debug_no_pad
This model is a fine-tuned version of sbchoi/rtdetr_r50vd_coco_o365 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 11.7188
- Map: 0.2736
- Map 50: 0.5376
- Map 75: 0.2345
- Map Small: 0.0676
- Map Medium: 0.2622
- Map Large: 0.3783
- Mar 1: 0.2586
- Mar 10: 0.457
- Mar 100: 0.5147
- Mar Small: 0.1125
- Mar Medium: 0.4717
- Mar Large: 0.5986
- Map Coverall: 0.2102
- Mar 100 Coverall: 0.5846
- Map Face Shield: 0.3488
- Mar 100 Face Shield: 0.6824
- Map Gloves: 0.3656
- Mar 100 Gloves: 0.5271
- Map Goggles: 0.1612
- Mar 100 Goggles: 0.3345
- Map Mask: 0.2823
- Mar 100 Mask: 0.4451
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- num_epochs: 30
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 Coverall | Mar 100 Coverall | Map Face Shield | Mar 100 Face Shield | Map Gloves | Mar 100 Gloves | Map Goggles | Mar 100 Goggles | Map Mask | Mar 100 Mask |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
No log | 1.0 | 107 | 101.3493 | 0.0 | 0.0002 | 0.0 | 0.0 | 0.0 | 0.0004 | 0.0026 | 0.0098 | 0.0201 | 0.0144 | 0.0106 | 0.0257 | 0.0002 | 0.0387 | 0.0 | 0.0139 | 0.0 | 0.0018 | 0.0 | 0.0462 | 0.0 | 0.0 |
No log | 2.0 | 214 | 29.9261 | 0.0003 | 0.0014 | 0.0 | 0.0 | 0.0 | 0.0003 | 0.0019 | 0.0114 | 0.0182 | 0.0 | 0.0133 | 0.0184 | 0.0013 | 0.091 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
No log | 3.0 | 321 | 21.9254 | 0.0031 | 0.0095 | 0.0014 | 0.0023 | 0.008 | 0.003 | 0.0233 | 0.0687 | 0.1387 | 0.0058 | 0.0927 | 0.1278 | 0.0119 | 0.3468 | 0.0007 | 0.1494 | 0.0009 | 0.0281 | 0.0 | 0.0308 | 0.0018 | 0.1382 |
No log | 4.0 | 428 | 17.4624 | 0.0317 | 0.0912 | 0.0132 | 0.0206 | 0.0307 | 0.0303 | 0.0537 | 0.1415 | 0.2005 | 0.0667 | 0.1778 | 0.2273 | 0.0349 | 0.3063 | 0.0077 | 0.2443 | 0.0105 | 0.1442 | 0.0012 | 0.0754 | 0.1044 | 0.2324 |
97.4578 | 5.0 | 535 | 16.2654 | 0.0654 | 0.1715 | 0.0386 | 0.031 | 0.0647 | 0.0918 | 0.1116 | 0.2112 | 0.2733 | 0.0983 | 0.2249 | 0.358 | 0.0664 | 0.445 | 0.0501 | 0.3405 | 0.0282 | 0.1335 | 0.031 | 0.1692 | 0.151 | 0.2782 |
97.4578 | 6.0 | 642 | 15.4886 | 0.0997 | 0.2444 | 0.0711 | 0.0568 | 0.0907 | 0.1367 | 0.1635 | 0.2746 | 0.3398 | 0.1459 | 0.2877 | 0.4549 | 0.114 | 0.4734 | 0.0637 | 0.3797 | 0.0467 | 0.2299 | 0.0762 | 0.2662 | 0.1982 | 0.3498 |
97.4578 | 7.0 | 749 | 15.3647 | 0.1205 | 0.3157 | 0.0659 | 0.0501 | 0.1134 | 0.1725 | 0.1602 | 0.2869 | 0.3296 | 0.1181 | 0.2841 | 0.4334 | 0.1443 | 0.3901 | 0.0689 | 0.4139 | 0.1082 | 0.2714 | 0.0928 | 0.2523 | 0.1882 | 0.3204 |
97.4578 | 8.0 | 856 | 15.2431 | 0.1016 | 0.2715 | 0.0558 | 0.0301 | 0.0905 | 0.146 | 0.1569 | 0.2829 | 0.344 | 0.129 | 0.2983 | 0.4391 | 0.1136 | 0.4009 | 0.0707 | 0.438 | 0.0902 | 0.2915 | 0.0755 | 0.2923 | 0.1579 | 0.2973 |
