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rtdetr-v2-r50-cppe5-finetune-2

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rt_detr_v2
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End of training

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  1. README.md +30 -43
  2. model.safetensors +1 -1
  3. preprocessor_config.json +2 -2
  4. runs/May19_03-53-12_6b43017bb33c/events.out.tfevents.1747626798.6b43017bb33c.3302.0 +3 -0
  5. runs/May19_03-53-12_6b43017bb33c/events.out.tfevents.1747629550.6b43017bb33c.3302.1 +3 -0
  6. training_args.bin +1 -1
README.md CHANGED
@@ -16,23 +16,23 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [PekingU/rtdetr_v2_r50vd](https://huggingface.co/PekingU/rtdetr_v2_r50vd) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 10.6817
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- - Map: 0.3253
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- - Map 50: 0.7158
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- - Map 75: 0.2083
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- - Map Small: 0.2981
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- - Map Medium: 0.5419
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- - Map Large: 0.4764
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- - Mar 1: 0.2175
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- - Mar 10: 0.4315
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- - Mar 100: 0.571
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- - Mar Small: 0.5436
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- - Mar Medium: 0.7592
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- - Mar Large: 0.78
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- - Map Football: 0.3773
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- - Mar 100 Football: 0.5711
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- - Map Player: 0.2732
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- - Mar 100 Player: 0.5709
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  ## Model description
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@@ -58,37 +58,24 @@ The following hyperparameters were used during training:
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  - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: cosine
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  - lr_scheduler_warmup_steps: 300
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- - num_epochs: 25
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  ### Training results
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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 Football | Mar 100 Football | Map Player | Mar 100 Player |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:----------:|:---------:|:------:|:------:|:-------:|:---------:|:----------:|:---------:|:------------:|:----------------:|:----------:|:--------------:|
