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resnet101-base_tobacco-cnn_tobacco3482_kd_MSE

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_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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+ # resnet101-base_tobacco-cnn_tobacco3482_kd_MSE
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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: 0.0899
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+ - Accuracy: 0.395
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+ - Brier Loss: 0.6867
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+ - Nll: 4.7352
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+ - F1 Micro: 0.395
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+ - F1 Macro: 0.2347
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+ - Ece: 0.2366
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+ - Aurc: 0.3626
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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 | 1.1202 | 0.17 | 0.8964 | 8.4790 | 0.17 | 0.1089 | 0.2136 | 0.8244 |
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+ | No log | 2.0 | 26 | 1.0772 | 0.165 | 0.8950 | 8.2397 | 0.165 | 0.0929 | 0.2120 | 0.8534 |
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+ | No log | 3.0 | 39 | 0.9427 | 0.2 | 0.8847 | 7.1036 | 0.2000 | 0.0796 | 0.2384 | 0.7748 |
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+ | No log | 4.0 | 52 | 0.7947 | 0.21 | 0.8720 | 6.5481 | 0.2100 | 0.0649 | 0.2432 | 0.7270 |
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+ | No log | 5.0 | 65 | 0.5378 | 0.205 | 0.8432 | 6.3064 | 0.205 | 0.0544 | 0.2367 | 0.6763 |
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+ | No log | 6.0 | 78 | 0.4557 | 0.18 | 0.8402 | 6.3878 | 0.18 | 0.0308 | 0.2384 | 0.7467 |
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+ | No log | 7.0 | 91 | 0.4326 | 0.18 | 0.8383 | 6.3386 | 0.18 | 0.0308 | 0.2385 | 0.7234 |
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+ | No log | 8.0 | 104 | 0.2832 | 0.265 | 0.8085 | 6.3561 | 0.265 | 0.1012 | 0.2570 | 0.6272 |
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+ | No log | 9.0 | 117 | 0.2672 | 0.255 | 0.8124 | 6.2296 | 0.255 | 0.0981 | 0.2569 | 0.6567 |
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+ | No log | 10.0 | 130 | 0.2452 | 0.29 | 0.7953 | 6.3199 | 0.29 | 0.1153 | 0.2717 | 0.5884 |
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+ | No log | 11.0 | 143 | 0.2155 | 0.31 | 0.7764 | 6.3618 | 0.31 | 0.1231 | 0.2728 | 0.4803 |
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+ | No log | 12.0 | 156 | 0.1315 | 0.31 | 0.7371 | 6.2610 | 0.31 | 0.1231 | 0.2343 | 0.4419 |
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+ | No log | 13.0 | 169 | 0.1803 | 0.3 | 0.7665 | 6.1189 | 0.3 | 0.1187 | 0.2587 | 0.4579 |
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+ | No log | 14.0 | 182 | 0.1426 | 0.31 | 0.7386 | 6.1115 | 0.31 | 0.1236 | 0.2502 | 0.4341 |
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+ | No log | 15.0 | 195 | 0.1431 | 0.31 | 0.7334 | 5.9353 | 0.31 | 0.1274 | 0.2624 | 0.4233 |
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+ | No log | 16.0 | 208 | 0.1540 | 0.32 | 0.7318 | 5.7102 | 0.32 | 0.1432 | 0.2493 | 0.4322 |
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+ | No log | 17.0 | 221 | 0.2603 | 0.305 | 0.7784 | 5.6776 | 0.305 | 0.1361 | 0.2751 | 0.5118 |
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+ | No log | 18.0 | 234 | 0.1000 | 0.35 | 0.7074 | 5.4636 | 0.35 | 0.1574 | 0.2420 | 0.4027 |
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+ | No log | 19.0 | 247 | 0.1014 | 0.33 | 0.7131 | 5.5297 | 0.33 | 0.1413 | 0.2439 | 0.4245 |
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+ | No log | 20.0 | 260 | 0.2862 | 0.265 | 0.8013 | 5.5041 | 0.265 | 0.1126 | 0.2762 | 0.6324 |
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+ | No log | 21.0 | 273 | 0.1224 | 0.34 | 0.7183 | 5.2027 | 0.34 | 0.1544 | 0.2673 | 0.4222 |
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+ | No log | 22.0 | 286 | 0.1406 | 0.345 | 0.7173 | 5.1426 | 0.345 | 0.1612 | 0.2710 | 0.4019 |
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+ | No log | 23.0 | 299 | 0.1509 | 0.34 | 0.7270 | 5.0281 | 0.34 | 0.1565 | 0.2641 | 0.4178 |
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+ | No log | 24.0 | 312 | 0.0994 | 0.37 | 0.6996 | 5.1278 | 0.37 | 0.1771 | 0.2390 | 0.3930 |
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+ | No log | 25.0 | 325 | 0.1965 | 0.35 | 0.7474 | 5.0356 | 0.35 | 0.1707 | 0.2774 | 0.4503 |
