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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-patch16-224-65-fold3 |
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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: 0.8732394366197183 |
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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-patch16-224-65-fold3 |
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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: 0.4993 |
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- Accuracy: 0.8732 |
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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 | 0.9231 | 3 | 0.7403 | 0.5493 | |
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| No log | 1.8462 | 6 | 0.7199 | 0.5211 | |
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| No log | 2.7692 | 9 | 0.7111 | 0.5634 | |
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| 0.7693 | 4.0 | 13 | 0.7015 | 0.5352 | |
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| 0.7693 | 4.9231 | 16 | 0.6471 | 0.6197 | |
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| 0.7693 | 5.8462 | 19 | 0.6691 | 0.6056 | |
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| 0.6542 | 6.7692 | 22 | 0.6188 | 0.6197 | |
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| 0.6542 | 8.0 | 26 | 0.6967 | 0.5775 | |
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| 0.6542 | 8.9231 | 29 | 0.5732 | 0.7324 | |
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| 0.5935 | 9.8462 | 32 | 0.5184 | 0.7042 | |
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| 0.5935 | 10.7692 | 35 | 0.6031 | 0.7183 | |
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| 0.5935 | 12.0 | 39 | 0.6671 | 0.6479 | |
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| 0.549 | 12.9231 | 42 | 0.5281 | 0.7183 | |
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| 0.549 | 13.8462 | 45 | 0.5792 | 0.7183 | |
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| 0.549 | 14.7692 | 48 | 0.5389 | 0.7465 | |
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| 0.4778 | 16.0 | 52 | 0.6010 | 0.7042 | |
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| 0.4778 | 16.9231 | 55 | 0.5245 | 0.7606 | |
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| 0.4778 | 17.8462 | 58 | 0.5491 | 0.7183 | |
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| 0.4039 | 18.7692 | 61 | 0.5590 | 0.7465 | |
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| 0.4039 | 20.0 | 65 | 0.4886 | 0.7324 | |
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| 0.4039 | 20.9231 | 68 | 0.5050 | 0.7324 | |
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| 0.3409 | 21.8462 | 71 | 0.4912 | 0.7465 | |
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| 0.3409 | 22.7692 | 74 | 0.4929 | 0.7746 | |
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| 0.3409 | 24.0 | 78 | 0.5365 | 0.7746 | |
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| 0.3202 | 24.9231 | 81 | 0.4685 | 0.8028 | |
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| 0.3202 | 25.8462 | 84 | 0.4404 | 0.8169 | |
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| 0.3202 | 26.7692 | 87 | 0.4639 | 0.8028 | |
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| 0.2466 | 28.0 | 91 | 0.5491 | 0.7606 | |
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| 0.2466 | 28.9231 | 94 | 0.5170 | 0.7606 | |
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| 0.2466 | 29.8462 | 97 | 0.4444 | 0.8028 | |
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| 0.2433 | 30.7692 | 100 | 0.4517 | 0.8310 | |
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| 0.2433 | 32.0 | 104 | 0.7797 | 0.7606 | |
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| 0.2433 | 32.9231 | 107 | 0.4321 | 0.8169 | |
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| 0.2535 | 33.8462 | 110 | 0.5956 | 0.7746 | |
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| 0.2535 | 34.7692 | 113 | 0.4695 | 0.7887 | |
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| 0.2535 | 36.0 | 117 | 0.8106 | 0.6901 | |
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| 0.2215 | 36.9231 | 120 | 0.7119 | 0.7465 | |
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| 0.2215 | 37.8462 | 123 | 0.4752 | 0.8028 | |
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| 0.2215 | 38.7692 | 126 | 0.4784 | 0.8169 | |
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| 0.2143 | 40.0 | 130 | 0.4773 | 0.8028 | |
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| 0.2143 | 40.9231 | 133 | 0.5581 | 0.8169 | |
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| 0.2143 | 41.8462 | 136 | 0.6098 | 0.8028 | |
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| 0.2143 | 42.7692 | 139 | 0.5193 | 0.8169 | |
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| 0.1726 | 44.0 | 143 | 0.4306 | 0.8451 | |
