--- license: apache-2.0 base_model: microsoft/resnet-50 tags: - generated_from_trainer metrics: - accuracy model-index: - name: resnet101_rvl-cdip-cnn_rvl_cdip-NK1000_kd results: [] --- # resnet101_rvl-cdip-cnn_rvl_cdip-NK1000_kd This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.6048 - Accuracy: 0.7867 - Brier Loss: 0.3046 - Nll: 2.0167 - F1 Micro: 0.7868 - F1 Macro: 0.7867 - Ece: 0.0468 - Aurc: 0.0597 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0001 - train_batch_size: 64 - eval_batch_size: 64 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 50 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | Brier Loss | Nll | F1 Micro | F1 Macro | Ece | Aurc | |:-------------:|:-----:|:-----:|:---------------:|:--------:|:----------:|:------:|:--------:|:--------:|:------:|:------:| | No log | 1.0 | 250 | 4.1589 | 0.1305 | 0.9320 | 7.8922 | 0.1305 | 0.0928 | 0.0637 | 0.8337 | | 4.1546 | 2.0 | 500 | 3.6898 | 0.3515 | 0.8840 | 4.7696 | 0.3515 | 0.3150 | 0.2354 | 0.5486 | | 4.1546 | 3.0 | 750 | 2.3450 | 0.4863 | 0.6606 | 3.2068 | 0.4863 | 0.4495 | 0.0978 | 0.2927 | | 2.419 | 4.0 | 1000 | 1.5206 | 0.6125 | 0.5126 | 2.7884 | 0.6125 | 0.5996 | 0.0512 | 0.1677 | | 2.419 | 5.0 | 1250 | 1.2545 | 0.6593 | 0.4574 | 2.6041 | 0.6593 | 0.6524 | 0.0483 | 0.1337 | | 1.1615 | 6.0 | 1500 | 0.9718 | 0.704 | 0.4062 | 2.4047 | 0.704 | 0.7017 | 0.0506 | 0.1043 | | 1.1615 | 7.0 | 1750 | 0.8636 | 0.73 | 0.3760 | 2.1975 | 0.7300 | 0.7304 | 0.0522 | 0.0902 | | 0.7217 | 8.0 | 2000 | 0.7892 | 0.737 | 0.3632 | 2.1583 | 0.737 | 0.7377 | 0.0551 | 0.0835 | | 0.7217 | 9.0 | 2250 | 0.7438 | 0.754 | 0.3470 | 2.0559 | 0.754 | 0.7531 | 0.0534 | 0.0766 | | 0.5268 | 10.0 | 2500 | 0.7322 | 0.758 | 0.3443 | 2.1043 | 0.7580 | 0.7584 | 0.0510 | 0.0742 | | 0.5268 | 11.0 | 2750 | 0.7003 | 0.7632 | 0.3335 | 2.0510 | 0.7632 | 0.7639 | 0.0472 | 0.0697 | | 0.4197 | 12.0 | 3000 | 0.6921 | 0.7665 | 0.3325 | 2.0569 | 0.7665 | 0.7668 | 0.0568 | 0.0694 | | 0.4197 | 13.0 | 3250 | 0.7003 | 0.7618 | 0.3330 | 2.0293 | 0.7618 | 0.7618 | 0.0465 | 0.0721 | | 0.3575 | 14.0 | 3500 | 0.6681 | 0.7728 | 0.3244 | 2.0037 | 0.7728 | 0.7739 | 0.0505 | 0.0664 | | 0.3575 | 15.0 | 3750 | 0.6862 | 0.7718 | 0.3279 | 2.0294 | 0.7717 | 0.7727 | 0.0442 | 0.0693 | | 0.3181 | 16.0 | 4000 | 0.6681 | 0.7738 | 0.3246 | 2.0559 | 0.7738 | 0.7739 | 0.0509 | 0.0671 | | 0.3181 | 17.0 | 4250 | 0.6473 | 0.7775 | 0.3177 | 1.9978 | 0.7775 | 0.7784 | 0.0494 | 0.0644 | | 0.2874 | 18.0 | 4500 | 0.6448 | 0.78 | 0.3172 | 2.0396 | 0.78 | 0.7805 | 0.0495 | 0.0651 | | 0.2874 | 19.0 | 4750 | 0.6484 | 0.779 | 0.3153 | 2.0251 | 0.779 | 0.7790 | 0.0519 | 0.0636 | | 0.2691 | 20.0 | 5000 | 0.6430 | 0.7768 | 0.3164 | 2.0897 | 0.7768 | 0.7771 | 0.0489 | 0.0635 | | 0.2691 | 21.0 | 5250 | 0.6363 | 0.78 | 0.3145 | 2.0663 | 0.78 | 0.7802 | 0.0476 | 0.0640 | | 0.2509 | 22.0 | 5500 | 0.6327 | 0.782 | 0.3127 | 