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--- |
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license: apache-2.0 |
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base_model: facebook/deit-base-distilled-patch16-224 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- imagefolder |
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metrics: |
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- accuracy |
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model-index: |
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- name: deit-base-distilled-patch16-224-55-fold2 |
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results: |
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- task: |
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name: Image Classification |
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type: image-classification |
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dataset: |
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name: imagefolder |
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type: imagefolder |
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config: default |
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split: train |
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args: default |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.810126582278481 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# deit-base-distilled-patch16-224-55-fold2 |
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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. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5842 |
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- Accuracy: 0.8101 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 100 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-------:|:----:|:---------------:|:--------:| |
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| No log | 0.8571 | 3 | 0.7763 | 0.5443 | |
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| No log | 2.0 | 7 | 0.6780 | 0.6203 | |
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| 0.721 | 2.8571 | 10 | 0.6954 | 0.5316 | |
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| 0.721 | 4.0 | 14 | 0.6370 | 0.6203 | |
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| 0.721 | 4.8571 | 17 | 0.6105 | 0.5949 | |
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| 0.6207 | 6.0 | 21 | 0.5798 | 0.6835 | |
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| 0.6207 | 6.8571 | 24 | 0.5704 | 0.7468 | |
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| 0.6207 | 8.0 | 28 | 0.5879 | 0.7089 | |
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| 0.5427 | 8.8571 | 31 | 0.6727 | 0.6582 | |
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| 0.5427 | 10.0 | 35 | 0.5841 | 0.6962 | |
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| 0.5427 | 10.8571 | 38 | 0.6059 | 0.6962 | |
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| 0.4775 | 12.0 | 42 | 1.0271 | 0.6076 | |
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| 0.4775 | 12.8571 | 45 | 0.6412 | 0.7089 | |
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| 0.4775 | 14.0 | 49 | 0.8064 | 0.6582 | |
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| 0.4961 | 14.8571 | 52 | 0.5600 | 0.6582 | |
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| 0.4961 | 16.0 | 56 | 0.5889 | 0.6709 | |
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| 0.4961 | 16.8571 | 59 | 0.8381 | 0.6835 | |
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| 0.4391 | 18.0 | 63 | 0.6725 | 0.6962 | |
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| 0.4391 | 18.8571 | 66 | 0.5350 | 0.7215 | |
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| 0.413 | 20.0 | 70 | 0.6033 | 0.7089 | |
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| 0.413 | 20.8571 | 73 | 0.7280 | 0.6835 | |
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| 0.413 | 22.0 | 77 | 0.6082 | 0.7342 | |
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| 0.336 | 22.8571 | 80 | 0.6530 | 0.7595 | |
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| 0.336 | 24.0 | 84 | 0.6922 | 0.7089 | |
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| 0.336 | 24.8571 | 87 | 0.6649 | 0.7089 | |
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| 0.2745 | 26.0 | 91 | 0.7311 | 0.7089 | |
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| 0.2745 | 26.8571 | 94 | 0.7192 | 0.7089 | |
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| 0.2745 | 28.0 | 98 | 0.7408 | 0.7215 | |
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| 0.2494 | 28.8571 | 101 | 0.5842 | 0.8101 | |
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| 0.2494 | 30.0 | 105 | 0.5949 | 0.7595 | |
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| 0.2494 | 30.8571 | 108 | 0.6885 | 0.7468 | |
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| 0.2291 | 32.0 | 112 | 0.8746 | 0.7089 | |
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| 0.2291 | 32.8571 | 115 | 0.8005 | 0.7089 | |
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| 0.2291 | 34.0 | 119 | 0.7034 | 0.7342 | |
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| 0.2 | 34.8571 | 122 | 0.7047 | 0.7089 | |
