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dit-base_tobacco-tiny_tobacco3482_kd_MSE

Image Classification
Transformers
Safetensors
vit
Generated from Trainer
Inference Endpoints
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  1. README.md +166 -0
  2. config.json +48 -0
  3. model.safetensors +3 -0
  4. test-logits.npz +3 -0
  5. test-references.npz +3 -0
  6. training_args.bin +3 -0
  7. validation-logits.npz +3 -0
  8. validation-references.npz +3 -0
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: WinKawaks/vit-tiny-patch16-224
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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: dit-base_tobacco-tiny_tobacco3482_kd_MSE
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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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+ # dit-base_tobacco-tiny_tobacco3482_kd_MSE
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+
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+ This model is a fine-tuned version of [WinKawaks/vit-tiny-patch16-224](https://huggingface.co/WinKawaks/vit-tiny-patch16-224) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.0108
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+ - Accuracy: 0.815
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+ - Brier Loss: 0.2593
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+ - Nll: 1.1011
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+ - F1 Micro: 0.815
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+ - F1 Macro: 0.8014
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+ - Ece: 0.1462
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+ - Aurc: 0.0442
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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: 0.0001
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+ - train_batch_size: 128
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+ - eval_batch_size: 128
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+ - seed: 42
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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 | Brier Loss | Nll | F1 Micro | F1 Macro | Ece | Aurc |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:----------:|:------:|:--------:|:--------:|:------:|:------:|
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+ | No log | 1.0 | 7 | 7.1562 | 0.195 | 0.9158 | 7.6908 | 0.195 | 0.1043 | 0.2991 | 0.7927 |
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+ | No log | 2.0 | 14 | 6.3485 | 0.245 | 0.8600 | 4.2261 | 0.245 | 0.1794 | 0.2960 | 0.7445 |
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+ | No log | 3.0 | 21 | 5.2488 | 0.41 | 0.7090 | 3.6293 | 0.41 | 0.3494 | 0.2826 | 0.3786 |
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+ | No log | 4.0 | 28 | 4.0484 | 0.565 | 0.5698 | 1.7703 | 0.565 | 0.5209 | 0.2622 | 0.2372 |
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+ | No log | 5.0 | 35 | 3.0368 | 0.655 | 0.4710 | 1.5921 | 0.655 | 0.6368 | 0.2222 | 0.1598 |
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+ | No log | 6.0 | 42 | 2.6191 | 0.695 | 0.4219 | 1.6919 | 0.695 | 0.6535 | 0.2041 | 0.1200 |
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+ | No log | 7.0 | 49 | 2.0941 | 0.725 | 0.3913 | 1.3852 | 0.7250 | 0.6844 | 0.2046 | 0.0966 |
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+ | No log | 8.0 | 56 | 2.0668 | 0.725 | 0.4119 | 1.3829 | 0.7250 | 0.6811 | 0.1890 | 0.1045 |
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+ | No log | 9.0 | 63 | 1.7456 | 0.79 | 0.3138 | 1.5258 | 0.79 | 0.7539 | 0.1521 | 0.0651 |
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+ | No log | 10.0 | 70 | 1.5815 | 0.77 | 0.3391 | 1.2461 | 0.7700 | 0.7323 | 0.1593 | 0.0725 |
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+ | No log | 11.0 | 77 | 1.5720 | 0.785 | 0.2895 | 1.3282 | 0.785 | 0.7659 | 0.1408 | 0.0522 |
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+ | No log | 12.0 | 84 | 1.8886 | 0.78 | 0.3692 | 1.6238 | 0.78 | 0.7717 | 0.2015 | 0.0917 |
