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finetuned-CK

Image Classification
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beit
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  2. model.safetensors +1 -1
  3. runs/Jan05_01-15-19_56de59eca2fc/events.out.tfevents.1704417337.56de59eca2fc.3067.0 +2 -2
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: microsoft/beit-base-patch16-224-pt22k-ft22k
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: finetuned-CK
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+ results: []
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+ ---
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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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+
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+ # finetuned-CK
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+
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+ This model is a fine-tuned version of [microsoft/beit-base-patch16-224-pt22k-ft22k](https://huggingface.co/microsoft/beit-base-patch16-224-pt22k-ft22k) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1159
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+ - Accuracy: 0.9873
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 5e-06
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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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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 0.87 | 5 | 2.0523 | 0.1139 |
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+ | 1.9841 | 1.91 | 11 | 1.9751 | 0.0633 |
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+ | 1.9841 | 2.96 | 17 | 1.8640 | 0.1392 |
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+ | 1.8698 | 4.0 | 23 | 1.7348 | 0.3291 |
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+ | 1.8698 | 4.87 | 28 | 1.6262 | 0.4430 |
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+ | 1.6947 | 5.91 | 34 | 1.4895 | 0.5823 |
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+ | 1.6038 | 6.96 | 40 | 1.3500 | 0.5949 |
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+ | 1.6038 | 8.0 | 46 | 1.1857 | 0.6835 |
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+ | 1.4019 | 8.87 | 51 | 1.0636 | 0.6962 |
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+ | 1.4019 | 9.91 | 57 | 0.9472 | 0.7468 |
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+ | 1.2101 | 10.96 | 63 | 0.8263 | 0.7722 |
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+ | 1.2101 | 12.0 | 69 | 0.7643 | 0.7595 |
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+ | 1.077 | 12.87 | 74 | 0.7260 | 0.7722 |
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+ | 0.9735 | 13.91 | 80 | 0.6628 | 0.8228 |
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+ | 0.9735 | 14.96 | 86 | 0.6245 | 0.8101 |
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+ | 0.8696 | 16.0 | 92 | 0.5579 | 0.8101 |
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+ | 0.8696 | 16.87 | 97 | 0.5309 | 0.8228 |
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+ | 0.858 | 17.91 | 103 | 0.5099 | 0.8354 |
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+ | 0.858 | 18.96 | 109 | 0.4997 | 0.8354 |
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+ | 0.7716 | 20.0 | 115 | 0.4679 | 0.8608 |
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+ | 0.699 | 20.87 | 120 | 0.4455 | 0.8481 |
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+ | 0.699 | 21.91 | 126 | 0.4409 | 0.8608 |
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+ | 0.6768 | 22.96 | 132 | 0.4186 | 0.8481 |
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+ | 0.6768 | 24.0 | 138 | 0.3826 | 0.8734 |
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+ | 0.6303 | 24.87 | 143 | 0.3708 | 0.8861 |
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+ | 0.6303 | 25.91 | 149 | 0.3545 | 0.8608 |
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+ | 0.5786 | 26.96 | 155 | 0.3480 | 0.8987 |
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+ | 0.5188 | 28.0 | 161 | 0.3241 | 0.9241 |
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+ | 0.5188 | 28.87 | 166 | 0.3257 | 0.9114 |
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+ | 0.5349 | 29.91 | 172 | 0.2963 | 0.9241 |
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+ | 0.5349 | 30.96 | 178 | 0.2836 | 0.9367 |
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+ | 0.5208 | 32.0 | 184 | 0.2822 | 0.9620 |
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+ | 0.5208 | 32.87 | 189 | 0.2933 | 0.9494 |
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+ | 0.4458 | 33.91 | 195 | 0.2742 | 0.9620 |
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+ | 0.4716 | 34.96 | 201 | 0.2580 | 0.9620 |
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+ | 0.4716 | 36.0 | 207 | 0.2432 | 0.9620 |
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+ | 0.427 | 36.87 | 212 | 0.2333 | 0.9747 |
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+ | 0.427 | 37.91 | 218 | 0.2115 | 0.9494 |
