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resnet101-base_tobacco-cnn_tobacco3482_kd

Image Classification
Transformers
Safetensors
resnet
Generated from Trainer
Inference Endpoints
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  1. README.md +116 -0
  2. config.json +65 -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: bdpc/resnet101-base_tobacco
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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
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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
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+
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+ This model is a fine-tuned version of [bdpc/resnet101-base_tobacco](https://huggingface.co/bdpc/resnet101-base_tobacco) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.8158
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+ - Accuracy: 0.565
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+ - Brier Loss: 0.6104
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+ - Nll: 2.6027
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+ - F1 Micro: 0.565
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+ - F1 Macro: 0.4783
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+ - Ece: 0.2677
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+ - Aurc: 0.2516
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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: 256
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+ - eval_batch_size: 256
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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 | 4 | 1.4988 | 0.065 | 0.9007 | 9.6504 | 0.065 | 0.0267 | 0.1512 | 0.9377 |
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+ | No log | 2.0 | 8 | 1.4615 | 0.155 | 0.8961 | 7.9200 | 0.155 | 0.0268 | 0.2328 | 0.9605 |
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+ | No log | 3.0 | 12 | 1.4913 | 0.155 | 0.9531 | 11.6402 | 0.155 | 0.0268 | 0.3390 | 0.8899 |
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+ | No log | 4.0 | 16 | 2.2747 | 0.155 | 1.4111 | 11.0294 | 0.155 | 0.0268 | 0.7077 | 0.7068 |
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+ | No log | 5.0 | 20 | 2.4543 | 0.155 | 1.4359 | 8.3074 | 0.155 | 0.0268 | 0.7226 | 0.6151 |
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+ | No log | 6.0 | 24 | 1.9614 | 0.155 | 1.1785 | 6.6431 | 0.155 | 0.0283 | 0.5497 | 0.6022 |
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+ | No log | 7.0 | 28 | 1.6280 | 0.18 | 0.9978 | 5.8468 | 0.18 | 0.0488 | 0.4014 | 0.6135 |
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+ | No log | 8.0 | 32 | 1.3465 | 0.225 | 0.8993 | 5.6177 | 0.225 | 0.0740 | 0.3378 | 0.5786 |
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+ | No log | 9.0 | 36 | 1.2597 | 0.225 | 0.8794 | 5.0542 | 0.225 | 0.0727 | 0.3403 | 0.5658 |
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+ | No log | 10.0 | 40 | 1.1149 | 0.27 | 0.8181 | 4.5188 | 0.27 | 0.1222 | 0.2890 | 0.5230 |
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+ | No log | 11.0 | 44 | 0.9805 | 0.31 | 0.7600 | 3.8687 | 0.31 | 0.1726 | 0.2703 | 0.4690 |
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+ | No log | 12.0 | 48 | 1.0099 | 0.335 | 0.7732 | 3.6652 | 0.335 | 0.2095 | 0.2892 | 0.4739 |
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+ | No log | 13.0 | 52 | 1.0522 | 0.335 | 0.7919 | 3.3843 | 0.335 | 0.2562 | 0.3006 | 0.6402 |
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+ | No log | 14.0 | 56 | 1.0566 | 0.32 | 0.7868 | 3.4244 | 0.32 | 0.2373 | 0.3023 | 0.6094 |
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+ | No log | 15.0 | 60 | 0.9670 | 0.405 | 0.7333 | 3.3926 | 0.405 | 0.3189 | 0.3013 | 0.4037 |
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+ | No log | 16.0 | 64 | 1.0979 | 0.31 | 0.7877 | 3.3045 | 0.31 | 0.2262 | 0.2792 | 0.5720 |
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+ | No log | 17.0 | 68 | 0.9022 | 0.44 | 0.6913 | 3.2277 | 0.44 | 0.3429 | 0.2902 | 0.3657 |
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+ | No log | 18.0 | 72 | 1.2120 | 0.315 | 0.8075 | 4.1289 | 0.315 | 0.2323 | 0.2857 | 0.5909 |
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+ | No log | 19.0 | 76 | 1.1945 | 0.39 | 0.7974 | 4.2350 | 0.39 | 0.3292 | 0.3271 | 0.5989 |
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+ | No log | 20.0 | 80 | 1.3861 | 0.345 | 0.7981 | 5.2605 | 0.345 | 0.2700 | 0.2832 | 0.5299 |
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+ | No log | 21.0 | 84 | 1.2243 | 0.33 | 0.8073 | 4.5262 | 0.33 | 0.2545 | 0.3068 | 0.6133 |