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+ | No log | 13.0 | 91 | 1.6164 | 0.785 | 0.2918 | 1.6303 | 0.785 | 0.7925 | 0.1545 | 0.0564 |
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+ | No log | 14.0 | 98 | 1.4318 | 0.785 | 0.3220 | 1.3070 | 0.785 | 0.7606 | 0.1430 | 0.0639 |
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+ | No log | 15.0 | 105 | 1.2774 | 0.81 | 0.2807 | 1.2877 | 0.81 | 0.7939 | 0.1532 | 0.0595 |
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+ | No log | 16.0 | 112 | 1.3797 | 0.8 | 0.2993 | 1.2409 | 0.8000 | 0.7759 | 0.1565 | 0.0700 |
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+ | No log | 17.0 | 119 | 1.3629 | 0.795 | 0.3091 | 1.1781 | 0.795 | 0.7670 | 0.1712 | 0.0567 |
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+ | No log | 18.0 | 126 | 1.5101 | 0.8 | 0.3192 | 1.3586 | 0.8000 | 0.7878 | 0.1919 | 0.0665 |
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+ | No log | 19.0 | 133 | 1.3897 | 0.805 | 0.2857 | 1.4983 | 0.805 | 0.7851 | 0.1356 | 0.0516 |
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+ | No log | 20.0 | 140 | 1.3821 | 0.795 | 0.3204 | 1.0916 | 0.795 | 0.7745 | 0.1678 | 0.0651 |
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+ | No log | 21.0 | 147 | 1.2852 | 0.83 | 0.2621 | 1.5182 | 0.83 | 0.8246 | 0.1483 | 0.0486 |
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+ | No log | 22.0 | 154 | 1.2080 | 0.815 | 0.2744 | 1.1921 | 0.815 | 0.7957 | 0.1319 | 0.0500 |
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+ | No log | 23.0 | 161 | 1.4016 | 0.805 | 0.3165 | 1.3364 | 0.805 | 0.7844 | 0.1534 | 0.0624 |
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+ | No log | 24.0 | 168 | 1.2883 | 0.825 | 0.2592 | 1.4946 | 0.825 | 0.8119 | 0.1549 | 0.0481 |
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+ | No log | 25.0 | 175 | 1.1715 | 0.815 | 0.2676 | 1.3363 | 0.815 | 0.8054 | 0.1464 | 0.0494 |
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+ | No log | 26.0 | 182 | 1.1844 | 0.825 | 0.2585 | 1.4938 | 0.825 | 0.8045 | 0.1572 | 0.0469 |
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+ | No log | 27.0 | 189 | 1.1739 | 0.81 | 0.2959 | 1.0692 | 0.81 | 0.7909 | 0.1625 | 0.0550 |
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+ | No log | 28.0 | 196 | 1.1944 | 0.815 | 0.2891 | 1.1811 | 0.815 | 0.7971 | 0.1430 | 0.0572 |
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+ | No log | 29.0 | 203 | 1.2115 | 0.83 | 0.2597 | 1.4809 | 0.83 | 0.8101 | 0.1289 | 0.0469 |
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+ | No log | 30.0 | 210 | 1.1622 | 0.81 | 0.2825 | 1.1104 | 0.81 | 0.7931 | 0.1463 | 0.0511 |
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+ | No log | 31.0 | 217 | 1.2591 | 0.8 | 0.3096 | 1.2310 | 0.8000 | 0.7789 | 0.1719 | 0.0591 |
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+ | No log | 32.0 | 224 | 1.1752 | 0.82 | 0.2687 | 1.4091 | 0.82 | 0.7959 | 0.1581 | 0.0504 |
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+ | No log | 33.0 | 231 | 1.1114 | 0.815 | 0.2719 | 1.0945 | 0.815 | 0.7885 | 0.1492 | 0.0485 |
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+ | No log | 34.0 | 238 | 1.1105 | 0.815 | 0.2727 | 1.1239 | 0.815 | 0.7962 | 0.1300 | 0.0479 |
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+ | No log | 35.0 | 245 | 1.1662 | 0.825 | 0.2748 | 1.3396 | 0.825 | 0.8100 | 0.1571 | 0.0554 |
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+ | No log | 36.0 | 252 | 1.1023 | 0.815 | 0.2757 | 1.1805 | 0.815 | 0.8031 | 0.1428 | 0.0504 |
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+ | No log | 37.0 | 259 | 1.1060 | 0.84 | 0.2604 | 1.3305 | 0.8400 | 0.8319 | 0.1596 | 0.0487 |
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+ | No log | 38.0 | 266 | 1.1123 | 0.81 | 0.2682 | 1.1122 | 0.81 | 0.7922 | 0.1310 | 0.0482 |
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+ | No log | 39.0 | 273 | 1.0820 | 0.815 | 0.2669 | 1.1629 | 0.815 | 0.7955 | 0.1479 | 0.0490 |
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+ | No log | 40.0 | 280 | 1.0972 | 0.805 | 0.2784 | 1.2442 | 0.805 | 0.7858 | 0.1576 | 0.0483 |
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+ | No log | 41.0 | 287 | 1.0845 | 0.83 | 0.2705 | 1.1180 | 0.83 | 0.8221 | 0.1504 | 0.0468 |
