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---
library_name: transformers
license: apache-2.0
base_model: PekingU/rtdetr_v2_r50vd
tags:
- generated_from_trainer
model-index:
- name: rtdetr-v2-r50-cppe5-finetune-2
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# rtdetr-v2-r50-cppe5-finetune-2
This model is a fine-tuned version of [PekingU/rtdetr_v2_r50vd](https://huggingface.co/PekingU/rtdetr_v2_r50vd) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 10.9252
- Map: 0.5289
- Map 50: 0.8232
- Map 75: 0.5878
- Map Small: 0.5195
- Map Medium: 0.4579
- Map Large: 0.7392
- Mar 1: 0.3957
- Mar 10: 0.6781
- Mar 100: 0.7168
- Mar Small: 0.6001
- Mar Medium: 0.684
- Mar Large: 0.8569
- Map Coverall: 0.5136
- Mar 100 Coverall: 0.8128
- Map Face Shield: 0.615
- Mar 100 Face Shield: 0.7588
- Map Gloves: 0.4422
- Mar 100 Gloves: 0.6508
- Map Goggles: 0.5149
- Mar 100 Goggles: 0.7103
- Map Mask: 0.5587
- Mar 100 Mask: 0.651
## 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: Use OptimizerNames.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_steps: 300
- num_epochs: 40
### 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 | 30.1306 | 0.0033 | 0.0092 | 0.0019 | 0.0019 | 0.0037 | 0.0043 | 0.0161 | 0.0548 | 0.1235 | 0.0321 | 0.0991 | 0.196 | 0.0071 | 0.2396 | 0.0002 | 0.1253 | 0.0005 | 0.1089 | 0.0 | 0.0 | 0.0087 | 0.1436 |
| No log | 2.0 | 214 | 16.1409 | 0.08 | 0.1545 | 0.0782 | 0.0416 | 0.0572 | 0.1101 | 0.1576 | 0.3669 | 0.467 | 0.2569 | 0.4071 | 0.6935 | 0.2097 | 0.6905 | 0.0102 | 0.5152 | 0.0474 | 0.4062 | 0.0107 | 0.2677 | 0.1221 | 0.4551 |
| No log | 3.0 | 321 | 13.2903 | 0.1968 | 0.3682 | 0.1824 | 0.0801 | 0.1695 | 0.3259 | 0.2393 | 0.4536 | 0.5143 | 0.2707 | 0.4941 | 0.7188 | 0.4182 | 0.6982 | 0.077 | 0.5608 | 0.0688 | 0.4513 | 0.1206 | 0.3769 | 0.2993 | 0.4844 |
| No log | 4.0 | 428 | 12.3417 | 0.2414 | 0.45 | 0.2204 | 0.0782 | 0.2017 | 0.3843 | 0.2618 | 0.4489 | 0.5207 | 0.2963 | 0.4924 | 0.7383 | 0.5136 | 0.7261 | 0.1126 | 0.5532 | 0.0948 | 0.4402 | 0.1453 | 0.3862 | 0.3409 | 0.4978 |