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| 0.2 | 36.0 | 126 | 0.8362 | 0.7342 | |
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| 0.2 | 36.8571 | 129 | 0.8509 | 0.7468 | |
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| 0.1674 | 38.0 | 133 | 0.9237 | 0.7595 | |
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| 0.1674 | 38.8571 | 136 | 0.7527 | 0.7595 | |
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| 0.1764 | 40.0 | 140 | 0.7904 | 0.7468 | |
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| 0.1764 | 40.8571 | 143 | 0.7333 | 0.7595 | |
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| 0.1764 | 42.0 | 147 | 0.7778 | 0.7342 | |
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| 0.1706 | 42.8571 | 150 | 0.7342 | 0.7722 | |
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| 0.1706 | 44.0 | 154 | 0.8144 | 0.7468 | |
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| 0.1706 | 44.8571 | 157 | 0.8299 | 0.7595 | |
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| 0.1617 | 46.0 | 161 | 1.0111 | 0.7468 | |
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| 0.1617 | 46.8571 | 164 | 0.8602 | 0.7595 | |
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| 0.1617 | 48.0 | 168 | 0.8332 | 0.7342 | |
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| 0.1622 | 48.8571 | 171 | 0.8297 | 0.7468 | |
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| 0.1622 | 50.0 | 175 | 0.8817 | 0.7595 | |
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| 0.1622 | 50.8571 | 178 | 0.8742 | 0.7595 | |
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| 0.1437 | 52.0 | 182 | 1.0696 | 0.7595 | |
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| 0.1437 | 52.8571 | 185 | 0.9412 | 0.7595 | |
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| 0.1437 | 54.0 | 189 | 0.7411 | 0.7975 | |
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| 0.1492 | 54.8571 | 192 | 0.9043 | 0.7595 | |
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| 0.1492 | 56.0 | 196 | 0.7936 | 0.7848 | |
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| 0.1492 | 56.8571 | 199 | 0.8231 | 0.7722 | |
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| 0.1279 | 58.0 | 203 | 1.0894 | 0.7722 | |
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| 0.1279 | 58.8571 | 206 | 1.0071 | 0.7975 | |
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| 0.1317 | 60.0 | 210 | 0.9893 | 0.7722 | |
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| 0.1317 | 60.8571 | 213 | 1.0476 | 0.7468 | |
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| 0.1317 | 62.0 | 217 | 0.8081 | 0.7848 | |
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| 0.1456 | 62.8571 | 220 | 0.8136 | 0.7468 | |
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| 0.1456 | 64.0 | 224 | 0.9613 | 0.7848 | |
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| 0.1456 | 64.8571 | 227 | 0.9783 | 0.7848 | |
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| 0.119 | 66.0 | 231 | 1.0226 | 0.7722 | |
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| 0.119 | 66.8571 | 234 | 1.0810 | 0.7722 | |
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| 0.119 | 68.0 | 238 | 0.9606 | 0.7975 | |
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| 0.1323 | 68.8571 | 241 | 0.9852 | 0.7848 | |
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| 0.1323 | 70.0 | 245 | 0.8826 | 0.7595 | |
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| 0.1323 | 70.8571 | 248 | 0.8169 | 0.7468 | |
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| 0.126 | 72.0 | 252 | 0.8815 | 0.7595 | |
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| 0.126 | 72.8571 | 255 | 0.9871 | 0.7722 | |
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| 0.126 | 74.0 | 259 | 0.8927 | 0.7722 | |
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| 0.1013 | 74.8571 | 262 | 0.8365 | 0.7468 | |
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| 0.1013 | 76.0 | 266 | 0.8423 | 0.7468 | |
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| 0.1013 | 76.8571 | 269 | 0.8331 | 0.7468 | |
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| 0.1142 | 78.0 | 273 | 0.8204 | 0.7722 | |
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| 0.1142 | 78.8571 | 276 | 0.8286 | 0.7722 | |
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| 0.1287 | 80.0 | 280 | 0.8702 | 0.7722 | |
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| 0.1287 | 80.8571 | 283 | 0.9070 | 0.7722 | |
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| 0.1287 | 82.0 | 287 | 0.9025 | 0.7722 | |
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| 0.099 | 82.8571 | 290 | 0.8806 | 0.7722 | |
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| 0.099 | 84.0 | 294 | 0.8637 | 0.7595 | |
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| 0.099 | 84.8571 | 297 | 0.8578 | 0.7595 | |
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| 0.1141 | 85.7143 | 300 | 0.8551 | 0.7468 | |
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### Framework versions |
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- Transformers 4.41.0 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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