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+ | No log | 26.0 | 338 | 0.1104 | 0.37 | 0.7085 | 5.0275 | 0.37 | 0.1984 | 0.2663 | 0.3927 |
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+ | No log | 27.0 | 351 | 0.1674 | 0.34 | 0.7299 | 4.9200 | 0.34 | 0.1739 | 0.2787 | 0.4257 |
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+ | No log | 28.0 | 364 | 0.2424 | 0.335 | 0.7626 | 5.0286 | 0.335 | 0.1693 | 0.2905 | 0.5297 |
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+ | No log | 29.0 | 377 | 0.1261 | 0.345 | 0.7185 | 5.0591 | 0.345 | 0.1730 | 0.2892 | 0.4142 |
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+ | No log | 30.0 | 390 | 0.1574 | 0.365 | 0.7213 | 4.8809 | 0.3650 | 0.1951 | 0.2983 | 0.4062 |
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+ | No log | 31.0 | 403 | 0.1227 | 0.365 | 0.7098 | 4.8152 | 0.3650 | 0.1996 | 0.2802 | 0.3992 |
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+ | No log | 32.0 | 416 | 0.1114 | 0.355 | 0.7010 | 4.8224 | 0.3550 | 0.1915 | 0.2657 | 0.3958 |
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+ | No log | 33.0 | 429 | 0.1027 | 0.39 | 0.6934 | 4.7755 | 0.39 | 0.2245 | 0.2653 | 0.3695 |
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+ | No log | 34.0 | 442 | 0.0959 | 0.385 | 0.6875 | 4.8715 | 0.3850 | 0.2299 | 0.2591 | 0.3699 |
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+ | No log | 35.0 | 455 | 0.0905 | 0.395 | 0.6897 | 4.8649 | 0.395 | 0.2367 | 0.2519 | 0.3627 |
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+ | No log | 36.0 | 468 | 0.0879 | 0.365 | 0.6911 | 4.8472 | 0.3650 | 0.2132 | 0.2437 | 0.3910 |
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+ | No log | 37.0 | 481 | 0.0867 | 0.39 | 0.6881 | 4.7379 | 0.39 | 0.2335 | 0.2576 | 0.3680 |
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+ | No log | 38.0 | 494 | 0.0934 | 0.4 | 0.6916 | 4.6797 | 0.4000 | 0.2490 | 0.2578 | 0.3628 |
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+ | 0.2032 | 39.0 | 507 | 0.0928 | 0.38 | 0.6901 | 4.6734 | 0.38 | 0.2268 | 0.2432 | 0.3783 |
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+ | 0.2032 | 40.0 | 520 | 0.0995 | 0.39 | 0.6875 | 4.8180 | 0.39 | 0.2323 | 0.2647 | 0.3730 |
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+ | 0.2032 | 41.0 | 533 | 0.0944 | 0.37 | 0.6892 | 4.8193 | 0.37 | 0.2174 | 0.2536 | 0.3862 |
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+ | 0.2032 | 42.0 | 546 | 0.0904 | 0.415 | 0.6885 | 4.5644 | 0.415 | 0.2556 | 0.2729 | 0.3573 |
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+ | 0.2032 | 43.0 | 559 | 0.0951 | 0.39 | 0.6899 | 4.6549 | 0.39 | 0.2417 | 0.2525 | 0.3692 |
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+ | 0.2032 | 44.0 | 572 | 0.0884 | 0.4 | 0.6860 | 4.6572 | 0.4000 | 0.2402 | 0.2587 | 0.3557 |
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+ | 0.2032 | 45.0 | 585 | 0.0867 | 0.38 | 0.6874 | 4.6558 | 0.38 | 0.2278 | 0.2526 | 0.3738 |
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+ | 0.2032 | 46.0 | 598 | 0.0861 | 0.405 | 0.6844 | 4.5777 | 0.405 | 0.2537 | 0.2548 | 0.3628 |
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+ | 0.2032 | 47.0 | 611 | 0.0874 | 0.385 | 0.6853 | 4.4946 | 0.3850 | 0.2380 | 0.2570 | 0.3743 |
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+ | 0.2032 | 48.0 | 624 | 0.0880 | 0.405 | 0.6857 | 4.5605 | 0.405 | 0.2500 | 0.2489 | 0.3555 |
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+ | 0.2032 | 49.0 | 637 | 0.0884 | 0.4 | 0.6853 | 4.6057 | 0.4000 | 0.2481 | 0.2401 | 0.3616 |
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+ | 0.2032 | 50.0 | 650 | 0.0899 | 0.395 | 0.6867 | 4.7352 | 0.395 | 0.2347 | 0.2366 | 0.3626 |
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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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+ "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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+ "id2label": {
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+ "1": "Email",
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+ "2": "Form",
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+ "4": "Memo",
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+ "model_type": "resnet",
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+ "out_features": [
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+ "out_indices": [
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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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