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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-fold4 |
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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: 0.8354430379746836 |
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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-fold4 |
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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: 0.4908 |
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- Accuracy: 0.8354 |
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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 | 0.8297 | 0.5063 | |
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| No log | 2.0 | 7 | 0.6548 | 0.6203 | |
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| 0.6826 | 2.8571 | 10 | 0.6513 | 0.5190 | |
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| 0.6826 | 4.0 | 14 | 0.6024 | 0.7342 | |
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| 0.6826 | 4.8571 | 17 | 0.6473 | 0.5823 | |
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| 0.6198 | 6.0 | 21 | 0.5717 | 0.6835 | |
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| 0.6198 | 6.8571 | 24 | 0.7837 | 0.5570 | |
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| 0.6198 | 8.0 | 28 | 0.5272 | 0.7595 | |
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| 0.5409 | 8.8571 | 31 | 0.5162 | 0.7342 | |
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| 0.5409 | 10.0 | 35 | 0.6156 | 0.6709 | |
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| 0.5409 | 10.8571 | 38 | 0.5844 | 0.6582 | |
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| 0.5177 | 12.0 | 42 | 0.7013 | 0.6709 | |
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| 0.5177 | 12.8571 | 45 | 0.5017 | 0.7722 | |
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| 0.5177 | 14.0 | 49 | 0.4723 | 0.7975 | |
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| 0.4995 | 14.8571 | 52 | 0.7057 | 0.6835 | |
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| 0.4995 | 16.0 | 56 | 0.4669 | 0.8228 | |
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| 0.4995 | 16.8571 | 59 | 0.5737 | 0.7468 | |
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| 0.3767 | 18.0 | 63 | 0.5035 | 0.8101 | |
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| 0.3767 | 18.8571 | 66 | 0.8993 | 0.6203 | |
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| 0.3602 | 20.0 | 70 | 0.5425 | 0.7975 | |
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| 0.3602 | 20.8571 | 73 | 0.5605 | 0.7722 | |
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| 0.3602 | 22.0 | 77 | 0.4260 | 0.7975 | |
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| 0.3479 | 22.8571 | 80 | 0.4117 | 0.8228 | |
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| 0.3479 | 24.0 | 84 | 0.4017 | 0.7975 | |
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| 0.3479 | 24.8571 | 87 | 0.4401 | 0.8228 | |
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| 0.2845 | 26.0 | 91 | 0.4490 | 0.7975 | |
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| 0.2845 | 26.8571 | 94 | 0.5080 | 0.8101 | |
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| 0.2845 | 28.0 | 98 | 0.5014 | 0.7975 | |
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| 0.2316 | 28.8571 | 101 | 0.5385 | 0.7722 | |
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| 0.2316 | 30.0 | 105 | 0.5643 | 0.7595 | |
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| 0.2316 | 30.8571 | 108 | 0.4887 | 0.7848 | |
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| 0.2212 | 32.0 | 112 | 0.5253 | 0.7975 | |
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| 0.2212 | 32.8571 | 115 | 0.4633 | 0.7975 | |
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| 0.2212 | 34.0 | 119 | 0.5079 | 0.8228 | |
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| 0.2093 | 34.8571 | 122 | 0.5082 | 0.7975 | |
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| 0.2093 | 36.0 | 126 | 0.6113 | 0.7468 | |
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| 0.2093 | 36.8571 | 129 | 0.5094 | 0.7848 | |
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| 0.179 | 38.0 | 133 | 0.6253 | 0.8101 | |
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| 0.179 | 38.8571 | 136 | 0.5406 | 0.7848 | |
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| 0.173 | 40.0 | 140 | 0.6687 | 0.7722 | |
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| 0.173 | 40.8571 | 143 | 0.5691 | 0.7975 | |