| 50.7583 | 5.0 | 535 | 11.9585 | 0.2679 | 0.4948 | 0.2476 | 0.1057 | 0.2268 | 0.3871 | 0.2772 | 0.4784 | 0.5446 | 0.3311 | 0.5048 | 0.7393 | 0.5397 | 0.7144 | 0.1776 | 0.5772 | 0.0923 | 0.4688 | 0.1827 | 0.44 | 0.3473 | 0.5227 |
| 50.7583 | 6.0 | 642 | 11.8258 | 0.2968 | 0.5495 | 0.2862 | 0.1496 | 0.252 | 0.4786 | 0.2938 | 0.4892 | 0.5473 | 0.3863 | 0.5011 | 0.7378 | 0.5384 | 0.7144 | 0.26 | 0.5468 | 0.131 | 0.4795 | 0.2031 | 0.4754 | 0.3515 | 0.5204 |
| 50.7583 | 7.0 | 749 | 12.4262 | 0.2653 | 0.4908 | 0.2367 | 0.1111 | 0.2373 | 0.3968 | 0.2659 | 0.4653 | 0.5364 | 0.3351 | 0.4954 | 0.7407 | 0.5349 | 0.6955 | 0.2055 | 0.5203 | 0.0872 | 0.4799 | 0.1766 | 0.4662 | 0.3223 | 0.52 |
| 50.7583 | 8.0 | 856 | 11.9738 | 0.3057 | 0.5759 | 0.285 | 0.1069 | 0.2512 | 0.5298 | 0.3007 | 0.4872 | 0.5626 | 0.3712 | 0.5167 | 0.7592 | 0.5483 | 0.6937 | 0.275 | 0.5646 | 0.1421 | 0.4996 | 0.2093 | 0.5262 | 0.3537 | 0.5289 |
| 50.7583 | 9.0 | 963 | 11.9453 | 0.3058 | 0.5724 | 0.2912 | 0.1435 | 0.2654 | 0.4913 | 0.3092 | 0.4881 | 0.5627 | 0.409 | 0.5199 | 0.7637 | 0.5258 | 0.6991 | 0.2898 | 0.543 | 0.163 | 0.4946 | 0.1925 | 0.5354 | 0.3581 | 0.5413 |
| 15.0731 | 10.0 | 1070 | 12.2255 | 0.3027 | 0.5728 | 0.2594 | 0.1298 | 0.2562 | 0.5114 | 0.2973 | 0.4767 | 0.5528 | 0.3384 | 0.5138 | 0.7396 | 0.5214 | 0.6878 | 0.2569 | 0.5392 | 0.1931 | 0.4808 | 0.1869 | 0.5231 | 0.3554 | 0.5329 |
| 15.0731 | 11.0 | 1177 | 12.5078 | 0.295 | 0.5725 | 0.2581 | 0.1354 | 0.2377 | 0.5292 | 0.293 | 0.4768 | 0.5405 | 0.3129 | 0.49 | 0.7511 | 0.5206 | 0.6968 | 0.2437 | 0.5089 | 0.1645 | 0.4817 | 0.2058 | 0.5185 | 0.3405 | 0.4964 |
| 15.0731 | 12.0 | 1284 | 12.5919 | 0.2983 | 0.5643 | 0.2728 | 0.1191 | 0.2515 | 0.5134 | 0.2922 | 0.4722 | 0.5341 | 0.3446 | 0.4901 | 0.7423 | 0.5184 | 0.6977 | 0.2272 | 0.5127 | 0.1873 | 0.4589 | 0.2134 | 0.5015 | 0.3452 | 0.4996 |
| 15.0731 | 13.0 | 1391 | 12.3976 | 0.2891 | 0.5358 | 0.2613 | 0.135 | 0.2718 | 0.4732 | 0.2889 | 0.4902 | 0.5592 | 0.3769 | 0.5097 | 0.7579 | 0.5143 | 0.7018 | 0.211 | 0.5481 | 0.1809 | 0.4955 | 0.216 | 0.5323 | 0.3231 | 0.5182 |
