--- library_name: transformers license: cc-by-nc-4.0 base_model: MCG-NJU/videomae-base tags: - generated_from_trainer metrics: - accuracy model-index: - name: videomae-base-finetuned-ucf101-subset results: [] --- # videomae-base-finetuned-ucf101-subset This model is a fine-tuned version of [MCG-NJU/videomae-base](https://huggingface.co/MCG-NJU/videomae-base) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 1.9989 - Accuracy: 0.5144 ## 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: 5e-05 - train_batch_size: 64 - eval_batch_size: 64 - 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: 1920 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:--------:|:----:|:---------------:|:--------:| | 4.2685 | 0.0083 | 16 | 4.2443 | 0.0144 | | 4.2462 | 1.0083 | 32 | 4.2229 | 0.0165 | | 4.2193 | 2.0083 | 48 | 4.2111 | 0.0129 | | 4.2251 | 3.0083 | 64 | 4.2124 | 0.0136 | | 4.231 | 4.0083 | 80 | 4.2131 | 0.0158 | | 4.2197 | 5.0083 | 96 | 4.2091 | 0.0151 | | 4.2239 | 6.0083 | 112 | 4.2100 | 0.0108 | | 4.2246 | 7.0083 | 128 | 4.2119 | 0.0144 | | 4.2131 | 8.0083 | 144 | 4.2030 | 0.0172 | | 4.236 | 9.0083 | 160 | 4.1979 | 0.0129 | | 4.177 | 10.0083 | 176 | 4.1328 | 0.0323 | | 4.0656 | 11.0083 | 192 | 4.0373 | 0.0316 | | 3.9339 | 12.0083 | 208 | 3.8848 | 0.0503 | | 3.7197 | 13.0083 | 224 | 3.7681 | 0.0783 | | 3.5657 | 14.0083 | 240 | 3.5790 | 0.1185 | | 3.3108 | 15.0083 | 256 | 3.5642 | 0.1466 | | 3.1687 | 16.0083 | 272 | 3.3210 | 0.1832 | | 3.1376 | 17.0083 | 288 | 3.1950 | 0.2292 | | 2.8366 | 18.0083 | 304 | 3.1270 | 0.2493 | | 2.6811 | 19.0083 | 320 | 2.9997 | 0.2895 | | 2.6104 | 20.0083 | 336 | 2.9776 | 0.2773 | | 2.5156 | 21.0083 | 352 | 2.8625 | 0.3125 | | 2.3804 | 22.0083 | 368 | 2.8223 | 0.2974 | | 2.2389 | 23.0083 | 384 | 2.7042 | 0.3412 | | 2.1889 | 24.0083 | 400 | 2.6846 | 0.3226 | | 1.9829 | 25.0083 | 416 | 2.6066 | 0.3592 | | 1.9466 | 26.0083 | 432 | 2.5845 | 0.3642 | | 1.8991 | 27.0083 | 448 | 2.5150 | 0.3922 | | 1.8629 | 28.0083 | 464 | 2.4958 | 0.3994 | | 1.8563 | 29.0083 | 480 | 2.5036 | 0.3994 | | 1.832 | 30.0083 | 496 | 2.4212 | 0.4037 | | 1.7148 | 31.0083 | 512 | 2.3891 | 0.4253 | | 1.6525 | 32.0083 | 528 | 2.3817 | 0.4109 | | 1.6489 | 33.0083 | 544 | 2.3351 | 0.4274 | | 1.6928 | 34.0083 | 560 | 2.3495 | 0.4188 | | 1.503 | 35.0083 | 576 | 2.2961 | 0.4274 | | 1.5126 | 36.0083 | 592 | 2.2620 | 0.4454 | | 1.4732 | 37.0083 | 608 | 2.2635 | 0.4368 | | 1.5553 | 38.0083 | 624 | 2.2326 | 0.4490 | | 1.7115 | 39.0083 | 640 | 2.2266 | 0.4404 | | 1.4851 | 40.0083 | 656 | 2.2690 | 0.4274 | | 1.455 | 41.0083 | 672 | 2.1921 | 0.4569 | | 1.4827 | 42.0083 | 688 | 2.2387 | 0.4504 | | 1.4839 | 43.0083 | 704 | 2.2020 | 0.4432 | | 1.2879 | 44.0083 | 720 | 2.1959 | 0.4397 | | 1.2722 | 45.0083 | 736 | 2.2158 | 0.4440 | | 1.2225 | 46.0083 | 752 | 2.1568 | 0.4662 | | 1.1821 | 47.0083 | 768 | 2.1312 | 0.4763 | | 1.2406 | 48.0083 | 784 | 2.1162 | 0.4784 | | 1.1717 | 49.0083 | 800 | 2.1368 | 0.4756 | | 1.2366 | 50.0083 | 816 | 2.1134 | 0.4835 | | 1.2534 | 51.0083 | 832 | 2.0964 | 0.4734 | | 1.2322 | 52.0083 | 848 | 2.1506 | 0.4641 | | 1.2742 | 53.0083 | 864 | 2.1719 | 0.4591 | | 1.132 | 