--- 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-fold2 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: 0.9154929577464789 --- # deit-base-distilled-patch16-224-65-fold2 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: 0.3095 - Accuracy: 0.9155 ## 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 | 0.7211 | 0.4366 | | No log | 1.8462 | 6 | 0.7016 | 0.5070 | | No log | 2.7692 | 9 | 0.6703 | 0.6197 | | 0.6946 | 4.0 | 13 | 0.6381 | 0.6620 | | 0.6946 | 4.9231 | 16 | 0.5945 | 0.6761 | | 0.6946 | 5.8462 | 19 | 0.6084 | 0.7183 | | 0.6262 | 6.7692 | 22 | 0.5639 | 0.7465 | | 0.6262 | 8.0 | 26 | 0.5203 | 0.7746 | | 0.6262 | 8.9231 | 29 | 0.4805 | 0.7887 | | 0.544 | 9.8462 | 32 | 0.5204 | 0.7324 | | 0.544 | 10.7692 | 35 | 0.4635 | 0.7746 | | 0.544 | 12.0 | 39 | 0.4957 | 0.7606 | | 0.516 | 12.9231 | 42 | 0.4723 | 0.7746 | | 0.516 | 13.8462 | 45 | 0.5170 | 0.7042 | | 0.516 | 14.7692 | 48 | 0.5405 | 0.8169 | | 0.4938 | 16.0 | 52 | 0.5082 | 0.7324 | | 0.4938 | 16.9231 | 55 | 0.4608 | 0.7887 | | 0.4938 | 17.8462 | 58 | 0.4211 | 0.7606 | | 0.4123 | 18.7692 | 61 | 0.5015 | 0.7746 | | 0.4123 | 20.0 | 65 | 0.3935 | 0.8592 | | 0.4123 | 20.9231 | 68 | 0.4179 | 0.8169 | | 0.3489 | 21.8462 | 71 | 0.3991 | 0.9014 | | 0.3489 | 22.7692 | 74 | 0.3910 | 0.8592 | | 0.3489 | 24.0 | 78 | 0.4277 | 0.8310 | | 0.2889 | 24.9231 | 81 | 0.4032 | 0.8169 | | 0.2889 | 25.8462 | 84 | 0.3703 | 0.8592 | | 0.2889 | 26.7692 | 87 | 0.4404 | 0.8310 | | 0.2659 | 28.0 | 91 | 0.3666 | 0.8592 | | 0.2659 | 28.9231 | 94 | 0.3992 | 0.8169 | | 0.2659 | 29.8462 | 97 | 0.4040 | 0.8169 | | 0.2269 | 30.7692 | 100 | 0.3559 | 0.8592 | | 0.2269 | 32.0 | 104 | 0.4766 | 0.8028 | | 0.2269 | 32.9231 | 107 | 0.3852 | 0.8592 | | 0.2031 | 33.8462 | 110 | 0.3702 | 0.8592 | | 0.2031 | 34.7692 | 113 | 0.3203 | 0.8732 | | 0.2031 | 36.0 | 117 | 0.5303 | 0.8169 | | 0.2037 | 36.9231 | 120 | 0.3897 | 0.8732 | | 0.2037 | 37.8462 | 123 | 0.3841 | 0.8732 | | 0.2037 | 38.7692 | 126 | 0.3896 | 0.8873 | | 0.2018 | 40.0 | 130 | 0.4177 | 0.8451 | | 0.2018 | 40.9231 | 133 | 0.4548 | 0.8451 | | 0.2018 | 41.8462 | 136 | 0.4115 | 0.8310 | | 0.2018 | 42.7692 | 139 | 0.4121 | 0.8451 | | 0.1721 | 44.0 | 143 | 0.3920 | 0.8592 | | 0.1721 | 44.9231 | 146 | 0.3693 | 