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bdpc
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resnet101-base_tobacco-cnn_tobacco3482_kd_CEKD_t1.5_a0.7

Image Classification
Transformers
PyTorch
resnet
Generated from Trainer
Inference Endpoints
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  1. README.md +116 -0
  2. config.json +64 -0
  3. pytorch_model.bin +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: microsoft/resnet-50
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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: resnet101-base_tobacco-cnn_tobacco3482_kd_CEKD_t1.5_a0.7
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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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+ # resnet101-base_tobacco-cnn_tobacco3482_kd_CEKD_t1.5_a0.7
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+
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+ This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.8009
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+ - Accuracy: 0.695
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+ - Brier Loss: 0.4518
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+ - Nll: 2.3840
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+ - F1 Micro: 0.695
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+ - F1 Macro: 0.6406
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+ - Ece: 0.2661
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+ - Aurc: 0.1211
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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: 64
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+ - eval_batch_size: 64
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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: 50
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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 | 13 | 1.7971 | 0.17 | 0.8966 | 8.4593 | 0.17 | 0.1148 | 0.2202 | 0.8308 |
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+ | No log | 2.0 | 26 | 1.7887 | 0.13 | 0.8956 | 8.3211 | 0.13 | 0.0772 | 0.2024 | 0.8359 |
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+ | No log | 3.0 | 39 | 1.7450 | 0.225 | 0.8868 | 6.4554 | 0.225 | 0.1165 | 0.2502 | 0.7572 |
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+ | No log | 4.0 | 52 | 1.6811 | 0.24 | 0.8733 | 5.9510 | 0.24 | 0.0953 | 0.2651 | 0.6944 |
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+ | No log | 5.0 | 65 | 1.6411 | 0.19 | 0.8649 | 6.0993 | 0.19 | 0.0493 | 0.2422 | 0.7783 |
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+ | No log | 6.0 | 78 | 1.5475 | 0.195 | 0.8429 | 6.2065 | 0.195 | 0.0630 | 0.2472 | 0.7110 |
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+ | No log | 7.0 | 91 | 1.4688 | 0.3 | 0.8197 | 6.0345 | 0.3 | 0.1481 | 0.2936 | 0.5379 |
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+ | No log | 8.0 | 104 | 1.5036 | 0.285 | 0.8294 | 5.6660 | 0.285 | 0.1428 | 0.2869 | 0.6535 |
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+ | No log | 9.0 | 117 | 1.3901 | 0.34 | 0.7934 | 5.9107 | 0.34 | 0.1853 | 0.2894 | 0.5277 |
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+ | No log | 10.0 | 130 | 1.3484 | 0.37 | 0.7760 | 5.6441 | 0.37 | 0.2175 | 0.3177 | 0.5266 |
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+ | No log | 11.0 | 143 | 1.3375 | 0.34 | 0.7734 | 5.0872 | 0.34 | 0.2083 | 0.2902 | 0.5557 |
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+ | No log | 12.0 | 156 | 1.3639 | 0.305 | 0.7834 | 4.5070 | 0.305 | 0.1885 | 0.2674 | 0.6177 |
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+ | No log | 13.0 | 169 | 1.2321 | 0.415 | 0.7225 | 4.3464 | 0.415 | 0.2751 | 0.2943 | 0.3825 |
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+ | No log | 14.0 | 182 | 1.1453 | 0.44 | 0.6767 | 4.4158 | 0.44 | 0.2864 | 0.2617 | 0.3413 |
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+ | No log | 15.0 | 195 | 1.1830 | 0.43 | 0.6965 | 3.8251 | 0.4300 | 0.2972 | 0.2912 | 0.4239 |
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+ | No log | 16.0 | 208 | 1.0572 | 0.535 | 0.6230 | 3.5943 | 0.535 | 0.3758 | 0.2861 | 0.2291 |
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+ | No log | 17.0 | 221 | 1.0532 | 0.585 | 0.6151 | 3.3834 | 0.585 | 0.4331 | 0.3278 | 0.1879 |
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+ | No log | 18.0 | 234 | 1.0940 | 0.565 | 0.6374 | 3.2290 | 0.565 | 0.4431 | 0.3313 | 0.2415 |
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+ | No log | 19.0 | 247 | 0.9877 | 0.585 | 0.5886 | 3.1068 | 0.585 | 0.4564 | 0.2896 | 0.2110 |
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+ | No log | 20.0 | 260 | 1.0405 | 0.61 | 0.6056 | 3.1786 | 0.61 | 0.5038 | 0.3428 | 0.1962 |
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+ | No log | 21.0 | 273 | 0.9728 | 0.635 | 0.5634 | 2.9133 | 0.635 | 0.5293 | 0.3333 | 0.1664 |
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+ | No log | 22.0 | 286 | 0.9425 | 0.635 | 0.5527 | 2.8909 | 0.635 | 0.5237 | 0.3131 | 0.1796 |
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+ | No log | 23.0 | 299 | 0.9549 | 0.65 | 0.5605 | 2.8074 | 0.65 | 0.5539 | 0.3283 | 0.1914 |
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+ | No log | 24.0 | 312 | 1.0085 | 0.67 | 0.5733 | 2.8377 | 0.67 | 0.5543 | 0.3525 | 0.1571 |
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+ | No log | 25.0 | 325 | 0.9140 | 0.655 | 0.5257 | 2.5878 | 0.655 | 0.5603 | 0.3171 | 0.1495 |
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+ | No log | 26.0 | 338 | 0.8979 | 0.65 | 0.5249 | 2.7723 | 0.65 | 0.5563 | 0.2843 | 0.1646 |
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+ | No log | 27.0 | 351 | 0.8912 | 0.675 | 0.5082 | 2.6562 | 0.675 | 0.5837 | 0.2871 | 0.1380 |
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+ | No log | 28.0 | 364 | 0.8966 | 0.66 | 0.5242 | 2.3150 | 0.66 | 0.5890 | 0.3180 | 0.1777 |