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+ | No log | 42.0 | 294 | 1.0769 | 0.82 | 0.2602 | 1.1173 | 0.82 | 0.8066 | 0.1458 | 0.0451 |
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+ | No log | 43.0 | 301 | 1.1366 | 0.81 | 0.2939 | 1.0722 | 0.81 | 0.7958 | 0.1532 | 0.0526 |
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+ | No log | 44.0 | 308 | 1.0716 | 0.82 | 0.2635 | 1.1839 | 0.82 | 0.8043 | 0.1403 | 0.0451 |
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+ | No log | 45.0 | 315 | 1.0865 | 0.81 | 0.2770 | 1.3595 | 0.81 | 0.7929 | 0.1501 | 0.0528 |
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+ | No log | 46.0 | 322 | 1.0768 | 0.82 | 0.2638 | 1.1161 | 0.82 | 0.8067 | 0.1462 | 0.0457 |
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+ | No log | 47.0 | 329 | 1.0644 | 0.825 | 0.2552 | 1.2086 | 0.825 | 0.8098 | 0.1579 | 0.0439 |
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+ | No log | 48.0 | 336 | 1.0511 | 0.815 | 0.2656 | 1.1019 | 0.815 | 0.8014 | 0.1518 | 0.0471 |
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+ | No log | 49.0 | 343 | 1.0517 | 0.82 | 0.2717 | 1.0881 | 0.82 | 0.8044 | 0.1559 | 0.0473 |
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+ | No log | 50.0 | 350 | 1.0824 | 0.81 | 0.2813 | 1.1022 | 0.81 | 0.7968 | 0.1538 | 0.0505 |
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+ | No log | 51.0 | 357 | 1.1439 | 0.835 | 0.2634 | 1.3483 | 0.835 | 0.8206 | 0.1471 | 0.0496 |
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+ | No log | 52.0 | 364 | 1.0444 | 0.83 | 0.2500 | 1.0999 | 0.83 | 0.8156 | 0.1310 | 0.0423 |
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+ | No log | 53.0 | 371 | 1.0426 | 0.825 | 0.2644 | 1.1112 | 0.825 | 0.8053 | 0.1295 | 0.0474 |
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+ | No log | 54.0 | 378 | 1.0341 | 0.825 | 0.2635 | 1.1053 | 0.825 | 0.8092 | 0.1467 | 0.0465 |
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+ | No log | 55.0 | 385 | 1.0900 | 0.815 | 0.2762 | 1.1021 | 0.815 | 0.7990 | 0.1439 | 0.0480 |
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+ | No log | 56.0 | 392 | 1.0423 | 0.845 | 0.2517 | 1.2594 | 0.845 | 0.8444 | 0.1497 | 0.0428 |
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+ | No log | 57.0 | 399 | 1.0246 | 0.825 | 0.2634 | 1.0927 | 0.825 | 0.8130 | 0.1260 | 0.0454 |
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+ | No log | 58.0 | 406 | 1.0365 | 0.835 | 0.2649 | 1.0825 | 0.835 | 0.8232 | 0.1291 | 0.0448 |
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+ | No log | 59.0 | 413 | 1.0394 | 0.82 | 0.2668 | 1.0968 | 0.82 | 0.8045 | 0.1458 | 0.0460 |
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+ | No log | 60.0 | 420 | 1.0261 | 0.815 | 0.2720 | 1.0883 | 0.815 | 0.8011 | 0.1409 | 0.0472 |
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+ | No log | 61.0 | 427 | 1.0503 | 0.83 | 0.2543 | 1.3230 | 0.83 | 0.8132 | 0.1378 | 0.0455 |
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+ | No log | 62.0 | 434 | 1.0400 | 0.82 | 0.2637 | 1.0958 | 0.82 | 0.8043 | 0.1397 | 0.0456 |
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+ | No log | 63.0 | 441 | 1.0338 | 0.82 | 0.2629 | 1.0960 | 0.82 | 0.8042 | 0.1338 | 0.0435 |
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+ | No log | 64.0 | 448 | 1.0373 | 0.84 | 0.2508 | 1.2817 | 0.8400 | 0.8260 | 0.1325 | 0.0433 |
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+ | No log | 65.0 | 455 | 1.0266 | 0.83 | 0.2663 | 1.1057 | 0.83 | 0.8163 | 0.1383 | 0.0460 |
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+ | No log | 66.0 | 462 | 1.0303 | 0.825 | 0.2549 | 1.1906 | 0.825 | 0.8098 | 0.1399 | 0.0450 |
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+ | No log | 67.0 | 469 | 1.0224 | 0.82 | 0.2668 | 1.0920 | 0.82 | 0.8042 | 0.1252 | 0.0433 |
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+ | No log | 68.0 | 476 | 1.0274 | 0.845 | 0.2526 | 1.1948 | 0.845 | 0.8368 | 0.1423 | 0.0442 |
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+ | No log | 69.0 | 483 | 1.0145 | 0.82 | 0.2647 | 1.0884 | 0.82 | 0.8070 | 0.1345 | 0.0449 |
