | 69.8462 | 227 | 0.5375 | 0.8310 | | 0.1208 | 70.7692 | 230 | 0.5158 | 0.8169 | | 0.1208 | 72.0 | 234 | 0.5431 | 0.8169 | | 0.1208 | 72.9231 | 237 | 0.5099 | 0.8451 | | 0.1126 | 73.8462 | 240 | 0.5803 | 0.7887 | | 0.1126 | 74.7692 | 243 | 0.5416 | 0.8028 | | 0.1126 | 76.0 | 247 | 0.5835 | 0.8451 | | 0.1089 | 76.9231 | 250 | 0.5923 | 0.8310 | | 0.1089 | 77.8462 | 253 | 0.5228 | 0.8310 | | 0.1089 | 78.7692 | 256 | 0.5467 | 0.8310 | | 0.0965 | 80.0 | 260 | 0.5156 | 0.8732 | | 0.0965 | 80.9231 | 263 | 0.5082 | 0.8451 | | 0.0965 | 81.8462 | 266 | 0.5071 | 0.8451 | | 0.0965 | 82.7692 | 269 | 0.5070 | 0.8592 | | 0.0947 | 84.0 | 273 | 0.5268 | 0.8592 | | 0.0947 | 84.9231 | 276 | 0.5283 | 0.8592 | | 0.0947 | 85.8462 | 279 | 0.5261 | 0.8451 | | 0.0751 | 86.7692 | 282 | 0.5286 | 0.8310 | | 0.0751 | 88.0 | 286 | 0.5415 | 0.8310 | | 0.0751 | 88.9231 | 289 | 0.5511 | 0.8310 | | 0.0912 | 89.8462 | 292 | 0.5542 | 0.8310 | | 0.0912 | 90.7692 | 295 | 0.5464 | 0.8310 | | 0.0912 | 92.0 | 299 | 0.5410 | 0.8310 | | 0.104 | 92.3077 | 300 | 0.5407 | 0.8310 | ### Framework versions - Transformers 4.41.0 - Pytorch 2.3.0+cu121 - Datasets 2.19.1 - Tokenizers 0.19.1