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- | No log | 1.0 | 62 | 28.5644 | 0.037 | 0.0874 | 0.0259 | 0.0272 | 0.0823 | 0.0613 | 0.0167 | 0.0808 | 0.1307 | 0.1015 | 0.2278 | 0.5756 | 0.0003 | 0.026 | 0.0738 | 0.2354 |
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- | No log | 2.0 | 124 | 16.4613 | 0.1563 | 0.3574 | 0.107 | 0.1299 | 0.3282 | 0.352 | 0.0935 | 0.2119 | 0.3076 | 0.2581 | 0.5648 | 0.7122 | 0.1104 | 0.1609 | 0.2022 | 0.4543 |
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- | No log | 3.0 | 186 | 11.6244 | 0.2239 | 0.4958 | 0.1964 | 0.191 | 0.4446 | 0.2868 | 0.1454 | 0.2799 | 0.4262 | 0.384 | 0.6749 | 0.722 | 0.2201 | 0.3036 | 0.2276 | 0.5488 |
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- | No log | 4.0 | 248 | 11.4733 | 0.2611 | 0.5765 | 0.1943 | 0.2277 | 0.4867 | 0.3122 | 0.1669 | 0.3124 | 0.4616 | 0.4253 | 0.6816 | 0.7268 | 0.2662 | 0.3438 | 0.2561 | 0.5795 |
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- | No log | 5.0 | 310 | 10.7257 | 0.2816 | 0.6122 | 0.2432 | 0.2468 | 0.4772 | 0.38 | 0.1948 | 0.3573 | 0.4964 | 0.4577 | 0.7219 | 0.7366 | 0.3116 | 0.4207 | 0.2516 | 0.572 |
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- | No log | 6.0 | 372 | 10.8138 | 0.2651 | 0.5967 | 0.2079 | 0.226 | 0.4794 | 0.4331 | 0.2059 | 0.3673 | 0.5145 | 0.4801 | 0.7013 | 0.7512 | 0.3038 | 0.4793 | 0.2264 | 0.5497 |
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- | No log | 7.0 | 434 | 10.8522 | 0.2813 | 0.6458 | 0.1927 | 0.2499 | 0.4755 | 0.3697 | 0.2116 | 0.369 | 0.5138 | 0.4802 | 0.6994 | 0.7537 | 0.3256 | 0.468 | 0.2369 | 0.5596 |
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- | No log | 8.0 | 496 | 11.3549 | 0.2781 | 0.6428 | 0.1954 | 0.2438 | 0.4894 | 0.3973 | 0.2059 | 0.3711 | 0.5282 | 0.5 | 0.6847 | 0.739 | 0.3264 | 0.5024 | 0.2298 | 0.554 |
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- | 21.3472 | 9.0 | 558 | 10.6918 | 0.3041 | 0.6564 | 0.2477 | 0.2679 | 0.5094 | 0.3658 | 0.2304 | 0.3981 | 0.543 | 0.5096 | 0.7264 | 0.7732 | 0.3625 | 0.5172 | 0.2457 | 0.5689 |
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- | 21.3472 | 10.0 | 620 | 11.1993 | 0.2906 | 0.6248 | 0.2312 | 0.2583 | 0.4805 | 0.3659 | 0.2228 | 0.383 | 0.5454 | 0.5143 | 0.7117 | 0.7683 | 0.3521 | 0.5249 | 0.2291 | 0.5659 |
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- | 21.3472 | 11.0 | 682 | 10.6698 | 0.3062 | 0.6837 | 0.2491 | 0.2644 | 0.5253 | 0.3482 | 0.2223 | 0.4043 | 0.53 | 0.4941 | 0.7204 | 0.7659 | 0.3588 | 0.5148 | 0.2536 | 0.5452 |
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- | 21.3472 | 12.0 | 744 | 10.9556 | 0.2994 | 0.6672 | 0.2355 | 0.2619 | 0.5214 | 0.4306 | 0.2366 | 0.3956 | 0.5389 | 0.5074 | 0.7037 | 0.7634 | 0.3614 | 0.526 | 0.2374 | 0.5518 |
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- | 21.3472 | 13.0 | 806 | 10.8259 | 0.3145 | 0.6878 | 0.2393 | 0.2773 | 0.5164 | 0.3525 | 0.232 | 0.4165 | 0.5563 | 0.5242 | 0.7264 | 0.7829 | 0.3624 | 0.5349 | 0.2666 | 0.5777 |