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| 0.173 | 42.0 | 147 | 0.5776 | 0.7975 | |
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| 0.1881 | 42.8571 | 150 | 0.7816 | 0.7595 | |
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| 0.1881 | 44.0 | 154 | 0.4908 | 0.8354 | |
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| 0.1881 | 44.8571 | 157 | 0.5330 | 0.7848 | |
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| 0.161 | 46.0 | 161 | 0.5351 | 0.7848 | |
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| 0.161 | 46.8571 | 164 | 0.6663 | 0.7848 | |
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| 0.161 | 48.0 | 168 | 0.5382 | 0.7975 | |
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| 0.1446 | 48.8571 | 171 | 0.5877 | 0.7848 | |
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| 0.1446 | 50.0 | 175 | 0.6856 | 0.8228 | |
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| 0.1446 | 50.8571 | 178 | 0.6044 | 0.8101 | |
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| 0.1556 | 52.0 | 182 | 0.7954 | 0.7848 | |
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| 0.1556 | 52.8571 | 185 | 0.7432 | 0.7848 | |
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| 0.1556 | 54.0 | 189 | 0.7896 | 0.8101 | |
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| 0.1602 | 54.8571 | 192 | 0.8400 | 0.8101 | |
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| 0.1602 | 56.0 | 196 | 0.8243 | 0.7848 | |
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| 0.1602 | 56.8571 | 199 | 0.6864 | 0.8354 | |
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| 0.1357 | 58.0 | 203 | 0.7131 | 0.7722 | |
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| 0.1357 | 58.8571 | 206 | 0.9191 | 0.7722 | |
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| 0.1262 | 60.0 | 210 | 0.7465 | 0.7722 | |
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| 0.1262 | 60.8571 | 213 | 0.7127 | 0.7848 | |
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| 0.1262 | 62.0 | 217 | 0.6973 | 0.7975 | |
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| 0.1323 | 62.8571 | 220 | 0.7125 | 0.7848 | |
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| 0.1323 | 64.0 | 224 | 0.7235 | 0.7848 | |
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| 0.1323 | 64.8571 | 227 | 0.7200 | 0.7975 | |
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| 0.1258 | 66.0 | 231 | 0.7616 | 0.7848 | |
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| 0.1258 | 66.8571 | 234 | 0.8537 | 0.7848 | |
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| 0.1258 | 68.0 | 238 | 0.8223 | 0.7848 | |
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| 0.1316 | 68.8571 | 241 | 0.7751 | 0.8228 | |
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| 0.1316 | 70.0 | 245 | 0.7689 | 0.8228 | |
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| 0.1316 | 70.8571 | 248 | 0.7751 | 0.8101 | |
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| 0.1104 | 72.0 | 252 | 0.7770 | 0.8101 | |
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| 0.1104 | 72.8571 | 255 | 0.7916 | 0.7975 | |
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| 0.1104 | 74.0 | 259 | 0.7995 | 0.7848 | |
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| 0.1239 | 74.8571 | 262 | 0.7981 | 0.7848 | |
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| 0.1239 | 76.0 | 266 | 0.7890 | 0.8228 | |
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| 0.1239 | 76.8571 | 269 | 0.7888 | 0.8228 | |
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| 0.1057 | 78.0 | 273 | 0.7957 | 0.8228 | |
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| 0.1057 | 78.8571 | 276 | 0.7979 | 0.8228 | |
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| 0.1015 | 80.0 | 280 | 0.7959 | 0.8101 | |
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| 0.1015 | 80.8571 | 283 | 0.7935 | 0.8101 | |
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| 0.1015 | 82.0 | 287 | 0.7973 | 0.8228 | |
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| 0.101 | 82.8571 | 290 | 0.8033 | 0.7975 | |
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| 0.101 | 84.0 | 294 | 0.8072 | 0.7975 | |
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| 0.101 | 84.8571 | 297 | 0.8049 | 0.7975 | |
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| 0.1116 | 85.7143 | 300 | 0.8042 | 0.8101 | |
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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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