--- library_name: transformers license: cc-by-nc-4.0 base_model: beingbatman/MAE-CT-M1N0-v11 tags: - generated_from_trainer metrics: - accuracy model-index: - name: MAE-CT-M1N0-v11 results: [] --- # MAE-CT-M1N0-v11 This model is a fine-tuned version of [beingbatman/MAE-CT-M1N0-v11](https://huggingface.co/beingbatman/MAE-CT-M1N0-v11) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 1.9107 - Accuracy: 0.7407 ## 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: 1e-05 - train_batch_size: 4 - eval_batch_size: 4 - seed: 42 - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - training_steps: 6600 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-------:|:----:|:---------------:|:--------:| | 0.0957 | 0.0102 | 67 | 1.0947 | 0.6176 | | 0.2452 | 1.0102 | 134 | 1.1772 | 0.6765 | | 0.5144 | 2.0102 | 201 | 1.5596 | 0.6471 | | 0.1315 | 3.0102 | 268 | 1.4470 | 0.5588 | | 0.0398 | 4.0102 | 335 | 1.5700 | 0.5882 | | 0.1834 | 5.0102 | 402 | 1.2757 | 0.7059 | | 0.1818 | 6.0102 | 469 | 1.5364 | 0.7059 | | 0.0496 | 7.0102 | 536 | 1.6521 | 0.7353 | | 0.0009 | 8.0102 | 603 | 1.8430 | 0.6765 | | 0.141 | 9.0102 | 670 | 2.2428 | 0.6176 | | 0.0338 | 10.0102 | 737 | 2.3844 | 0.6176 | | 0.0353 | 11.0102 | 804 | 2.0932 | 0.7059 | | 0.3218 | 12.0102 | 871 | 2.0158 | 0.6471 | | 0.1485 | 13.0102 | 938 | 1.8430 | 0.6176 | | 0.004 | 14.0102 | 1005 | 2.1836 | 0.5882 | | 0.1743 | 15.0102 | 1072 | 2.1859 | 0.6471 | | 0.0932 | 16.0102 | 1139 | 1.6879 | 0.7353 | | 0.0039 | 17.0102 | 1206 | 2.0492 | 0.6471 | | 0.2276 | 18.0102 | 1273 | 2.2761 | 0.5882 | | 0.5771 | 19.0102 | 1340 | 2.5674 | 0.6471 | | 0.1686 | 20.0102 | 1407 | 2.2761 | 0.6471 | | 0.3135 | 21.0102 | 1474 | 2.2901 | 0.6176 | | 0.0004 | 22.0102 | 1541 | 2.1465 | 0.7353 | | 0.1221 | 23.0102 | 1608 | 2.2524 | 0.6471 | | 0.0717 | 24.0102 | 1675 | 2.5812 | 0.5882 | | 0.0763 | 25.0102 | 1742 | 2.9429 | 0.6176 | | 0.0001 | 26.0102 | 1809 | 2.3691 | 0.7059 | | 0.3076 | 27.0102 | 1876 | 2.7487 | 0.6176 | | 0.2701 | 28.0102 | 1943 | 2.1523 | 0.6471 | | 0.0018 | 29.0102 | 2010 | 2.9072 | 0.6176 | | 0.096 | 30.0102 | 2077 | 2.9151 | 0.5882 | | 0.2654 | 31.0102 | 2144 | 2.8686 | 0.6471 | | 0.0002 | 32.0102 | 2211 | 2.6399 | 0.6471 | | 0.0002 | 33.0102 | 2278 | 2.7440 | 0.6471 | | 0.0113 | 34.0102 | 2345 | 2.5598 | 0.6471 | | 0.0001 | 35.0102 | 2412 | 2.9623 | 0.5882 | | 0.1484 | 36.0102 | 2479 | 2.5132 | 0.6765 | | 0.0001 | 37.0102 | 2546 | 2.7195 | 0.6176 | | 0.0004 | 38.0102 | 2613 | 1.9358 | 0.7647 | | 0.0 | 39.0102 | 2680 | 2.6720 | 0.6471 | | 0.0 | 40.0102 | 2747 | 2.9154 | 0.6176 | | 0.0 | 41.0102 | 2814 | 2.9176 | 0.6176 | | 0.0 | 42.0102 | 2881 | 2.9299 | 0.6176 | | 0.0 | 43.0102 | 2948 | 2.8822 | 0.5882 | | 0.0007 | 44.0102 | 3015 | 3.0881 | 0.6176 | | 0.0001 | 45.0102 | 3082 | 3.3474 | 0.5882 | | 0.0 | 46.0102 | 3149 | 3.2999 | 0.5882 | | 0.0005 | 47.0102 | 3216 | 3.3930 | 0.5882 | | 0.0001 | 48.0102 | 3283 | 3.4111 | 0.5882 | | 0.0245 | 49.0102 | 3350 | 3.1914 | 0.6176 | | 0.0003 | 50.0102 | 3417 | 3.0377 | 0.6765 | | 0.0024 | 51.0102 | 3484 | 3.2830 | 0.5882 | | 0.0001 | 52.0102 | 3551 | 2.5779 | 0.7059 | | 0.0001 | 53.0102 | 3618 | 3.5160 | 0.5588 | | 0.0 | 54.0102 | 3685 | 3.4892 | 0.5882 | | 0.0 | 55.0102 | 3752 | 3.3148 | 0.5882 | | 0.0 | 56.0102 | 3819 | 3.3751 | 0.5882 | | 0.2024 | 57.0102 | 3886 | 3.4587 | 0.6176 | | 0.0009 | 58.0102 | 3953 | 3.2979 | 0.5882 | | 0.0 | 59.0102 | 4020 | 3.5841 | 0.5882 | | 0.0001 | 60.0102 | 4087 | 3.4411 | 0.5882 | | 0.0006 | 61.0102 | 4154 | 3.0952 | 0.6471 | | 0.0 | 62.0102 | 4221 | 3.2242 | 0.5882 | | 0.0947 | 63.0102 | 4288 | 3.1971 | 0.6176 | | 0.0 | 64.0102 | 4355 | 3.3249 | 0.5882 | | 0.0 | 65.0102 | 4422 | 3.5612 | 0.5882 | | 0.0 | 66.0102 | 4489 | 3.6243 | 0.5882 | | 0.0 | 67.0102 | 4556 | 3.3772 | 0.6176 | | 0.0 | 68.0102 | 4623 | 3.4673 | 0.6176 | | 0.0 | 69.0102 | 4690 | 3.4033 | 0.6176 | | 0.0 | 70.0102 | 4757 | 3.2678 | 0.5882 | | 0.0 | 71.0102 | 4824 | 3.2038 | 0.6471 | | 0.135 | 72.0102 | 4891 | 2.8182 | 0.6176 | | 0.0 | 73.0102 | 4958 | 3.1443 | 0.6765 | | 0.0 | 74.0102 | 5025 | 3.7653 | 0.5882 | | 0.0 | 75.0102 | 5092 | 3.7835 | 0.5882 | | 0.0 | 76.0102 | 5159 | 3.7721 | 0.5882 | | 0.0 | 77.0102 | 5226 | 3.7777 | 0.5882 | | 0.0 | 78.0102 | 5293 | 3.7851 | 0.5882 | | 0.0 | 79.0102 | 5360 | 3.7914 | 0.5882 | | 0.0 | 80.0102 | 5427 | 3.7988 | 0.5882 | | 0.0 | 81.0102 | 5494 | 3.8051 | 0.5882 | | 0.0 | 82.0102 | 5561 | 3.8111 | 0.5882 | | 0.0 | 83.0102 | 5628 | 3.8290 | 0.5882 | | 0.0 | 84.0102 | 5695 | 3.8341 | 0.5882 | | 0.0 | 85.0102 | 5762 | 3.8388 | 0.5882 | | 0.0 | 86.0102 | 5829 | 3.8458 | 0.5882 | | 0.0 | 87.0102 | 5896 | 3.8484 | 0.5882 | | 0.0 | 88.0102 | 5963 | 3.8243 | 0.5882 | | 0.0 | 89.0102 | 6030 | 3.8309 | 0.5882 | | 0.0 | 90.0102 | 6097 | 3.8333 | 0.5882 | | 0.0 | 91.0102 | 6164 | 3.8336 | 0.5882 | | 0.0 | 92.0102 | 6231 | 3.8408 | 0.5882 | | 0.0 | 93.0102 | 6298 | 3.8428 | 0.5882 | | 0.0 | 94.0102 | 6365 | 3.8271 | 0.5882 | | 0.0 | 95.0102 | 6432 | 3.8282 | 0.5882 | | 0.0 | 96.0102 | 6499 | 3.8579 | 0.5882 | | 0.0028 | 97.0102 | 6566 | 3.8781 | 0.5882 | | 0.0 | 98.0052 | 6600 | 3.8801 | 0.5882 | ### Framework versions - Transformers 4.46.2 - Pytorch 2.0.1+cu117 - Datasets 3.0.1 - Tokenizers 0.20.0