97.4578 | 9.0 | 963 | 14.7396 | 0.1497 | 0.3629 | 0.1013 | 0.0641 | 0.1617 | 0.1877 | 0.1691 | 0.3051 | 0.3433 | 0.2003 | 0.3204 | 0.4348 | 0.1987 | 0.4293 | 0.1105 | 0.3861 | 0.1467 | 0.3379 | 0.1034 | 0.2462 | 0.1894 | 0.3169 |
27.2963 | 10.0 | 1070 | 14.2373 | 0.1549 | 0.3715 | 0.1124 | 0.0798 | 0.163 | 0.1902 | 0.192 | 0.3368 | 0.4073 | 0.2642 | 0.3594 | 0.5035 | 0.1891 | 0.4977 | 0.1105 | 0.4646 | 0.1507 | 0.3763 | 0.1091 | 0.3108 | 0.2154 | 0.3871 |
27.2963 | 11.0 | 1177 | 14.4769 | 0.1413 | 0.3176 | 0.1085 | 0.0477 | 0.1304 | 0.2084 | 0.1892 | 0.3246 | 0.3797 | 0.195 | 0.3323 | 0.4877 | 0.1858 | 0.4775 | 0.1162 | 0.4532 | 0.1387 | 0.3683 | 0.1182 | 0.2569 | 0.1477 | 0.3427 |
27.2963 | 12.0 | 1284 | 13.9935 | 0.1922 | 0.4287 | 0.146 | 0.0793 | 0.1931 | 0.2346 | 0.2099 | 0.3566 | 0.4036 | 0.2114 | 0.3472 | 0.5202 | 0.2718 | 0.5117 | 0.1478 | 0.4392 | 0.1856 | 0.3893 | 0.1322 | 0.3 | 0.2236 | 0.3778 |
27.2963 | 13.0 | 1391 | 13.7867 | 0.1745 | 0.4012 | 0.1326 | 0.0796 | 0.1727 | 0.2301 | 0.1965 | 0.3503 | 0.4054 | 0.2274 | 0.352 | 0.5241 | 0.2083 | 0.5086 | 0.1234 | 0.4633 | 0.2004 | 0.3924 | 0.1076 | 0.2754 | 0.2327 | 0.3871 |
27.2963 | 14.0 | 1498 | 13.7474 | 0.18 | 0.3989 | 0.1445 | 0.0579 | 0.1639 | 0.241 | 0.1995 | 0.3449 | 0.3898 | 0.2128 | 0.3156 | 0.5022 | 0.1854 | 0.4761 | 0.1402 | 0.4038 | 0.2065 | 0.4094 | 0.1273 | 0.2692 | 0.2409 | 0.3902 |
24.8642 | 15.0 | 1605 | 13.4012 | 0.1958 | 0.4352 | 0.157 | 0.0757 | 0.1788 | 0.2823 | 0.2073 | 0.3522 | 0.4008 | 0.212 | 0.3359 | 0.5287 | 0.198 | 0.5099 | 0.1506 | 0.4101 | 0.2134 | 0.3933 | 0.1558 | 0.2831 | 0.2611 | 0.4076 |
24.8642 | 16.0 | 1712 | 13.3569 | 0.19 | 0.4224 | 0.1454 | 0.1542 | 0.2044 | 0.2407 | 0.2128 | 0.3568 | 0.3989 | 0.2681 | 0.3554 | 0.5058 | 0.1902 | 0.4977 | 0.1678 | 0.3911 | 0.225 | 0.3978 | 0.1325 | 0.2923 | 0.2347 | 0.4156 |
24.8642 | 17.0 | 1819 | 13.4929 | 0.1809 | 0.3983 | 0.1353 | 0.0679 | 0.1746 | 0.267 | 0.2142 | 0.3496 | 0.3898 | 0.2683 | 0.3211 | 0.5047 | 0.2047 | 0.5185 | 0.174 | 0.4329 | 0.1679 | 0.321 | 0.1303 | 0.2769 | 0.2276 | 0.3996 |
24.8642 | 18.0 | 1926 | 13.4921 | 0.1789 | 0.3853 | 0.1477 | 0.057 | 0.1655 | 0.2511 | 0.2202 | 0.3641 | 0.4147 | 0.2614 | 0.349 | 0.5348 | 0.2266 | 0.55 | 0.1629 | 0.4759 | 0.2087 | 0.3857 | 0.138 | 0.2908 | 0.1584 | 0.3711 |
23.551 | 19.0 | 2033 | 13.3617 | 0.1824 | 0.3978 | 0.1471 | 0.0609 | 0.1695 | 0.2607 | 0.2263 | 0.388 | 0.4319 | 0.2304 | 0.3643 | 0.555 | 0.2282 | 0.5536 | 0.1568 | 0.4886 | 0.2076 | 0.4094 | 0.1415 | 0.3046 | 0.1776 | 0.4031 |