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+ | 0.4052 | 38.96 | 224 | 0.2044 | 0.9873 |
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+ | 0.3899 | 40.0 | 230 | 0.2081 | 0.9747 |
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+ | 0.3899 | 40.87 | 235 | 0.2110 | 0.9620 |
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+ | 0.4098 | 41.91 | 241 | 0.2099 | 0.9494 |
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+ | 0.4098 | 42.96 | 247 | 0.1899 | 0.9747 |
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+ | 0.3691 | 44.0 | 253 | 0.1783 | 0.9873 |
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+ | 0.3691 | 44.87 | 258 | 0.1768 | 0.9747 |
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+ | 0.3878 | 45.91 | 264 | 0.1836 | 0.9873 |
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+ | 0.3582 | 46.96 | 270 | 0.1876 | 0.9747 |
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+ | 0.3582 | 48.0 | 276 | 0.1761 | 0.9747 |
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+ | 0.356 | 48.87 | 281 | 0.1745 | 0.9620 |
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+ | 0.356 | 49.91 | 287 | 0.1761 | 0.9620 |
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+ | 0.3715 | 50.96 | 293 | 0.1716 | 0.9873 |
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+ | 0.3715 | 52.0 | 299 | 0.1694 | 0.9620 |
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+ | 0.3195 | 52.87 | 304 | 0.1660 | 0.9873 |
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+ | 0.3452 | 53.91 | 310 | 0.1584 | 0.9873 |
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+ | 0.3452 | 54.96 | 316 | 0.1579 | 0.9620 |
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+ | 0.3407 | 56.0 | 322 | 0.1431 | 0.9873 |
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+ | 0.3407 | 56.87 | 327 | 0.1423 | 0.9873 |
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+ | 0.3092 | 57.91 | 333 | 0.1434 | 0.9747 |
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+ | 0.3092 | 58.96 | 339 | 0.1391 | 0.9873 |
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+ | 0.3346 | 60.0 | 345 | 0.1362 | 0.9873 |
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+ | 0.3107 | 60.87 | 350 | 0.1341 | 0.9873 |
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+ | 0.3107 | 61.91 | 356 | 0.1368 | 0.9873 |
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+ | 0.2884 | 62.96 | 362 | 0.1393 | 0.9747 |
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+ | 0.2884 | 64.0 | 368 | 0.1347 | 0.9873 |
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+ | 0.3048 | 64.87 | 373 | 0.1334 | 0.9873 |
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+ | 0.3048 | 65.91 | 379 | 0.1342 | 0.9747 |
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+ | 0.3452 | 66.96 | 385 | 0.1310 | 0.9747 |
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+ | 0.2835 | 68.0 | 391 | 0.1308 | 0.9873 |
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+ | 0.2835 | 68.87 | 396 | 0.1304 | 0.9747 |
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+ | 0.3865 | 69.91 | 402 | 0.1264 | 0.9873 |
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+ | 0.3865 | 70.96 | 408 | 0.1247 | 0.9873 |
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+ | 0.2729 | 72.0 | 414 | 0.1239 | 0.9873 |
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+ | 0.2729 | 72.87 | 419 | 0.1249 | 0.9747 |
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+ | 0.2643 | 73.91 | 425 | 0.1189 | 0.9873 |
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+ | 0.3176 | 74.96 | 431 | 0.1171 | 0.9873 |
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+ | 0.3176 | 76.0 | 437 | 0.1174 | 0.9873 |
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+ | 0.3184 | 76.87 | 442 | 0.1184 | 0.9873 |
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+ | 0.3184 | 77.91 | 448 | 0.1160 | 0.9873 |
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+ | 0.2817 | 78.96 | 454 | 0.1147 | 0.9873 |
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+ | 0.2666 | 80.0 | 460 | 0.1133 | 0.9873 |
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+ | 0.2666 | 80.87 | 465 | 0.1139 | 0.9873 |
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+ | 0.2589 | 81.91 | 471 | 0.1142 | 0.9873 |
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+ | 0.2589 | 82.96 | 477 | 0.1150 | 0.9873 |
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+ | 0.275 | 84.0 | 483 | 0.1156 | 0.9873 |
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+ | 0.275 | 84.87 | 488 | 0.1160 | 0.9873 |
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+ | 0.2644 | 85.91 | 494 | 0.1160 | 0.9873 |
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+ | 0.3187 | 86.96 | 500 | 0.1159 | 0.9873 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.2
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+ - Pytorch 2.1.0+cu121
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+ - Datasets 2.16.1
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+ - Tokenizers 0.15.0
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