--- 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-fold4 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: 0.8450704225352113 --- # deit-base-distilled-patch16-224-65-fold4 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: 0.5367 - Accuracy: 0.8451 ## 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 | 0.7145 | 0.5211 | | No log | 1.8462 | 6 | 0.7082 | 0.5070 | | No log | 2.7692 | 9 | 0.6889 | 0.6056 | | 0.6878 | 4.0 | 13 | 0.6703 | 0.6620 | | 0.6878 | 4.9231 | 16 | 0.6556 | 0.6761 | | 0.6878 | 5.8462 | 19 | 0.6430 | 0.6620 | | 0.6203 | 6.7692 | 22 | 0.6250 | 0.6761 | | 0.6203 | 8.0 | 26 | 0.7464 | 0.6197 | | 0.6203 | 8.9231 | 29 | 0.6647 | 0.6056 | | 0.5703 | 9.8462 | 32 | 0.6097 | 0.7042 | | 0.5703 | 10.7692 | 35 | 0.6261 | 0.6620 | | 0.5703 | 12.0 | 39 | 0.5926 | 0.7042 | | 0.5281 | 12.9231 | 42 | 0.5370 | 0.7465 | | 0.5281 | 13.8462 | 45 | 0.5638 | 0.7465 | | 0.5281 | 14.7692 | 48 | 0.7175 | 0.6056 | | 0.4616 | 16.0 | 52 | 0.8917 | 0.5775 | | 0.4616 | 16.9231 | 55 | 0.6761 | 0.6761 | | 0.4616 | 17.8462 | 58 | 0.5606 | 0.7324 | | 0.4943 | 18.7692 | 61 | 0.6963 | 0.6338 | | 0.4943 | 20.0 | 65 | 0.6462 | 0.6620 | | 0.4943 | 20.9231 | 68 | 0.6246 | 0.7183 | | 0.4058 | 21.8462 | 71 | 0.7336 | 0.6620 | | 0.4058 | 22.7692 | 74 | 0.6270 | 0.7324 | | 0.4058 | 24.0 | 78 | 0.6097 | 0.7183 | | 0.3577 | 24.9231 | 81 | 0.6700 | 0.7606 | | 0.3577 | 25.8462 | 84 | 0.6676 | 0.7183 | | 0.3577 | 26.7692 | 87 | 0.5475 | 0.7887 | | 0.2988 | 28.0 | 91 | 0.5383 | 0.8028 | | 0.2988 | 28.9231 | 94 | 0.5534 | 0.7183 | | 0.2988 | 29.8462 | 97 | 0.5842 | 0.8028 | | 0.2595 | 30.7692 | 100 | 0.5965 | 0.7887 | | 0.2595 | 32.0 | 104 | 0.6220 | 0.7606 | | 0.2595 | 32.9231 | 107 | 0.6027 | 0.7606 | | 0.2422 | 33.8462 | 110 | 0.6369 | 0.7183 | | 0.2422 | 34.7692 | 113 | 0.6033 | 0.7746 | | 0.2422 | 36.0 | 117 | 0.6912 | 0.7324 | | 0.1927 | 36.9231 | 120 | 0.6582 | 0.7887 | | 0.1927 | 37.8462 | 123 | 0.6320 | 0.7746 | | 0.1927 | 38.7692 | 126 | 0.7532 | 0.7606 | | 0.2399 | 40.0 | 130 | 0.7909 | 0.7606 | | 0.2399 | 40.9231 | 133 | 0.6808 | 0.7465 | | 0.2399 | 41.8462 | 136 | 0.5816 | 0.7887 | | 0.2399 | 42.7692 | 139 | 0.5474 | 0.7887 | | 0.2218 | 44.0 | 143 | 0.6310 | 0.7042 | | 0.2218 | 44.9231 | 146 | 0.6453 | 0.8028 | | 0.2218 | 45.8462 | 149 | 0.6170 | 0.7887 | | 0.1817 | 46.7692 | 152 | 0.6034 | 0.7887 | | 0.1817 | 48.0 | 156 | 0.6350 | 0.8310 | | 0.1817 | 48.9231 | 159 | 0.6027 | 0.7887 | | 0.1483 | 49.8462 | 162 | 0.5599 | 0.8028 | | 0.1483 | 50.7692 | 165 | 0.5817 | 0.8310 | | 0.1483 | 52.0 | 169 | 0.6086 | 0.7746 | | 0.1668 | 52.9231 | 172 | 0.5744 | 0.8169 | | 0.1668 | 53.8462 | 175 | 0.6059 | 0.7887 | | 0.1668 | 54.7692 | 178 | 0.6455 | 0.7887 | | 0.1372 | 56.0 | 182 | 0.5367 | 0.8451 | | 0.1372 | 56.9231 | 185 | 0.5615 | 0.8169 | | 0.1372 | 57.8462 | 188 | 0.6378 | 0.8028 | | 0.1485 | 58.7692 | 191 | 0.5687 | 0.8169 | | 0.1485 | 60.0 | 195 | 0.4897 | 0.8169 | | 0.1485 | 60.9231 | 198 | 0.4384 | 0.8451 | | 0.1426 | 61.8462 | 201 | 0.5087 | 0.7887 | | 0.1426 | 62.7692 | 204 | 0.4757 | 0.8169 | | 0.1426 | 64.0 | 208 | 0.4373 | 0.8169 | | 0.1333 | 64.9231 | 211 | 0.4512 | 0.8169 | | 0.1333 | 65.8462 | 214 | 0.4619 | 0.7887 | | 0.1333 | 66.7692 | 217 | 0.5520 | 0.8028 | | 0.1306 | 68.0 | 221 | 0.5161 | 0.7887 | | 0.1306 | 68.9231 | 224 | 0.5180 | 0.7606 | | 0.1306 | 69.8462 | 227 | 0.5778 | 0.8028 | | 0.1327 | 70.7692 | 230 | 0.5933 | 0.8028 | | 0.1327 | 72.0 | 234 | 0.5222 | 0.7887 | | 0.1327 | 72.9231 | 237 | 0.5104 | 0.8169 | | 0.1171 | 73.8462 | 240 | 0.5024 | 0.8169 | | 0.1171 | 74.7692 | 243 | 0.5060 | 0.8028 | | 0.1171 | 76.0 | 247 | 0.5267 | 0.7746 | | 0.1227 | 76.9231 | 250 | 0.4775 | 0.8169 | | 0.1227 | 77.8462 | 253 | 0.5020 | 0.8169 | | 0.1227 | 78.7692 | 256 | 0.5243 | 0.7606 | | 0.1304 | 80.0 | 260 | 0.6195 | 0.7887 | | 0.1304 | 80.9231 | 263 | 0.5740 | 0.7606 | | 0.1304 | 81.8462 | 266 | 0.5652 | 0.8169 | | 0.1304 | 82.7692 | 269 | 0.5750 | 0.8169 | | 0.1152 | 84.0 | 273 | 0.5829 | 0.7887 | | 0.1152 | 84.9231 | 276 | 0.5854 | 0.7887 | | 0.1152 | 85.8462 | 279 | 0.5854 | 0.7887 | | 0.1069 | 86.7692 | 282 | 0.5826 | 0.8028 | | 0.1069 | 88.0 | 286 | 0.5839 | 0.7887 | | 0.1069 | 88.9231 | 289 | 0.5792 | 0.8169 | | 0.122 | 89.8462 | 292 | 0.5755 | 0.8169 | | 0.122 | 90.7692 | 295 | 0.5751 | 0.8169 | | 0.122 | 92.0 | 299 | 0.5748 | 0.8169 | | 0.1268 | 92.3077 | 300 | 0.5748 | 0.8169 | ### Framework versions - Transformers 4.41.0 - Pytorch 2.3.0+cu121 - Datasets 2.19.1 - Tokenizers 0.19.1