| 15.0731 | 14.0 | 1498 | 12.9003 | 0.287 | 0.5522 | 0.2447 | 0.1257 | 0.2583 | 0.4905 | 0.2795 | 0.4689 | 0.5417 | 0.3617 | 0.4917 | 0.7422 | 0.5046 | 0.6932 | 0.2454 | 0.5139 | 0.1973 | 0.504 | 0.1597 | 0.4846 | 0.3282 | 0.5129 |
| 13.1572 | 15.0 | 1605 | 12.6192 | 0.3073 | 0.5783 | 0.2877 | 0.1218 | 0.2839 | 0.5186 | 0.2992 | 0.4899 | 0.5512 | 0.3749 | 0.4869 | 0.7463 | 0.5127 | 0.7045 | 0.2924 | 0.5177 | 0.1725 | 0.5031 | 0.2065 | 0.5185 | 0.3525 | 0.512 |
| 13.1572 | 16.0 | 1712 | 12.6974 | 0.3148 | 0.5891 | 0.2976 | 0.1418 | 0.2752 | 0.547 | 0.2972 | 0.4855 | 0.5477 | 0.3664 | 0.4915 | 0.7403 | 0.5252 | 0.7054 | 0.2604 | 0.5392 | 0.2203 | 0.4946 | 0.2306 | 0.4923 | 0.3374 | 0.5067 |
| 13.1572 | 17.0 | 1819 | 12.7546 | 0.309 | 0.5834 | 0.2957 | 0.1464 | 0.2622 | 0.5244 | 0.2892 | 0.4786 | 0.5422 | 0.3815 | 0.487 | 0.7318 | 0.5321 | 0.7081 | 0.2632 | 0.5316 | 0.2115 | 0.4656 | 0.207 | 0.5046 | 0.3312 | 0.5009 |
| 13.1572 | 18.0 | 1926 | 12.4739 | 0.3261 | 0.6068 | 0.3129 | 0.1463 | 0.2788 | 0.563 | 0.308 | 0.4842 | 0.5405 | 0.3694 | 0.4842 | 0.7321 | 0.5407 | 0.7005 | 0.3057 | 0.5443 | 0.1988 | 0.4531 | 0.2305 | 0.4969 | 0.3549 | 0.5076 |
| 12.1044 | 19.0 | 2033 | 12.7141 | 0.3043 | 0.58 | 0.275 | 0.1231 | 0.2812 | 0.4983 | 0.2993 | 0.4846 | 0.5432 | 0.3575 | 0.4988 | 0.7318 | 0.5016 | 0.6919 | 0.2864 | 0.5291 | 0.2124 | 0.4871 | 0.1879 | 0.4923 | 0.3332 | 0.5156 |
| 12.1044 | 20.0 | 2140 | 12.9148 | 0.3047 | 0.5753 | 0.2695 | 0.1177 | 0.2649 | 0.5339 | 0.2967 | 0.472 | 0.528 | 0.3175 | 0.4851 | 0.7236 | 0.5224 | 0.6883 | 0.2746 | 0.5165 | 0.1856 | 0.4728 | 0.2051 | 0.4569 | 0.3358 | 0.5053 |
| 12.1044 | 21.0 | 2247 | 12.9878 | 0.2933 | 0.5616 | 0.2602 | 0.1003 | 0.2634 | 0.5186 | 0.2895 | 0.4822 | 0.5381 | 0.3471 | 0.4833 | 0.7167 | 0.4917 | 0.7171 | 0.2743 | 0.5228 | 0.1895 | 0.4759 | 0.189 | 0.4785 | 0.3218 | 0.4964 |
| 12.1044 | 22.0 | 2354 | 13.0391 | 0.3147 | 0.5842 | 0.2908 | 0.1329 | 0.2609 | 0.5326 | 0.2863 | 0.4803 | 0.5368 | 0.3258 | 0.4759 | 0.7315 | 0.5115 | 0.7068 | 0.3036 | 0.4987 | 0.2268 | 0.4906 | 0.1915 | 0.4738 | 0.3402 | 0.5142 |