54.0083 | 880 | 2.1557 | 0.4648 | | 1.1306 | 55.0083 | 896 | 2.1010 | 0.4878 | | 1.2719 | 56.0083 | 912 | 2.1482 | 0.4619 | | 1.1549 | 57.0083 | 928 | 2.0961 | 0.4813 | | 1.1495 | 58.0083 | 944 | 2.1246 | 0.4763 | | 1.2539 | 59.0083 | 960 | 2.1118 | 0.4806 | | 1.1719 | 60.0083 | 976 | 2.0666 | 0.4935 | | 1.1108 | 61.0083 | 992 | 2.0630 | 0.4835 | | 1.0417 | 62.0083 | 1008 | 2.0635 | 0.4899 | | 1.1755 | 63.0083 | 1024 | 2.0862 | 0.4720 | | 1.0512 | 64.0083 | 1040 | 2.0730 | 0.4878 | | 0.9824 | 65.0083 | 1056 | 2.0709 | 0.4907 | | 1.0924 | 66.0083 | 1072 | 2.1638 | 0.4612 | | 1.1027 | 67.0083 | 1088 | 2.0572 | 0.4777 | | 1.0956 | 68.0083 | 1104 | 2.0502 | 0.4892 | | 0.8823 | 69.0083 | 1120 | 2.1128 | 0.4756 | | 1.0344 | 70.0083 | 1136 | 2.0950 | 0.4727 | | 1.0887 | 71.0083 | 1152 | 2.0543 | 0.4943 | | 1.0763 | 72.0083 | 1168 | 2.0535 | 0.4907 | | 0.9652 | 73.0083 | 1184 | 2.0280 | 0.5 | | 1.0445 | 74.0083 | 1200 | 2.0551 | 0.4820 | | 0.9844 | 75.0083 | 1216 | 2.0514 | 0.5043 | | 1.0809 | 76.0083 | 1232 | 2.0552 | 0.5022 | | 1.1158 | 77.0083 | 1248 | 2.0469 | 0.4878 | | 0.9017 | 78.0083 | 1264 | 2.0516 | 0.4907 | | 1.0449 | 79.0083 | 1280 | 2.0770 | 0.4864 | | 1.0167 | 80.0083 | 1296 | 2.0374 | 0.4943 | | 0.975 | 81.0083 | 1312 | 2.0631 | 0.4943 | | 0.9285 | 82.0083 | 1328 | 2.0499 | 0.4871 | | 0.9762 | 83.0083 | 1344 | 2.0618 | 0.4964 | | 0.9454 | 84.0083 | 1360 | 2.0462 | 0.4993 | | 0.8665 | 85.0083 | 1376 | 2.0765 | 0.4892 | | 0.9202 | 86.0083 | 1392 | 2.0513 | 0.4950 | | 0.8186 | 87.0083 | 1408 | 2.0254 | 0.5093 | | 0.8659 | 88.0083 | 1424 | 2.1060 | 0.4792 | | 0.8789 | 89.0083 | 1440 | 2.0296 | 0.4964 | | 0.8592 | 90.0083 | 1456 | 2.0757 | 0.4849 | | 0.8093 | 91.0083 | 1472 | 2.0289 | 0.4986 | | 0.9074 | 92.0083 | 1488 | 2.0539 | 0.4921 | | 0.82 | 93.0083 | 1504 | 2.0481 | 0.5014 | | 0.8318 | 94.0083 | 1520 | 2.0309 | 0.5022 | | 0.8337 | 95.0083 | 1536 | 2.0335 | 0.5050 | | 0.9089 | 96.0083 | 1552 | 2.0456 | 0.5022 | | 0.8189 | 97.0083 | 1568 | 2.0107 | 0.4986 | | 0.7603 | 98.0083 | 1584 | 2.0147 | 0.5072 | | 0.9197 | 99.0083 | 1600 | 2.0438 | 0.5014 | | 0.8021 | 100.0083 | 1616 | 2.0311 | 0.5 | | 0.7474 | 101.0083 | 1632 | 2.0348 | 0.5007 | | 0.9423 | 102.0083 | 1648 | 2.0177 | 0.5007 | | 0.8135 | 103.0083 | 1664 | 2.0140 | 0.5029 | | 0.8244 | 104.0083 | 1680 | 2.0124 | 0.4986 | | 0.8446 | 105.0083 | 1696 | 2.0022 | 0.5065 | | 0.7965 | 106.0083 | 1712 | 1.9957 | 0.5108 | | 0.8256 | 107.0083 | 1728 | 1.9995 | 0.5108 | | 0.8448 | 108.0083 | 1744 | 2.0056 | 0.5093 | | 0.7144 | 109.0083 | 1760 | 2.0084 | 0.5072 | | 0.7869 | 110.0083 | 1776 | 1.9967 | 0.5115 | | 0.8149 | 111.0083 | 1792 | 1.9973 | 0.5115 | | 0.7896 | 112.0083 | 1808 | 2.0014 | 0.5122 | | 0.8189 | 113.0083 | 1824 | 1.9989 | 0.5144 | | 0.6775 | 114.0083 | 1840 | 1.9957 | 0.5122 | | 0.8642 | 115.0083 | 1856 | 2.0001 | 0.5101 | | 0.7308 | 116.0083 | 1872 | 1.9895 | 0.5086 | | 0.8616 | 117.0083 | 1888 | 1.9854 | 0.5079 | | 0.7763 | 118.0083 | 1904 | 1.9896 | 0.5072 | | 0.8009 | 119.0083 | 1920 | 1.9903 | 0.5072 | ### Framework versions - Transformers 4.48.0 - Pytorch 2.5.1+cu118 - Datasets 3.2.0 - Tokenizers 0.21.0