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rtdetr-r50-cppe5-finetune-use_focal-False

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rt_detr
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  1. README.md +109 -0
  2. config.json +111 -0
  3. model.safetensors +3 -0
  4. preprocessor_config.json +26 -0
  5. training_args.bin +3 -0
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: PekingU/rtdetr_r50vd_coco_o365
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: rtdetr-r50-cppe5-finetune-use_focal-False
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # rtdetr-r50-cppe5-finetune-use_focal-False
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+
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+ This model is a fine-tuned version of [PekingU/rtdetr_r50vd_coco_o365](https://huggingface.co/PekingU/rtdetr_r50vd_coco_o365) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 5.9218
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+ - Map: 0.3752
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+ - Map 50: 0.5265
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+ - Map 75: 0.4224
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+ - Map Small: 0.6103
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+ - Map Medium: 0.4091
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+ - Map Large: 0.5522
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+ - Mar 1: 0.3993
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+ - Mar 10: 0.7339
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+ - Mar 100: 0.7986
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+ - Mar Small: 0.7494
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+ - Mar Medium: 0.7108
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+ - Mar Large: 0.9271
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+ - Map Coverall: 0.3753
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+ - Mar 100 Coverall: 0.8128
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+ - Map Face Shield: 0.3528
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+ - Mar 100 Face Shield: 0.8467
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+ - Map Gloves: 0.319
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+ - Mar 100 Gloves: 0.7723
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+ - Map Goggles: 0.4667
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+ - Mar 100 Goggles: 0.775
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+ - Map Mask: 0.3622
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+ - Mar 100 Mask: 0.7864
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 5e-05
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_steps: 300
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+ - num_epochs: 30
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+
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+ ### Training results
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+