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| 0.1726 | 44.9231 | 146 | 0.4234 | 0.8592 | |
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| 0.1726 | 45.8462 | 149 | 0.5264 | 0.8169 | |
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| 0.1684 | 46.7692 | 152 | 0.7303 | 0.8028 | |
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| 0.1684 | 48.0 | 156 | 0.5079 | 0.8169 | |
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| 0.1684 | 48.9231 | 159 | 0.5392 | 0.8169 | |
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| 0.1604 | 49.8462 | 162 | 0.3951 | 0.8169 | |
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| 0.1604 | 50.7692 | 165 | 0.4311 | 0.8028 | |
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| 0.1604 | 52.0 | 169 | 0.4082 | 0.8028 | |
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| 0.1457 | 52.9231 | 172 | 0.4173 | 0.7887 | |
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| 0.1457 | 53.8462 | 175 | 0.4311 | 0.8310 | |
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| 0.1457 | 54.7692 | 178 | 0.4213 | 0.8028 | |
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| 0.1549 | 56.0 | 182 | 0.4713 | 0.8451 | |
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| 0.1549 | 56.9231 | 185 | 0.7493 | 0.8028 | |
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| 0.1549 | 57.8462 | 188 | 0.5161 | 0.8451 | |
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| 0.1391 | 58.7692 | 191 | 0.4685 | 0.8169 | |
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| 0.1391 | 60.0 | 195 | 0.6968 | 0.8028 | |
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| 0.1391 | 60.9231 | 198 | 0.5837 | 0.8310 | |
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| 0.1272 | 61.8462 | 201 | 0.5863 | 0.8169 | |
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| 0.1272 | 62.7692 | 204 | 0.5460 | 0.8310 | |
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| 0.1272 | 64.0 | 208 | 0.6198 | 0.8310 | |
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| 0.1341 | 64.9231 | 211 | 0.5584 | 0.8592 | |
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| 0.1341 | 65.8462 | 214 | 0.6429 | 0.8451 | |
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| 0.1341 | 66.7692 | 217 | 0.8592 | 0.8028 | |
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| 0.1144 | 68.0 | 221 | 0.8472 | 0.8028 | |
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| 0.1144 | 68.9231 | 224 | 0.8360 | 0.8169 | |
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| 0.1144 | 69.8462 | 227 | 0.6697 | 0.8169 | |
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| 0.1321 | 70.7692 | 230 | 0.6625 | 0.8028 | |
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| 0.1321 | 72.0 | 234 | 0.7228 | 0.8310 | |
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| 0.1321 | 72.9231 | 237 | 0.6793 | 0.8310 | |
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| 0.1206 | 73.8462 | 240 | 0.5571 | 0.8592 | |
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| 0.1206 | 74.7692 | 243 | 0.5106 | 0.8451 | |
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| 0.1206 | 76.0 | 247 | 0.6686 | 0.8310 | |
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| 0.131 | 76.9231 | 250 | 0.7132 | 0.8310 | |
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| 0.131 | 77.8462 | 253 | 0.5945 | 0.8451 | |
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| 0.131 | 78.7692 | 256 | 0.5516 | 0.7746 | |
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| 0.1009 | 80.0 | 260 | 0.5474 | 0.7606 | |
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| 0.1009 | 80.9231 | 263 | 0.5219 | 0.7887 | |
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| 0.1009 | 81.8462 | 266 | 0.5375 | 0.8451 | |
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| 0.1009 | 82.7692 | 269 | 0.5133 | 0.8451 | |
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| 0.1084 | 84.0 | 273 | 0.4911 | 0.8451 | |
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| 0.1084 | 84.9231 | 276 | 0.4993 | 0.8732 | |
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| 0.1084 | 85.8462 | 279 | 0.5418 | 0.8592 | |
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| 0.0851 | 86.7692 | 282 | 0.6010 | 0.8451 | |
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| 0.0851 | 88.0 | 286 | 0.6305 | 0.8451 | |
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| 0.0851 | 88.9231 | 289 | 0.6016 | 0.8451 | |
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| 0.1071 | 89.8462 | 292 | 0.5773 | 0.8592 | |
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| 0.1071 | 90.7692 | 295 | 0.5610 | 0.8732 | |
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| 0.1071 | 92.0 | 299 | 0.5522 | 0.8732 | |
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| 0.1139 | 92.3077 | 300 | 0.5514 | 0.8732 | |
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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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