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+ | No log | 70.0 | 490 | 1.0194 | 0.815 | 0.2606 | 1.1076 | 0.815 | 0.8014 | 0.1529 | 0.0446 |
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+ | No log | 71.0 | 497 | 1.0153 | 0.825 | 0.2572 | 1.2484 | 0.825 | 0.8142 | 0.1425 | 0.0445 |
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+ | 0.6377 | 72.0 | 504 | 1.0265 | 0.815 | 0.2607 | 1.1109 | 0.815 | 0.8039 | 0.1457 | 0.0445 |
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+ | 0.6377 | 73.0 | 511 | 1.0081 | 0.82 | 0.2567 | 1.1031 | 0.82 | 0.8040 | 0.1321 | 0.0440 |
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+ | 0.6377 | 74.0 | 518 | 1.0135 | 0.825 | 0.2600 | 1.1036 | 0.825 | 0.8074 | 0.1477 | 0.0450 |
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+ | 0.6377 | 75.0 | 525 | 1.0053 | 0.82 | 0.2616 | 1.1012 | 0.82 | 0.8044 | 0.1542 | 0.0442 |
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+ | 0.6377 | 76.0 | 532 | 1.0187 | 0.82 | 0.2598 | 1.1115 | 0.82 | 0.8069 | 0.1566 | 0.0445 |
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+ | 0.6377 | 77.0 | 539 | 1.0127 | 0.82 | 0.2610 | 1.1024 | 0.82 | 0.8097 | 0.1489 | 0.0443 |
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+ | 0.6377 | 78.0 | 546 | 1.0079 | 0.82 | 0.2581 | 1.1034 | 0.82 | 0.8069 | 0.1463 | 0.0434 |
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+ | 0.6377 | 79.0 | 553 | 1.0097 | 0.815 | 0.2592 | 1.1030 | 0.815 | 0.8014 | 0.1478 | 0.0438 |
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+ | 0.6377 | 80.0 | 560 | 1.0131 | 0.835 | 0.2556 | 1.1048 | 0.835 | 0.8281 | 0.1508 | 0.0441 |
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+ | 0.6377 | 81.0 | 567 | 1.0183 | 0.82 | 0.2602 | 1.1057 | 0.82 | 0.8044 | 0.1417 | 0.0446 |
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+ | 0.6377 | 82.0 | 574 | 1.0190 | 0.815 | 0.2665 | 1.0966 | 0.815 | 0.7987 | 0.1370 | 0.0462 |
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+ | 0.6377 | 83.0 | 581 | 1.0117 | 0.815 | 0.2619 | 1.0974 | 0.815 | 0.8014 | 0.1614 | 0.0442 |
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+ | 0.6377 | 84.0 | 588 | 1.0099 | 0.82 | 0.2557 | 1.1070 | 0.82 | 0.8044 | 0.1327 | 0.0436 |
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+ | 0.6377 | 85.0 | 595 | 1.0088 | 0.82 | 0.2569 | 1.1037 | 0.82 | 0.8044 | 0.1446 | 0.0437 |
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+ | 0.6377 | 86.0 | 602 | 1.0110 | 0.82 | 0.2596 | 1.0945 | 0.82 | 0.8043 | 0.1505 | 0.0442 |
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+ | 0.6377 | 87.0 | 609 | 1.0151 | 0.815 | 0.2606 | 1.1046 | 0.815 | 0.8014 | 0.1416 | 0.0451 |
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+ | 0.6377 | 88.0 | 616 | 1.0101 | 0.815 | 0.2587 | 1.1025 | 0.815 | 0.8014 | 0.1435 | 0.0440 |
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+ | 0.6377 | 89.0 | 623 | 1.0106 | 0.815 | 0.2613 | 1.0976 | 0.815 | 0.8014 | 0.1489 | 0.0443 |
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+ | 0.6377 | 90.0 | 630 | 1.0097 | 0.815 | 0.2590 | 1.0993 | 0.815 | 0.8014 | 0.1490 | 0.0439 |
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+ | 0.6377 | 91.0 | 637 | 1.0098 | 0.815 | 0.2593 | 1.1024 | 0.815 | 0.8014 | 0.1510 | 0.0440 |
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+ | 0.6377 | 92.0 | 644 | 1.0116 | 0.815 | 0.2600 | 1.1004 | 0.815 | 0.8014 | 0.1465 | 0.0442 |
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+ | 0.6377 | 93.0 | 651 | 1.0107 | 0.815 | 0.2596 | 1.1005 | 0.815 | 0.8014 | 0.1548 | 0.0442 |
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+ | 0.6377 | 94.0 | 658 | 1.0110 | 0.815 | 0.2599 | 1.0993 | 0.815 | 0.8014 | 0.1463 | 0.0440 |
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+ | 0.6377 | 95.0 | 665 | 1.0106 | 0.815 | 0.2593 | 1.1011 | 0.815 | 0.8014 | 0.1409 | 0.0441 |
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+ | 0.6377 | 96.0 | 672 | 1.0106 | 0.815 | 0.2596 | 1.1011 | 0.815 | 0.8014 | 0.1496 | 0.0442 |
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+ | 0.6377 | 97.0 | 679 | 1.0109 | 0.815 | 0.2595 | 1.1007 | 0.815 | 0.8014 | 0.1462 | 0.0442 |