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+ | 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 |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:----------:|:---------:|:------:|:------:|:-------:|:---------:|:----------:|:---------:|:------------:|:----------------:|:---------------:|:-------------------:|:----------:|:--------------:|:-----------:|:---------------:|:--------:|:------------:|
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+ | No log | 1.0 | 106 | 24.0471 | 0.0066 | 0.0124 | 0.0069 | 0.0032 | 0.011 | 0.0084 | 0.0186 | 0.0717 | 0.1332 | 0.0557 | 0.0892 | 0.229 | 0.006 | 0.2935 | 0.0 | 0.028 | 0.0092 | 0.1991 | 0.0 | 0.0 | 0.0176 | 0.1452 |
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+ | No log | 2.0 | 212 | 14.0932 | 0.0807 | 0.1577 | 0.0773 | 0.0348 | 0.0677 | 0.1606 | 0.1488 | 0.337 | 0.3981 | 0.1782 | 0.3341 | 0.6135 | 0.1593 | 0.6166 | 0.021 | 0.344 | 0.0608 | 0.4274 | 0.0303 | 0.1891 | 0.1319 | 0.4137 |
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+ | No log | 3.0 | 318 | 13.2860 | 0.1033 | 0.1897 | 0.0986 | 0.0603 | 0.0941 | 0.1477 | 0.1938 | 0.3595 | 0.4228 | 0.2721 | 0.3335 | 0.6581 | 0.2055 | 0.6889 | 0.0416 | 0.3773 | 0.0798 | 0.5128 | 0.0479 | 0.1469 | 0.1419 | 0.3881 |
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+ | No log | 4.0 | 424 | 10.7598 | 0.1113 | 0.2036 | 0.1048 | 0.091 | 0.0902 | 0.1804 | 0.2358 | 0.4236 | 0.4965 | 0.2469 | 0.4356 | 0.7288 | 0.2198 | 0.7101 | 0.0378 | 0.524 | 0.0983 | 0.5155 | 0.0661 | 0.2984 | 0.1344 | 0.4342 |
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+ | 24.0469 | 5.0 | 530 | 11.5195 | 0.1126 | 0.1927 | 0.1137 | 0.1686 | 0.102 | 0.1816 | 0.2387 | 0.4267 | 0.4927 | 0.2938 | 0.4254 | 0.7416 | 0.217 | 0.7106 | 0.0748 | 0.508 | 0.1123 | 0.5228 | 0.0581 | 0.2875 | 0.1005 | 0.4347 |
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+ | 24.0469 | 6.0 | 636 | 9.9747 | 0.138 | 0.2341 | 0.1415 | 0.1598 | 0.123 | 0.2096 | 0.2646 | 0.4565 | 0.539 | 0.3445 | 0.4726 | 0.7601 | 0.2753 | 0.7438 | 0.0713 | 0.548 | 0.1061 | 0.5447 | 0.0954 | 0.3766 | 0.1421 | 0.4817 |
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+ | 24.0469 | 7.0 | 742 | 9.9184 | 0.1363 | 0.233 | 0.1403 | 0.1365 | 0.1191 | 0.2167 | 0.267 | 0.4522 | 0.5231 | 0.341 | 0.4487 | 0.7366 | 0.2782 | 0.7465 | 0.0697 | 0.556 | 0.0996 | 0.5516 | 0.1023 | 0.3063 | 0.1315 | 0.4553 |
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+ | 24.0469 | 8.0 | 848 | 9.7247 | 0.1463 | 0.2561 | 0.1524 | 0.1711 | 0.1251 | 0.24 | 0.2846 | 0.4771 | 0.5495 | 0.3839 | 0.4697 | 0.7746 | 0.305 | 0.7424 | 0.0723 | 0.56 | 0.1003 | 0.579 | 0.1129 | 0.3641 | 0.1409 | 0.5018 |
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+ | 24.0469 | 9.0 | 954 | 9.5843 | 0.1428 | 0.2487 | 0.1549 | 0.1736 | 0.1326 | 0.2182 | 0.2743 | 0.4714 | 0.5589 | 0.3942 | 0.4817 | 0.7706 | 0.3025 | 0.7484 | 0.084 | 0.5973 | 0.1304 | 0.5434 | 0.1006 | 0.375 | 0.0966 | 0.5306 |
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+ | 9.6616 | 10.0 | 1060 | 9.3868 | 0.161 | 0.2745 | 0.1683 | 0.1815 | 0.1396 | 0.242 | 0.2883 | 0.4894 | 0.5672 | 0.4062 | 0.4967 | 0.7772 | 0.3168 | 0.7493 | 0.1275 | 0.632 | 0.1247 | 0.5708 | 0.1099 | 0.3734 | 0.1262 | 0.5105 |