2.0358 | 0.782 | 0.7820 | 0.0440 | 0.0634 | | 0.2509 | 23.0 | 5750 | 0.6287 | 0.7863 | 0.3113 | 2.0157 | 0.7863 | 0.7865 | 0.0463 | 0.0630 | | 0.2393 | 24.0 | 6000 | 0.6315 | 0.7778 | 0.3137 | 2.0623 | 0.7778 | 0.7773 | 0.0492 | 0.0633 | | 0.2393 | 25.0 | 6250 | 0.6345 | 0.7775 | 0.3149 | 2.0397 | 0.7775 | 0.7773 | 0.0514 | 0.0635 | | 0.2291 | 26.0 | 6500 | 0.6233 | 0.7815 | 0.3102 | 1.9988 | 0.7815 | 0.7816 | 0.0444 | 0.0626 | | 0.2291 | 27.0 | 6750 | 0.6224 | 0.783 | 0.3095 | 2.0085 | 0.7830 | 0.7830 | 0.0502 | 0.0615 | | 0.2191 | 28.0 | 7000 | 0.6159 | 0.7835 | 0.3089 | 2.0340 | 0.7835 | 0.7834 | 0.0499 | 0.0614 | | 0.2191 | 29.0 | 7250 | 0.6203 | 0.7825 | 0.3096 | 2.0280 | 0.7825 | 0.7825 | 0.0480 | 0.0617 | | 0.2139 | 30.0 | 7500 | 0.6233 | 0.7802 | 0.3093 | 2.0660 | 0.7802 | 0.7805 | 0.0518 | 0.0609 | | 0.2139 | 31.0 | 7750 | 0.6128 | 0.785 | 0.3049 | 2.0148 | 0.785 | 0.7851 | 0.0471 | 0.0604 | | 0.2068 | 32.0 | 8000 | 0.6124 | 0.7855 | 0.3064 | 2.0336 | 0.7855 | 0.7855 | 0.0433 | 0.0604 | | 0.2068 | 33.0 | 8250 | 0.6117 | 0.7835 | 0.3068 | 2.0208 | 0.7835 | 0.7833 | 0.0469 | 0.0604 | | 0.202 | 34.0 | 8500 | 0.6105 | 0.7857 | 0.3063 | 1.9918 | 0.7857 | 0.7854 | 0.0454 | 0.0611 | | 0.202 | 35.0 | 8750 | 0.6136 | 0.7877 | 0.3088 | 2.0272 | 0.7877 | 0.7884 | 0.0444 | 0.0607 | | 0.1974 | 36.0 | 9000 | 0.6095 | 0.786 | 0.3052 | 2.0275 | 0.786 | 0.7862 | 0.0423 | 0.0600 | | 0.1974 | 37.0 | 9250 | 0.6108 | 0.786 | 0.3077 | 2.0035 | 0.786 | 0.7860 | 0.0477 | 0.0606 | | 0.1945 | 38.0 | 9500 | 0.6107 | 0.7817 | 0.3078 | 2.0042 | 0.7817 | 0.7820 | 0.0482 | 0.0611 | | 0.1945 | 39.0 | 9750 | 0.6077 | 0.7875 | 0.3051 | 1.9959 | 0.7875 | 0.7878 | 0.0510 | 0.0599 | | 0.1919 | 40.0 | 10000 | 0.6099 | 0.7863 | 0.3072 | 2.0323 | 0.7863 | 0.7866 | 0.0468 | 0.0603 | | 0.1919 | 41.0 | 10250 | 0.6046 | 0.7847 | 0.3046 | 2.0113 | 0.7847 | 0.7850 | 0.0442 | 0.0600 | | 0.1874 | 42.0 | 10500 | 0.6062 | 0.7865 | 0.3059 | 2.0055 | 0.7865 | 0.7865 | 0.0486 | 0.0598 | | 0.1874 | 43.0 | 10750 | 0.6051 | 0.787 | 0.3042 | 2.0151 | 0.787 | 0.7870 | 0.0451 | 0.0596 | | 0.1859 | 44.0 | 11000 | 0.6082 | 0.7855 | 0.3063 | 2.0123 | 0.7855 | 0.7860 | 0.0470 | 0.0600 | | 0.1859 | 45.0 | 11250 | 0.6066 | 0.7867 | 0.3047 | 2.0000 | 0.7868 | 0.7865 | 0.0479 | 0.0599 | | 0.1856 | 46.0 | 11500 | 0.6049 | 0.7863 | 0.3054 | 2.0058 | 0.7863 | 0.7861 | 0.0475 | 0.0598 | | 0.1856 | 47.0 | 11750 | 0.6041 | 0.7887 | 0.3047 | 1.9992 | 0.7887 | 0.7891 | 0.0482 | 0.0595 | | 0.1842 | 48.0 | 12000 | 0.6063 | 0.7843 | 0.3055 | 2.0346 | 0.7843 | 0.7843 | 0.0480 | 0.0601 | | 0.1842 | 49.0 | 12250 | 0.6058 | 0.786 | 0.3051 | 2.0319 | 0.786 | 0.7861 | 0.0481 | 0.0598 | | 0.1829 | 50.0 | 12500 | 0.6048 | 0.7867 | 0.3046 | 2.0167 | 0.7868 | 0.7867 | 0.0468 | 0.0597 | ### Framework versions - Transformers 4.33.3 - Pytorch 2.2.0.dev20231002 - Datasets 2.7.1 - Tokenizers 0.13.3