--- license: apache-2.0 base_model: ArrayDice/Super_Detection_Model2 tags: - generated_from_trainer model-index: - name: Super_Detection_Model3 results: [] --- # Super_Detection_Model3 This model is a fine-tuned version of [ArrayDice/Super_Detection_Model2](https://huggingface.co/ArrayDice/Super_Detection_Model2) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.1571 - Map: 0.1696 - Map 50: 0.3271 - Map 75: 0.1562 - Map Small: 0.1107 - Map Medium: 0.2616 - Map Large: 0.2231 - Mar 1: 0.1116 - Mar 10: 0.2157 - Mar 100: 0.2529 - Mar Small: 0.1876 - Mar Medium: 0.3221 - Mar Large: 0.4017 - Map Car: 0.2983 - Mar 100 Car: 0.4065 - Map Hgv: 0.3148 - Mar 100 Hgv: 0.491 - Map Motorcycle: 0.0651 - Mar 100 Motorcycle: 0.1143 - Map Other: 0.0 - Mar 100 Other: 0.0 ## 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: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - num_epochs: 20 ### Training results | Training Loss | Epoch | Step | Validation Loss | Map | Map 50 | Map 75 | Map Small | Map Medium | Map Large | Mar 1 | Mar 10 | Mar 100 | Mar Small | Mar Medium | Mar Large | Map Car | Mar 100 Car | Map Hgv | Mar 100 Hgv | Map Motorcycle | Mar 100 Motorcycle | Map Other | Mar 100 Other | |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:----------:|:---------:|:------:|:------:|:-------:|:---------:|:----------:|:---------:|:-------:|:-----------:|:-------:|:-----------:|:--------------:|:------------------:|:---------:|:-------------:| | 1.4133 | 1.0 | 1431 | 1.3878 | 0.1118 | 0.2461 | 0.0892 | 0.0643 | 0.2086 | 0.153 | 0.0842 | 0.1683 | 0.2003 | 0.1397 | 0.2803 | 0.3359 | 0.1979 | 0.3241 | 0.2175 | 0.3971 | 0.0318 | 0.08 | 0.0 | 0.0 | | 1.4871 | 2.0 | 2862 | 1.4927 | 0.0816 | 0.1914 | 0.0587 | 0.0525 | 0.1696 | 0.108 | 0.0687 | 0.1399 | 0.1659 | 0.1193 | 0.2457 | 0.2894 | 0.1602 | 0.3123 | 0.1616 | 0.3004 | 0.0046 | 0.0509 | 0.0 | 0.0 | | 1.474 | 3.0 | 4293 | 1.3646 | 0.1173 | 0.2545 | 0.0943 | 0.0635 | 0.2175 | 0.1614 | 0.0844 | 0.1708 | 0.202 | 0.1383 | 0.2838 | 0.3361 | 0.2145 | 0.3427 | 0.2288 | 0.3962 | 0.026 | 0.0691 | 0.0 | 0.0 | | 1.4236 | 4.0 | 5724 | 1.3576 | 0.1186 | 0.2538 | 0.0955 | 0.0724 | 0.2144 | 0.1237 | 0.0873 | 0.1692 | 0.1988 | 0.1367 | 0.2806 | 0.3138 | 0.2108 | 0.335 | 0.2272 | 0.378 | 0.0366 | 0.0823 | 0.0 | 0.0 | | 1.4074 | 5.0 | 7155 | 1.3601 | 0.1238 | 0.2678 | 0.0964 | 0.0746 | 0.2107 | 0.161 | 0.0927 | 0.181 | 0.2143 | 0.1519 | 0.276 | 0.3352 | 0.2202 | 0.3451 | 0.2255 | 0.3875 | 0.0497 | 0.1246 | 0.0 | 0.0 | | 1.3695 | 6.0 | 8586 | 1.3266 | 0.1191 | 0.2578 | 0.0966 | 0.0724 | 0.2171 | 0.1591 | 0.0863 | 0.1755 | 0.2095 | 0.1502 | 0.2824 | 0.323 | 0.2095 | 0.353 | 0.2327 | 0.3952 | 0.0341 | 0.0897 | 0.0 | 0.0 | | 1.4115 | 7.0 | 10017 | 1.3915 | 0.1139 | 0.2468 | 0.0956 | 0.0672 | 0.2111 | 0.1399 | 0.0868 | 0.1751 | 0.2091 | 0.1466 | 0.2817 | 0.3676 | 0.2017 | 0.345 | 0.2244 | 0.3989 | 0.0295 | 0.0926 | 0.0 | 0.0 | | 1.3927 | 8.0 | 11448 | 1.3455 | 0.1255 | 0.2657 | 0.1047 | 0.0754 | 0.2207 | 0.1601 | 0.0903 | 0.1795 | 0.2143 | 0.1506 | 0.291 | 0.3208 | 0.2407 | 0.3574 | 0.2311 | 0.4193 | 0.0302 | 0.0806 | 0.0 | 0.0 | | 1.3754 | 9.0 | 12879 | 1.3246 | 0.1264 | 0.2683 | 0.1046 | 0.077 | 0.2192 | 0.1416 | 0.0896 | 0.1806 | 0.2119 | 0.1459 | 0.2895 | 0.3651 | 0.235 | 0.3474 | 0.2389 | 0.4166 | 0.0316 | 0.0834 | 0.0 | 0.0 | | 1.3245 | 10.0 | 14310 | 1.2692 | 0.1326 | 0.2825 | 0.1094 | 0.0767 | 0.2328 | 0.2152 | 0.1007 | 0.1888 | 0.2253 | 0.1617 | 0.296 | 0.3717 | 0.2349 | 0.3698 | 0.2549 | 0.4235 | 0.0408 | 0.108 | 0.0 | 0.0 | | 1.2893 | 11.0 | 15741 | 1.2871 | 0.1484 | 0.3003 | 0.1276 | 0.0933 | 0.238 | 0.2028 | 0.1031 | 0.1992 | 0.2366 | 0.1757 | 0.3048 | 0.3834 | 0.2554 | 0.38 | 0.2745 | 0.4563 | 0.0636 | 0.1103 | 0.0 | 0.0 | | 1.2561 | 12.0 | 17172 | 1.2404 | 0.1442 | 0.2917 | 0.1245 | 0.0882 | 0.2375 | 0.1869 | 0.1004 | 0.1959 | 0.2316 | 0.1664 | 0.303 | 0.358 | 0.2566 | 0.3783 | 0.2622 | 0.4316 | 0.0581 | 0.1166 | 0.0 | 0.0 | | 1.2142 | 13.0 | 18603 | 1.2255 | 0.1529 | 0.3127 | 0.1346 | 0.0976 | 0.2445 | 0.2094 | 0.1027 | 0.2058 | 0.2415 | 0.1803 | 0.3083 | 0.364 | 0.2686 | 0.3803 | 0.2821 | 0.4653 | 0.0607 | 0.1206 | 0.0 | 0.0 | | 1.2031 | 14.0 | 20034 | 1.1940 | 0.1576 | 0.3085 | 0.144 | 0.1005 | 0.2502 | 0.1978 | 0.1083 | 0.208 | 0.2453 | 0.1816 | 0.3129 | 0.3738 | 0.2918 | 0.3994 | 0.2798 | 0.4637 | 0.0585 | 0.1183 | 0.0 | 0.0 | | 1.1984 | 15.0 | 21465 | 1.1855 | 0.1603 | 0.3121 | 0.1475 | 0.1035 | 0.2533 | 0.217 | 0.1079 | 0.211 | 0.2505 | 0.1842 | 0.321 | 0.3969 | 0.2929 | 0.3983 | 0.2924 | 0.4865 | 0.0561 | 0.1171 | 0.0 | 0.0 | | 1.1851 | 16.0 | 22896 | 1.1813 | 0.1616 | 0.3207 | 0.1411 | 0.1027 | 0.2557 | 0.2162 | 0.1103 | 0.2076 | 0.2448 | 0.1785 | 0.3165 | 0.3894 | 0.2888 | 0.3972 | 0.2986 | 0.469 | 0.0591 | 0.1131 | 0.0 | 0.0 | | 1.1626 | 17.0 | 24327 | 1.1633 | 0.1661 | 0.3274 | 0.1543 | 0.1083 | 0.2577 | 0.2191 | 0.1119 | 0.217 | 0.2545 | 0.1875 | 0.3228 | 0.4001 | 0.2947 | 0.4027 | 0.3086 | 0.4912 | 0.0609 | 0.124 | 0.0 | 0.0 | | 1.1577 | 18.0 | 25758 | 1.1572 | 0.1688 | 0.3267 | 0.1577 | 0.1104 | 0.2614 | 0.2228 | 0.1136 | 0.218 | 0.2552 | 0.1908 | 0.3224 | 0.406 | 0.2997 | 0.4064 | 0.3121 | 0.4946 | 0.0634 | 0.12 | 0.0 | 0.0 | | 1.1682 | 19.0 | 27189 | 1.1584 | 0.1685 | 0.3254 | 0.1554 | 0.1103 | 0.2611 | 0.2207 | 0.1114 | 0.2156 | 0.2525 | 0.187 | 0.3218 | 0.4025 | 0.2985 | 0.406 | 0.3119 | 0.4897 | 0.0636 | 0.1143 | 0.0 | 0.0 | | 1.135 | 20.0 | 28620 | 1.1571 | 0.1696 | 0.3271 | 0.1562 | 0.1107 | 0.2616 | 0.2231 | 0.1116 | 0.2157 | 0.2529 | 0.1876 | 0.3221 | 0.4017 | 0.2983 | 0.4065 | 0.3148 | 0.491 | 0.0651 | 0.1143 | 0.0 | 0.0 | ### Framework versions - Transformers 4.44.0 - Pytorch 2.4.0+cu121 - Datasets 2.20.0 - Tokenizers 0.19.1