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+ | 9.6616 | 11.0 | 1166 | 9.3399 | 0.1547 | 0.2696 | 0.1545 | 0.1827 | 0.1214 | 0.2563 | 0.2935 | 0.4995 | 0.5729 | 0.3657 | 0.4947 | 0.7793 | 0.2687 | 0.7461 | 0.091 | 0.5467 | 0.1407 | 0.5584 | 0.1535 | 0.4781 | 0.1197 | 0.5352 |
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+ | 9.6616 | 12.0 | 1272 | 9.2511 | 0.151 | 0.2625 | 0.1509 | 0.1655 | 0.1369 | 0.2599 | 0.2915 | 0.4833 | 0.5633 | 0.3922 | 0.4894 | 0.7828 | 0.2591 | 0.753 | 0.1236 | 0.572 | 0.1064 | 0.5598 | 0.1508 | 0.4031 | 0.1151 | 0.5288 |
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+ | 9.6616 | 13.0 | 1378 | 9.3660 | 0.1795 | 0.3123 | 0.185 | 0.2092 | 0.1558 | 0.3135 | 0.2906 | 0.4945 | 0.5739 | 0.3906 | 0.5012 | 0.7681 | 0.3021 | 0.7562 | 0.151 | 0.6093 | 0.1284 | 0.5607 | 0.1602 | 0.4094 | 0.1558 | 0.5338 |
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+ | 9.6616 | 14.0 | 1484 | 9.7121 | 0.1608 | 0.2758 | 0.1754 | 0.1888 | 0.1498 | 0.2211 | 0.3027 | 0.491 | 0.5667 | 0.3848 | 0.4918 | 0.7867 | 0.3091 | 0.7507 | 0.137 | 0.6173 | 0.1309 | 0.5699 | 0.1033 | 0.3734 | 0.1236 | 0.5224 |
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+ | 7.7703 | 15.0 | 1590 | 9.3829 | 0.1735 | 0.3082 | 0.1795 | 0.1816 | 0.1703 | 0.255 | 0.3013 | 0.5023 | 0.5785 | 0.3995 | 0.5123 | 0.7851 | 0.284 | 0.7516 | 0.1921 | 0.624 | 0.111 | 0.5662 | 0.1307 | 0.425 | 0.1497 | 0.5256 |
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+ | 7.7703 | 16.0 | 1696 | 9.7996 | 0.1767 | 0.3065 | 0.1815 | 0.1793 | 0.1544 | 0.2373 | 0.309 | 0.5112 | 0.5822 | 0.3835 | 0.5201 | 0.7888 | 0.3528 | 0.7562 | 0.1269 | 0.6173 | 0.1243 | 0.553 | 0.1228 | 0.4391 | 0.1566 | 0.5452 |
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+ | 7.7703 | 17.0 | 1802 | 9.8642 | 0.1689 | 0.2962 | 0.1733 | 0.1934 | 0.1501 | 0.2263 | 0.3139 | 0.5025 | 0.5835 | 0.4012 | 0.5151 | 0.7941 | 0.3135 | 0.7544 | 0.1404 | 0.6 | 0.139 | 0.5708 | 0.1113 | 0.4609 | 0.1402 | 0.5315 |
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+ | 7.7703 | 18.0 | 1908 | 9.5005 | 0.1839 | 0.3224 | 0.1882 | 0.1887 | 0.1634 | 0.2638 | 0.317 | 0.513 | 0.5886 | 0.4156 | 0.5216 | 0.7778 | 0.325 | 0.7576 | 0.1512 | 0.6173 | 0.1358 | 0.5626 | 0.1518 | 0.4594 | 0.1558 | 0.5461 |
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+ | 6.699 | 19.0 | 2014 | 9.7569 | 0.1761 | 0.3125 | 0.1794 | 0.1864 | 0.161 | 0.2976 | 0.3078 | 0.4987 | 0.5758 | 0.3795 | 0.5069 | 0.7975 | 0.2971 | 0.7608 | 0.1542 | 0.5827 | 0.114 | 0.558 | 0.1569 | 0.4297 | 0.1585 | 0.5479 |
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+ | 6.699 | 20.0 | 2120 | 9.8298 | 0.1878 | 0.328 | 0.189 | 0.1867 | 0.159 | 0.2966 | 0.311 | 0.5071 | 0.5835 | 0.4039 | 0.5116 | 0.7997 | 0.3451 | 0.7599 | 0.1478 | 0.612 | 0.1191 | 0.5557 | 0.1641 | 0.4484 | 0.1629 | 0.5416 |
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+ | 6.699 | 21.0 | 2226 | 9.7809 | 0.1822 | 0.315 | 0.1913 | 0.18 | 0.1636 | 0.2603 | 0.3143 | 0.511 | 0.5844 | 0.4044 | 0.5111 | 0.793 | 0.3392 | 0.7567 | 0.1617 | 0.604 | 0.1174 | 0.558 | 0.1433 | 0.4531 | 0.1492 | 0.5502 |