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- | 21.3472 | 14.0 | 868 | 11.1133 | 0.3045 | 0.6694 | 0.2262 | 0.2713 | 0.5265 | 0.3611 | 0.2413 | 0.3956 | 0.5467 | 0.5125 | 0.7323 | 0.7537 | 0.3848 | 0.5361 | 0.2242 | 0.5572 |
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- | 21.3472 | 15.0 | 930 | 10.8950 | 0.309 | 0.6791 | 0.2332 | 0.2737 | 0.5338 | 0.3714 | 0.2498 | 0.4106 | 0.5541 | 0.5233 | 0.7127 | 0.7805 | 0.3808 | 0.5456 | 0.2372 | 0.5627 |
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- | 21.3472 | 16.0 | 992 | 11.0041 | 0.3054 | 0.688 | 0.2228 | 0.266 | 0.5183 | 0.3347 | 0.2313 | 0.4054 | 0.5421 | 0.5093 | 0.7147 | 0.778 | 0.3596 | 0.5243 | 0.2512 | 0.56 |
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- | 11.3378 | 17.0 | 1054 | 11.0604 | 0.2979 | 0.6857 | 0.2053 | 0.2671 | 0.5052 | 0.383 | 0.2319 | 0.4111 | 0.5523 | 0.519 | 0.723 | 0.8 | 0.3492 | 0.5402 | 0.2465 | 0.5643 |
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- | 11.3378 | 18.0 | 1116 | 11.3049 | 0.3075 | 0.675 | 0.222 | 0.2752 | 0.5225 | 0.3644 | 0.2485 | 0.4188 | 0.5634 | 0.5341 | 0.7101 | 0.7878 | 0.3738 | 0.5663 | 0.2411 | 0.5605 |
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- | 11.3378 | 19.0 | 1178 | 11.0193 | 0.3037 | 0.6876 | 0.2184 | 0.2675 | 0.5153 | 0.3811 | 0.2363 | 0.4094 | 0.5487 | 0.5161 | 0.7233 | 0.7707 | 0.3608 | 0.5379 | 0.2465 | 0.5596 |
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- | 11.3378 | 20.0 | 1240 | 11.0761 | 0.2982 | 0.6817 | 0.2123 | 0.2583 | 0.5289 | 0.3294 | 0.2292 | 0.4055 | 0.5377 | 0.5027 | 0.7243 | 0.7707 | 0.346 | 0.5237 | 0.2504 | 0.5516 |
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- | 11.3378 | 21.0 | 1302 | 11.1049 | 0.3006 | 0.6856 | 0.2179 | 0.2661 | 0.5168 | 0.3644 | 0.2351 | 0.4125 | 0.5504 | 0.5174 | 0.7264 | 0.7585 | 0.3581 | 0.5414 | 0.243 | 0.5593 |
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- | 11.3378 | 22.0 | 1364 | 11.1346 | 0.3085 | 0.6906 | 0.2309 | 0.2728 | 0.5266 | 0.3686 | 0.24 | 0.4128 | 0.5517 | 0.5192 | 0.7218 | 0.7707 | 0.3727 | 0.5485 | 0.2443 | 0.5549 |
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- | 11.3378 | 23.0 | 1426 | 11.0953 | 0.3058 | 0.6872 | 0.2333 | 0.2686 | 0.5365 | 0.2948 | 0.2404 | 0.4172 | 0.553 | 0.5212 | 0.7199 | 0.7634 | 0.3666 | 0.5497 | 0.2451 | 0.5563 |
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- | 11.3378 | 24.0 | 1488 | 11.0875 | 0.3094 | 0.6888 | 0.223 | 0.2702 | 0.5372 | 0.3423 | 0.2403 | 0.4151 | 0.5535 | 0.5212 | 0.7234 | 0.7683 | 0.3676 | 0.5491 | 0.2511 | 0.558 |
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- | 10.5848 | 25.0 | 1550 | 11.0936 | 0.3079 | 0.6883 | 0.2247 | 0.2693 | 0.5367 | 0.3189 | 0.2401 | 0.4175 | 0.5542 | 0.5211 | 0.7289 | 0.7707 | 0.3664 | 0.5515 | 0.2494 | 0.5569 |
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  ### Framework versions
 