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+ | 0.6377 | 98.0 | 686 | 1.0107 | 0.815 | 0.2593 | 1.1013 | 0.815 | 0.8014 | 0.1409 | 0.0441 |
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+ | 0.6377 | 99.0 | 693 | 1.0107 | 0.815 | 0.2594 | 1.1009 | 0.815 | 0.8014 | 0.1462 | 0.0441 |
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+ | 0.6377 | 100.0 | 700 | 1.0108 | 0.815 | 0.2593 | 1.1011 | 0.815 | 0.8014 | 0.1462 | 0.0442 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.36.0.dev0
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+ - Pytorch 2.2.0.dev20231112+cu118
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+ - Datasets 2.14.5
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+ - Tokenizers 0.14.1
config.json ADDED
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+ {
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+ "_name_or_path": "WinKawaks/vit-tiny-patch16-224",
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+ "architectures": [
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+ "ViTForImageClassification"
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+ ],
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+ "attention_probs_dropout_prob": 0.0,
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+ "encoder_stride": 16,
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.0,
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+ "hidden_size": 192,
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+ "id2label": {
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+ "0": "ADVE",
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+ "1": "Email",
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+ "2": "Form",
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+ "3": "Letter",
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+ "4": "Memo",
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+ "5": "News",
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+ "6": "Note",
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+ "7": "Report",
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+ "8": "Resume",
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+ "9": "Scientific"
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+ },
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+ "image_size": 224,
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+ "initializer_range": 0.02,
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+ "intermediate_size": 768,
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+ "label2id": {
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+ "ADVE": 0,
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+ "Email": 1,
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+ "Form": 2,
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+ "Letter": 3,
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+ "Memo": 4,
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+ "News": 5,
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+ "Note": 6,
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+ "Report": 7,
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+ "Resume": 8,
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+ "Scientific": 9
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+ },
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+ "layer_norm_eps": 1e-12,
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+ "model_type": "vit",
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+ "num_attention_heads": 3,
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+ "num_channels": 3,
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+ "num_hidden_layers": 12,
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+ "patch_size": 16,
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+ "problem_type": "single_label_classification",
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+ "qkv_bias": true,
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.36.0.dev0"
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+ }
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