| 12.1044 | 23.0 | 2461 | 13.2321 | 0.2848 | 0.5356 | 0.2554 | 0.1215 | 0.2375 | 0.5009 | 0.2792 | 0.4757 | 0.5336 | 0.3475 | 0.4788 | 0.7255 | 0.4874 | 0.6986 | 0.2456 | 0.4987 | 0.1974 | 0.4812 | 0.173 | 0.4908 | 0.3203 | 0.4987 |
| 11.3907 | 24.0 | 2568 | 12.9094 | 0.2921 | 0.5297 | 0.2786 | 0.1582 | 0.2313 | 0.4932 | 0.2627 | 0.4665 | 0.5309 | 0.3716 | 0.4684 | 0.7263 | 0.5157 | 0.7095 | 0.2247 | 0.5 | 0.2192 | 0.4754 | 0.1818 | 0.4692 | 0.3193 | 0.5004 |
| 11.3907 | 25.0 | 2675 | 13.1896 | 0.2916 | 0.5488 | 0.2705 | 0.1376 | 0.2321 | 0.5111 | 0.2805 | 0.468 | 0.5292 | 0.3219 | 0.4672 | 0.7313 | 0.4882 | 0.6995 | 0.2901 | 0.5038 | 0.2008 | 0.4812 | 0.1645 | 0.46 | 0.3146 | 0.5013 |
| 11.3907 | 26.0 | 2782 | 13.3057 | 0.2814 | 0.5293 | 0.2534 | 0.1361 | 0.237 | 0.5023 | 0.2719 | 0.4709 | 0.5314 | 0.3286 | 0.4737 | 0.7395 | 0.4358 | 0.682 | 0.2713 | 0.5013 | 0.2023 | 0.4929 | 0.1942 | 0.4877 | 0.3035 | 0.4933 |
| 11.3907 | 27.0 | 2889 | 13.2976 | 0.2946 | 0.539 | 0.2662 | 0.1257 | 0.2337 | 0.5238 | 0.274 | 0.4691 | 0.5301 | 0.3015 | 0.4757 | 0.7401 | 0.4843 | 0.6932 | 0.2787 | 0.5025 | 0.1916 | 0.4683 | 0.1903 | 0.4908 | 0.328 | 0.4956 |
| 11.3907 | 28.0 | 2996 | 13.2500 | 0.2861 | 0.536 | 0.2679 | 0.1326 | 0.2341 | 0.4953 | 0.2837 | 0.4718 | 0.5304 | 0.3165 | 0.4726 | 0.7186 | 0.5058 | 0.7063 | 0.2518 | 0.5076 | 0.1894 | 0.4777 | 0.1731 | 0.4677 | 0.3104 | 0.4929 |
| 10.7552 | 29.0 | 3103 | 12.9360 | 0.3062 | 0.5605 | 0.2827 | 0.1408 | 0.2672 | 0.5143 | 0.2911 | 0.4806 | 0.534 | 0.3076 | 0.4856 | 0.7429 | 0.5045 | 0.6982 | 0.2797 | 0.5101 | 0.2048 | 0.4902 | 0.2139 | 0.4815 | 0.3282 | 0.4898 |
| 10.7552 | 30.0 | 3210 | 13.0449 | 0.3156 | 0.5766 | 0.294 | 0.1465 | 0.2623 | 0.5119 | 0.2914 | 0.4803 | 0.5382 | 0.3286 | 0.4759 | 0.7233 | 0.4969 | 0.7045 | 0.3117 | 0.519 | 0.2131 | 0.4996 | 0.2239 | 0.4738 | 0.3324 | 0.4942 |
| 10.7552 | 31.0 | 3317 | 13.2706 | 0.2812 | 0.5226 | 0.2591 | 0.1406 | 0.2324 | 0.4773 | 0.2754 | 0.4651 | 0.5246 | 0.3284 | 0.4658 | 0.7171 | 0.459 | 0.6874 | 0.2297 | 0.5063 | 0.2102 | 0.4848 | 0.1874 | 0.4477 | 0.3199 | 0.4969 |
| 10.7552 | 32.0 | 3424 | 13.0841 | 0.2858 | 0.5304 | 0.2602 | 0.1358 | 0.2482 | 0.4722 | 0.2823 | 0.4772 | 0.5352 | 0.3454 | 0.4845 | 0.7112 | 0.5004 | 0.7063 | 0.2369 | 0.5139 | 0.203 | 0.4955 | 0.1745 | 0.4662 | 0.3141 | 0.4942 |