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+ | 6.699 | 22.0 | 2332 | 10.1915 | 0.1831 | 0.3242 | 0.1808 | 0.1777 | 0.1639 | 0.2464 | 0.3135 | 0.5036 | 0.5789 | 0.3989 | 0.5114 | 0.7721 | 0.3304 | 0.7567 | 0.1778 | 0.624 | 0.124 | 0.5511 | 0.1355 | 0.4016 | 0.1478 | 0.5612 |
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+ | 6.699 | 23.0 | 2438 | 10.0230 | 0.1795 | 0.3247 | 0.1738 | 0.1757 | 0.1667 | 0.2382 | 0.3162 | 0.5023 | 0.5835 | 0.4075 | 0.518 | 0.7682 | 0.3191 | 0.7539 | 0.1626 | 0.6107 | 0.1269 | 0.542 | 0.1216 | 0.4594 | 0.1673 | 0.5516 |
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+ | 6.1765 | 24.0 | 2544 | 10.0386 | 0.1765 | 0.3184 | 0.178 | 0.1784 | 0.1576 | 0.2469 | 0.3126 | 0.4972 | 0.5806 | 0.4138 | 0.5063 | 0.7636 | 0.3146 | 0.7521 | 0.1745 | 0.6187 | 0.1135 | 0.5539 | 0.1344 | 0.4328 | 0.1454 | 0.5457 |
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+ | 6.1765 | 25.0 | 2650 | 10.2036 | 0.1855 | 0.3316 | 0.1806 | 0.1837 | 0.154 | 0.2811 | 0.3204 | 0.5076 | 0.5864 | 0.4197 | 0.5177 | 0.7589 | 0.3374 | 0.759 | 0.1864 | 0.6027 | 0.1212 | 0.5443 | 0.1277 | 0.4625 | 0.1546 | 0.5635 |
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+ | 6.1765 | 26.0 | 2756 | 10.1975 | 0.1848 | 0.3283 | 0.1854 | 0.1827 | 0.168 | 0.2654 | 0.3155 | 0.511 | 0.581 | 0.4125 | 0.499 | 0.7679 | 0.3064 | 0.7608 | 0.1949 | 0.612 | 0.1287 | 0.5447 | 0.1375 | 0.4406 | 0.1566 | 0.547 |
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+ | 6.1765 | 27.0 | 2862 | 10.2368 | 0.1864 | 0.3324 | 0.1914 | 0.178 | 0.1717 | 0.2878 | 0.3171 | 0.5122 | 0.5833 | 0.3902 | 0.5185 | 0.7613 | 0.3065 | 0.759 | 0.2008 | 0.612 | 0.1237 | 0.5461 | 0.1455 | 0.4531 | 0.1555 | 0.5461 |
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+ | 6.1765 | 28.0 | 2968 | 10.2034 | 0.1857 | 0.3297 | 0.1869 | 0.1918 | 0.1673 | 0.2712 | 0.3207 | 0.5125 | 0.5904 | 0.4132 | 0.52 | 0.7673 | 0.3133 | 0.759 | 0.1976 | 0.6267 | 0.1251 | 0.5562 | 0.1392 | 0.4563 | 0.1533 | 0.5539 |
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+ | 5.7542 | 29.0 | 3074 | 10.1788 | 0.1825 | 0.3255 | 0.1822 | 0.1735 | 0.1703 | 0.2771 | 0.3209 | 0.5056 | 0.5837 | 0.4034 | 0.5125 | 0.7695 | 0.2897 | 0.7558 | 0.1932 | 0.616 | 0.1255 | 0.5516 | 0.1387 | 0.4453 | 0.1652 | 0.5498 |
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+ | 5.7542 | 30.0 | 3180 | 10.3023 | 0.1765 | 0.319 | 0.1787 | 0.1774 | 0.1643 | 0.2572 | 0.3181 | 0.5139 | 0.5843 | 0.4012 | 0.5167 | 0.7677 | 0.2839 | 0.7525 | 0.1903 | 0.6293 | 0.1252 | 0.5516 | 0.1252 | 0.4391 | 0.1577 | 0.5489 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.45.0.dev0
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+ - Pytorch 2.4.0+cu121
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+ - Datasets 2.20.0
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+ - Tokenizers 0.19.1
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+ "with_box_refine": true
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