23.551 | 20.0 | 2140 | 13.3499 | 0.1834 | 0.4074 | 0.1496 | 0.0734 | 0.156 | 0.2478 | 0.2276 | 0.3903 | 0.4373 | 0.2858 | 0.3555 | 0.5568 | 0.2326 | 0.5392 | 0.1721 | 0.4987 | 0.2169 | 0.4237 | 0.1402 | 0.3508 | 0.1553 | 0.3742 |
23.551 | 21.0 | 2247 | 13.4009 | 0.1858 | 0.3991 | 0.1394 | 0.0578 | 0.1748 | 0.2553 | 0.2214 | 0.375 | 0.4254 | 0.1951 | 0.3547 | 0.5506 | 0.2349 | 0.5473 | 0.1842 | 0.4861 | 0.2227 | 0.4223 | 0.1443 | 0.3185 | 0.1428 | 0.3529 |
23.551 | 22.0 | 2354 | 13.4129 | 0.1824 | 0.3995 | 0.1459 | 0.0715 | 0.1394 | 0.2581 | 0.2234 | 0.3735 | 0.4277 | 0.2243 | 0.348 | 0.5472 | 0.2425 | 0.5491 | 0.1465 | 0.4949 | 0.2072 | 0.417 | 0.133 | 0.3015 | 0.1826 | 0.376 |
23.551 | 23.0 | 2461 | 13.4100 | 0.1902 | 0.4141 | 0.1602 | 0.0641 | 0.171 | 0.2609 | 0.2162 | 0.3732 | 0.4327 | 0.2437 | 0.368 | 0.5519 | 0.2405 | 0.5644 | 0.1554 | 0.5139 | 0.2313 | 0.4071 | 0.1506 | 0.3185 | 0.1733 | 0.3596 |
23.8193 | 24.0 | 2568 | 13.3091 | 0.1857 | 0.4151 | 0.1452 | 0.0708 | 0.1669 | 0.2486 | 0.214 | 0.3653 | 0.4232 | 0.2201 | 0.358 | 0.5354 | 0.2348 | 0.5676 | 0.145 | 0.4899 | 0.2294 | 0.4004 | 0.1476 | 0.2938 | 0.1717 | 0.3644 |
23.8193 | 25.0 | 2675 | 13.2781 | 0.2006 | 0.4435 | 0.1611 | 0.065 | 0.1657 | 0.2624 | 0.215 | 0.3741 | 0.4223 | 0.1951 | 0.351 | 0.5465 | 0.2609 | 0.5595 | 0.1831 | 0.5025 | 0.2365 | 0.3982 | 0.1364 | 0.2877 | 0.1863 | 0.3636 |
23.8193 | 26.0 | 2782 | 13.2183 | 0.1951 | 0.4333 | 0.1577 | 0.063 | 0.1709 | 0.2501 | 0.22 | 0.3751 | 0.4286 | 0.1712 | 0.3619 | 0.5411 | 0.2431 | 0.5734 | 0.163 | 0.4772 | 0.2165 | 0.4013 | 0.1581 | 0.3215 | 0.1946 | 0.3693 |
23.8193 | 27.0 | 2889 | 13.2704 | 0.2009 | 0.4453 | 0.1559 | 0.0626 | 0.1881 | 0.2605 | 0.2209 | 0.3766 | 0.4293 | 0.1594 | 0.371 | 0.5524 | 0.2635 | 0.5721 | 0.1797 | 0.5127 | 0.2159 | 0.4031 | 0.159 | 0.2938 | 0.1864 | 0.3649 |
23.8193 | 28.0 | 2996 | 13.1710 | 0.2062 | 0.4625 | 0.1583 | 0.0722 | 0.1803 | 0.2726 | 0.2227 | 0.3843 | 0.433 | 0.2041 | 0.3729 | 0.5589 | 0.2826 | 0.5838 | 0.1861 | 0.5101 | 0.2225 | 0.3973 | 0.1413 | 0.3015 | 0.1986 | 0.372 |
23.7672 | 29.0 | 3103 | 13.1248 | 0.2038 | 0.4521 | 0.1679 | 0.0703 | 0.1655 | 0.2771 | 0.2255 | 0.3828 | 0.4367 | 0.1904 | 0.3678 | 0.5661 | 0.2629 | 0.5757 | 0.1836 | 0.5241 | 0.2332 | 0.4027 | 0.1466 | 0.3031 | 0.1928 | 0.3778 |
23.7672 | 30.0 | 3210 | 13.1506 | 0.2026 | 0.4492 | 0.1638 | 0.0726 | 0.1655 | 0.2732 | 0.2221 | 0.3782 | 0.4312 | 0.1892 | 0.3446 | 0.5587 | 0.2662 | 0.5721 | 0.1827 | 0.519 | 0.2317 | 0.3991 | 0.1477 | 0.2938 | 0.1846 | 0.372 |
Framework versions
- Transformers 4.42.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.19.1
- Tokenizers 0.19.1
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PekingU/rtdetr_r50vd_coco_o365
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