| 10.2631 | 33.0 | 3531 | 12.9221 | 0.3048 | 0.5746 | 0.2841 | 0.143 | 0.2504 | 0.51 | 0.2899 | 0.4708 | 0.5359 | 0.3624 | 0.487 | 0.7162 | 0.491 | 0.7081 | 0.304 | 0.5278 | 0.2065 | 0.492 | 0.1978 | 0.4538 | 0.3248 | 0.4978 |
| 10.2631 | 34.0 | 3638 | 12.9561 | 0.3023 | 0.5617 | 0.2687 | 0.1488 | 0.2626 | 0.4948 | 0.2924 | 0.4769 | 0.5318 | 0.3244 | 0.4858 | 0.7071 | 0.5001 | 0.7108 | 0.2777 | 0.4823 | 0.2106 | 0.492 | 0.1998 | 0.4754 | 0.3231 | 0.4987 |
| 10.2631 | 35.0 | 3745 | 12.9901 | 0.3112 | 0.5755 | 0.2957 | 0.1425 | 0.253 | 0.5239 | 0.2966 | 0.4697 | 0.5293 | 0.3265 | 0.4762 | 0.7156 | 0.4979 | 0.7027 | 0.3118 | 0.5013 | 0.2161 | 0.4844 | 0.2095 | 0.4662 | 0.3206 | 0.492 |
| 10.2631 | 36.0 | 3852 | 12.9676 | 0.3082 | 0.5757 | 0.2826 | 0.1399 | 0.2568 | 0.5179 | 0.296 | 0.4652 | 0.5255 | 0.3093 | 0.4788 | 0.7221 | 0.5139 | 0.7086 | 0.2789 | 0.4848 | 0.2089 | 0.4951 | 0.2139 | 0.4523 | 0.3252 | 0.4867 |
| 10.2631 | 37.0 | 3959 | 12.9603 | 0.3154 | 0.5872 | 0.294 | 0.1415 | 0.2549 | 0.5283 | 0.3011 | 0.4676 | 0.5282 | 0.317 | 0.4739 | 0.7252 | 0.5015 | 0.7059 | 0.3124 | 0.4975 | 0.2096 | 0.4906 | 0.2304 | 0.46 | 0.3229 | 0.4871 |
| 9.744 | 38.0 | 4066 | 12.9339 | 0.3146 | 0.5811 | 0.2906 | 0.1366 | 0.2556 | 0.5248 | 0.2976 | 0.4678 | 0.5252 | 0.3072 | 0.4768 | 0.7116 | 0.5143 | 0.7059 | 0.3002 | 0.5051 | 0.2073 | 0.4692 | 0.2263 | 0.4569 | 0.3251 | 0.4889 |
| 9.744 | 39.0 | 4173 | 12.9478 | 0.3174 | 0.5849 | 0.2971 | 0.1443 | 0.2569 | 0.5225 | 0.3002 | 0.4711 | 0.5315 | 0.3106 | 0.477 | 0.7177 | 0.51 | 0.7113 | 0.3174 | 0.5127 | 0.2151 | 0.4804 | 0.2202 | 0.4615 | 0.3242 | 0.4916 |
| 9.744 | 40.0 | 4280 | 12.9020 | 0.3204 | 0.5974 | 0.2952 | 0.1477 | 0.2578 | 0.5216 | 0.2975 | 0.4722 | 0.5299 | 0.303 | 0.476 | 0.7165 | 0.5197 | 0.7113 | 0.3134 | 0.5076 | 0.2225 | 0.483 | 0.2217 | 0.4615 | 0.3248 | 0.4862 |
### Framework versions
- Transformers 4.49.0
- Pytorch 2.8.0+cu128
- Datasets 2.20.0
- Tokenizers 0.21.4
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