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+ | No log | 29.0 | 377 | 0.8602 | 0.67 | 0.4959 | 2.5813 | 0.67 | 0.5866 | 0.3023 | 0.1319 |
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+ | No log | 30.0 | 390 | 0.8434 | 0.69 | 0.4779 | 2.5451 | 0.69 | 0.6130 | 0.3061 | 0.1188 |
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+ | No log | 31.0 | 403 | 0.8406 | 0.715 | 0.4782 | 2.3339 | 0.715 | 0.6438 | 0.3241 | 0.1092 |
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+ | No log | 32.0 | 416 | 0.8294 | 0.71 | 0.4726 | 2.5394 | 0.7100 | 0.6308 | 0.2922 | 0.1218 |
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+ | No log | 33.0 | 429 | 0.8329 | 0.68 | 0.4763 | 2.4520 | 0.68 | 0.6166 | 0.2592 | 0.1396 |
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+ | No log | 34.0 | 442 | 0.8937 | 0.69 | 0.5015 | 2.5649 | 0.69 | 0.6357 | 0.3293 | 0.1279 |
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+ | No log | 35.0 | 455 | 0.8358 | 0.665 | 0.4807 | 2.4437 | 0.665 | 0.6178 | 0.2380 | 0.1473 |
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+ | No log | 36.0 | 468 | 0.8283 | 0.685 | 0.4747 | 2.5408 | 0.685 | 0.6304 | 0.3126 | 0.1361 |
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+ | No log | 37.0 | 481 | 0.8235 | 0.685 | 0.4707 | 2.4620 | 0.685 | 0.6300 | 0.2757 | 0.1343 |
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+ | No log | 38.0 | 494 | 0.8289 | 0.68 | 0.4778 | 2.5443 | 0.68 | 0.6305 | 0.2935 | 0.1469 |
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+ | 0.9462 | 39.0 | 507 | 0.8373 | 0.69 | 0.4728 | 2.5775 | 0.69 | 0.6281 | 0.3028 | 0.1149 |
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+ | 0.9462 | 40.0 | 520 | 0.8062 | 0.715 | 0.4548 | 2.3673 | 0.715 | 0.6587 | 0.2776 | 0.1133 |
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+ | 0.9462 | 41.0 | 533 | 0.7990 | 0.705 | 0.4517 | 2.3284 | 0.705 | 0.6463 | 0.2716 | 0.1185 |
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+ | 0.9462 | 42.0 | 546 | 0.8210 | 0.7 | 0.4650 | 2.5646 | 0.7 | 0.6432 | 0.2690 | 0.1199 |
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+ | 0.9462 | 43.0 | 559 | 0.8102 | 0.695 | 0.4558 | 2.5651 | 0.695 | 0.6442 | 0.2656 | 0.1184 |
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+ | 0.9462 | 44.0 | 572 | 0.8061 | 0.69 | 0.4566 | 2.5154 | 0.69 | 0.6356 | 0.2816 | 0.1267 |
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+ | 0.9462 | 45.0 | 585 | 0.8018 | 0.7 | 0.4531 | 2.4982 | 0.7 | 0.6419 | 0.2696 | 0.1192 |
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+ | 0.9462 | 46.0 | 598 | 0.8040 | 0.7 | 0.4521 | 2.5309 | 0.7 | 0.6448 | 0.2797 | 0.1166 |
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+ | 0.9462 | 47.0 | 611 | 0.8062 | 0.68 | 0.4560 | 2.5452 | 0.68 | 0.6370 | 0.2744 | 0.1217 |
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+ | 0.9462 | 48.0 | 624 | 0.8011 | 0.69 | 0.4529 | 2.4281 | 0.69 | 0.6402 | 0.2594 | 0.1224 |
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+ | 0.9462 | 49.0 | 637 | 0.8017 | 0.69 | 0.4532 | 2.4239 | 0.69 | 0.6400 | 0.2613 | 0.1261 |
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+ | 0.9462 | 50.0 | 650 | 0.8009 | 0.695 | 0.4518 | 2.3840 | 0.695 | 0.6406 | 0.2661 | 0.1211 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.33.3
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+ - Pytorch 2.2.0.dev20231002
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+ - Datasets 2.7.1
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+ - Tokenizers 0.13.3
config.json ADDED
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+ {
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+ "_name_or_path": "microsoft/resnet-50",
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+ "architectures": [
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+ "ResNetForImageClassification"
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+ ],
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+ 4,
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+ "downsample_in_first_stage": false,
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+ "embedding_size": 64,
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+ "hidden_act": "relu",
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+ "hidden_sizes": [
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+ 256,
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+ 512,
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+ 1024,
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+ 2048
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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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+ "layer_type": "bottleneck",
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+ "model_type": "resnet",
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+ "num_channels": 3,
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+ "out_features": [
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+ "stage4"
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+ ],
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+ "out_indices": [
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+ 4
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+ "problem_type": "single_label_classification",
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+ "stage_names": [
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+ "stem",
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+ "stage1",
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+ "stage2",
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+ "stage3",
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+ "stage4"
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+ ],
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.33.3"
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+ }
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