0.8451 | | 0.1721 | 45.8462 | 149 | 0.3605 | 0.8592 | | 0.1678 | 46.7692 | 152 | 0.5434 | 0.8310 | | 0.1678 | 48.0 | 156 | 0.4189 | 0.8310 | | 0.1678 | 48.9231 | 159 | 0.3124 | 0.8873 | | 0.1604 | 49.8462 | 162 | 0.3293 | 0.8873 | | 0.1604 | 50.7692 | 165 | 0.3372 | 0.9014 | | 0.1604 | 52.0 | 169 | 0.3505 | 0.8732 | | 0.1406 | 52.9231 | 172 | 0.3095 | 0.9155 | | 0.1406 | 53.8462 | 175 | 0.3054 | 0.9155 | | 0.1406 | 54.7692 | 178 | 0.3695 | 0.8873 | | 0.1492 | 56.0 | 182 | 0.4058 | 0.8592 | | 0.1492 | 56.9231 | 185 | 0.4650 | 0.8451 | | 0.1492 | 57.8462 | 188 | 0.4060 | 0.8592 | | 0.1359 | 58.7692 | 191 | 0.3819 | 0.8873 | | 0.1359 | 60.0 | 195 | 0.5230 | 0.7887 | | 0.1359 | 60.9231 | 198 | 0.4986 | 0.8169 | | 0.1264 | 61.8462 | 201 | 0.4570 | 0.8310 | | 0.1264 | 62.7692 | 204 | 0.4507 | 0.8451 | | 0.1264 | 64.0 | 208 | 0.5765 | 0.8028 | | 0.1478 | 64.9231 | 211 | 0.4514 | 0.8592 | | 0.1478 | 65.8462 | 214 | 0.4434 | 0.8873 | | 0.1478 | 66.7692 | 217 | 0.4403 | 0.8592 | | 0.1398 | 68.0 | 221 | 0.5928 | 0.8310 | | 0.1398 | 68.9231 | 224 | 0.4587 | 0.8592 | | 0.1398 | 69.8462 | 227 | 0.4053 | 0.8451 | | 0.161 | 70.7692 | 230 | 0.4233 | 0.8592 | | 0.161 | 72.0 | 234 | 0.4264 | 0.8592 | | 0.161 | 72.9231 | 237 | 0.4127 | 0.8310 | | 0.1326 | 73.8462 | 240 | 0.4013 | 0.8592 | | 0.1326 | 74.7692 | 243 | 0.4389 | 0.8451 | | 0.1326 | 76.0 | 247 | 0.3772 | 0.8592 | | 0.1236 | 76.9231 | 250 | 0.3600 | 0.8732 | | 0.1236 | 77.8462 | 253 | 0.3890 | 0.8873 | | 0.1236 | 78.7692 | 256 | 0.4401 | 0.8451 | | 0.0973 | 80.0 | 260 | 0.4014 | 0.8592 | | 0.0973 | 80.9231 | 263 | 0.3766 | 0.8732 | | 0.0973 | 81.8462 | 266 | 0.3908 | 0.8451 | | 0.0973 | 82.7692 | 269 | 0.4339 | 0.8592 | | 0.1079 | 84.0 | 273 | 0.4567 | 0.8592 | | 0.1079 | 84.9231 | 276 | 0.4415 | 0.8732 | | 0.1079 | 85.8462 | 279 | 0.4183 | 0.8592 | | 0.1015 | 86.7692 | 282 | 0.4039 | 0.8873 | | 0.1015 | 88.0 | 286 | 0.3996 | 0.8873 | | 0.1015 | 88.9231 | 289 | 0.4031 | 0.9014 | | 0.1174 | 89.8462 | 292 | 0.4101 | 0.8732 | | 0.1174 | 90.7692 | 295 | 0.4153 | 0.8732 | | 0.1174 | 92.0 | 299 | 0.4146 | 0.8732 | | 0.0968 | 92.3077 | 300 | 0.4145 | 0.8732 | ### Framework versions - Transformers 4.41.0 - Pytorch 2.3.0+cu121 - Datasets 2.19.1 - Tokenizers 0.19.1