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+ | No log | 22.0 | 88 | 1.0455 | 0.38 | 0.7238 | 2.7133 | 0.38 | 0.3084 | 0.2901 | 0.4855 |
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+ | No log | 23.0 | 92 | 0.9044 | 0.45 | 0.6814 | 3.4361 | 0.45 | 0.3273 | 0.2927 | 0.3246 |
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+ | No log | 24.0 | 96 | 0.8930 | 0.495 | 0.6596 | 3.3412 | 0.495 | 0.4185 | 0.2882 | 0.3070 |
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+ | No log | 25.0 | 100 | 0.8665 | 0.485 | 0.6534 | 2.9998 | 0.485 | 0.4154 | 0.2641 | 0.3298 |
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+ | No log | 26.0 | 104 | 1.0458 | 0.375 | 0.7579 | 3.1074 | 0.375 | 0.3333 | 0.2735 | 0.5293 |
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+ | No log | 27.0 | 108 | 1.0170 | 0.41 | 0.7321 | 2.8884 | 0.41 | 0.3468 | 0.2976 | 0.4566 |
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+ | No log | 28.0 | 112 | 1.0956 | 0.395 | 0.7464 | 3.3094 | 0.395 | 0.3255 | 0.3154 | 0.4684 |
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+ | No log | 29.0 | 116 | 1.0805 | 0.39 | 0.7544 | 3.2115 | 0.39 | 0.3193 | 0.3014 | 0.4594 |
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+ | No log | 30.0 | 120 | 1.2358 | 0.375 | 0.7733 | 4.3992 | 0.375 | 0.3058 | 0.2845 | 0.4876 |
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+ | No log | 31.0 | 124 | 1.0532 | 0.4 | 0.7458 | 2.7398 | 0.4000 | 0.3614 | 0.2890 | 0.4961 |
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+ | No log | 32.0 | 128 | 1.0166 | 0.365 | 0.7355 | 2.5093 | 0.3650 | 0.2862 | 0.2728 | 0.5057 |
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+ | No log | 33.0 | 132 | 0.9395 | 0.48 | 0.6807 | 2.6211 | 0.48 | 0.4394 | 0.2843 | 0.3719 |
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+ | No log | 34.0 | 136 | 0.8718 | 0.52 | 0.6538 | 2.6802 | 0.52 | 0.4697 | 0.2954 | 0.3051 |
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+ | No log | 35.0 | 140 | 0.8339 | 0.51 | 0.6362 | 3.1084 | 0.51 | 0.4373 | 0.2654 | 0.3006 |
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+ | No log | 36.0 | 144 | 0.8411 | 0.51 | 0.6359 | 2.7881 | 0.51 | 0.4286 | 0.2759 | 0.2906 |
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+ | No log | 37.0 | 148 | 0.8556 | 0.505 | 0.6402 | 2.5519 | 0.505 | 0.4076 | 0.2522 | 0.3060 |
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+ | No log | 38.0 | 152 | 1.0928 | 0.395 | 0.7438 | 2.8660 | 0.395 | 0.3337 | 0.2815 | 0.4724 |
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+ | No log | 39.0 | 156 | 1.3830 | 0.39 | 0.8135 | 4.7392 | 0.39 | 0.3094 | 0.2879 | 0.5239 |
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+ | No log | 40.0 | 160 | 1.2180 | 0.38 | 0.7760 | 3.8384 | 0.38 | 0.3106 | 0.2614 | 0.5109 |
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+ | No log | 41.0 | 164 | 1.1337 | 0.365 | 0.7486 | 2.8843 | 0.3650 | 0.2948 | 0.2665 | 0.4630 |
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+ | No log | 42.0 | 168 | 0.8814 | 0.53 | 0.6425 | 2.3353 | 0.53 | 0.4645 | 0.2968 | 0.2973 |
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+ | No log | 43.0 | 172 | 0.8324 | 0.515 | 0.6174 | 2.4407 | 0.515 | 0.4517 | 0.2847 | 0.2742 |
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+ | No log | 44.0 | 176 | 0.8477 | 0.53 | 0.6282 | 2.5469 | 0.53 | 0.4615 | 0.2712 | 0.2831 |
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+ | No log | 45.0 | 180 | 0.8307 | 0.515 | 0.6190 | 2.4871 | 0.515 | 0.4404 | 0.2594 | 0.2845 |
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+ | No log | 46.0 | 184 | 0.8116 | 0.53 | 0.6070 | 2.4944 | 0.53 | 0.4410 | 0.2337 | 0.2451 |
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+ | No log | 47.0 | 188 | 0.8349 | 0.54 | 0.6260 | 2.2843 | 0.54 | 0.4423 | 0.2911 | 0.2616 |
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+ | No log | 48.0 | 192 | 0.8298 | 0.555 | 0.6178 | 2.2946 | 0.555 | 0.4725 | 0.2568 | 0.2482 |
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+ | No log | 49.0 | 196 | 0.8252 | 0.565 | 0.6141 | 2.3311 | 0.565 | 0.4762 | 0.2810 | 0.2504 |
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+ | No log | 50.0 | 200 | 0.8158 | 0.565 | 0.6104 | 2.6027 | 0.565 | 0.4783 | 0.2677 | 0.2516 |
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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": "bdpc/resnet101-base_tobacco",
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+ "ResNetForImageClassification"
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+ "3": "Letter",
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+ "4": "Memo",
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+ "transformers_version": "4.36.0.dev0"
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