16
 
17
  This model is a fine-tuned version of [PekingU/rtdetr_v2_r50vd](https://huggingface.co/PekingU/rtdetr_v2_r50vd) on an unknown dataset.
18
  It achieves the following results on the evaluation set:
19
+ - Loss: 10.6505
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+ - Map: 0.4323
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+ - Map 50: 0.8963
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+ - Map 75: 0.3219
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+ - Map Small: 0.3756
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+ - Map Medium: 0.5476
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+ - Map Large: 0.7106
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+ - Mar 1: 0.2852
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+ - Mar 10: 0.4788
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+ - Mar 100: 0.5715
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+ - Mar Small: 0.5305
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+ - Mar Medium: 0.6698
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+ - Mar Large: 0.7583
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+ - Map Football: 0.4833
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+ - Mar 100 Football: 0.5867
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+ - Map Player: 0.3814
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+ - Mar 100 Player: 0.5564
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37
  ## Model description
38
 
 
58
  - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: cosine
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  - lr_scheduler_warmup_steps: 300
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+ - num_epochs: 12
62
 
63
  ### Training results
64
 
65
  | 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 Football | Mar 100 Football | Map Player | Mar 100 Player |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:----------:|:---------:|:------:|:------:|:-------:|:---------:|:----------:|:---------:|:------------:|:----------------:|:----------:|:--------------:|
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+ | No log | 1.0 | 62 | 17.5576 | 0.1072 | 0.2555 | 0.0663 | 0.0878 | 0.1914 | 0.1325 | 0.0543 | 0.208 | 0.3404 | 0.2858 | 0.4734 | 0.5447 | 0.0102 | 0.2166 | 0.2042 | 0.4642 |
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+ | No log | 2.0 | 124 | 9.5985 | 0.3615 | 0.8054 | 0.2547 | 0.3082 | 0.5041 | 0.5671 | 0.2189 | 0.4346 | 0.5265 | 0.4739 | 0.6782 | 0.6455 | 0.3255 | 0.4828 | 0.3975 | 0.5702 |
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+ | No log | 3.0 | 186 | 9.6654 | 0.3647 | 0.8181 | 0.2656 | 0.3115 | 0.5271 | 0.6 | 0.2353 | 0.4404 | 0.5339 | 0.4772 | 0.685 | 0.7447 | 0.3696 | 0.5225 | 0.3597 | 0.5452 |
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+ | No log | 4.0 | 248 | 10.0423 | 0.3637 | 0.8276 | 0.2328 | 0.3011 | 0.5362 | 0.6091 | 0.2209 | 0.4219 | 0.5103 | 0.4515 | 0.674 | 0.7477 | 0.345 | 0.474 | 0.3823 | 0.5467 |
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+ | No log | 5.0 | 310 | 10.2540 | 0.3952 | 0.8224 | 0.3201 | 0.3304 | 0.5617 | 0.6733 | 0.2556 | 0.4589 | 0.548 | 0.4924 | 0.6929 | 0.7598 | 0.4203 | 0.5509 | 0.3702 | 0.5452 |
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+ | No log | 6.0 | 372 | 10.4936 | 0.3862 | 0.8134 | 0.3167 | 0.3148 | 0.5569 | 0.6616 | 0.2459 | 0.4368 | 0.5254 | 0.4659 | 0.6818 | 0.797 | 0.3995 | 0.5089 | 0.373 | 0.5418 |
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+ | No log | 7.0 | 434 | 10.6991 | 0.4119 | 0.8405 | 0.3383 | 0.348 | 0.5668 | 0.6627 | 0.2615 | 0.4528 | 0.5379 | 0.4824 | 0.6929 | 0.7515 | 0.4282 | 0.5219 | 0.3955 | 0.5539 |
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+ | No log | 8.0 | 496 | 10.7472 | 0.4216 | 0.8338 | 0.3662 | 0.3592 | 0.5737 | 0.6884 | 0.2668 | 0.4624 | 0.5513 | 0.4966 | 0.701 | 0.7561 | 0.4488 | 0.5438 | 0.3943 | 0.5588 |
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+ | 19.6326 | 9.0 | 558 | 10.9720 | 0.3984 | 0.8353 | 0.3183 | 0.3307 | 0.5564 | 0.7087 | 0.2605 | 0.4449 | 0.5241 | 0.4658 | 0.6661 | 0.797 | 0.4371 | 0.5302 | 0.3598 | 0.518 |
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+ | 19.6326 | 10.0 | 620 | 10.9521 | 0.4117 | 0.8392 | 0.3436 | 0.3458 | 0.569 | 0.6785 | 0.2584 | 0.4495 | 0.5315 | 0.4753 | 0.6815 | 0.75 | 0.436 | 0.5195 | 0.3873 | 0.5435 |
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+ | 19.6326 | 11.0 | 682 | 11.0008 | 0.4158 | 0.8449 | 0.3501 | 0.3509 | 0.5711 | 0.6707 | 0.2626 | 0.4517 | 0.5369 | 0.4837 | 0.6821 | 0.7447 | 0.4374 | 0.5237 | 0.3942 | 0.5502 |
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+ | 19.6326 | 12.0 | 744 | 11.0544 | 0.411 | 0.8363 | 0.3415 | 0.3436 | 0.5727 | 0.6689 | 0.259 | 0.4496 | 0.5331 | 0.4775 | 0.6857 | 0.7439 | 0.4336 | 0.5225 | 0.3883 | 0.5438 |
 
 
 
 
 
 
 
 
 
 
 
 
 
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