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---
license: apache-2.0
base_model: PekingU/rtdetr_r50vd_coco_o365
tags:
- generated_from_trainer
model-index:
- name: rtdetr-r50-cppe5-finetune-use_focal-False
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-r50-cppe5-finetune-use_focal-False
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.
It achieves the following results on the evaluation set:
- Loss: 10.2265
- Map: 0.3751
- Map 50: 0.5356
- Map 75: 0.4176
- Map Small: 0.5517
- Map Medium: 0.3568
- Map Large: 0.5283
- Mar 1: 0.329
- Mar 10: 0.6005
- Mar 100: 0.6462
- Mar Small: 0.5882
- Mar Medium: 0.5601
- Mar Large: 0.7161
- Map Coverall: 0.3237
- Mar 100 Coverall: 0.8564
- Map Face Shield: 0.4291
- Mar 100 Face Shield: 0.8467
- Map Gloves: 0.6116
- Mar 100 Gloves: 0.7638
- Map Goggles: 0.5111
- Mar 100 Goggles: 0.7643
- Map Mask: 0.0
- Mar 100 Mask: 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: linear
- lr_scheduler_warmup_steps: 300
- 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 | 106 | 48.0056 | 0.0096 | 0.0182 | 0.0078 | 0.0004 | 0.0011 | 0.0141 | 0.0279 | 0.0877 | 0.1286 | 0.0364 | 0.0457 | 0.2074 | 0.0454 | 0.3986 | 0.0008 | 0.0467 | 0.0014 | 0.0836 | 0.0002 | 0.1141 | 0.0 | 0.0 |
| No log | 2.0 | 212 | 24.1177 | 0.0533 | 0.0967 | 0.0483 | 0.0429 | 0.0161 | 0.0799 | 0.0924 | 0.2249 | 0.2994 | 0.1024 | 0.1912 | 0.4803 | 0.1701 | 0.63 | 0.0057 | 0.3213 | 0.07 | 0.3301 | 0.0207 | 0.2156 | 0.0 | 0.0 |
| No log | 3.0 | 318 | 19.6837 | 0.0909 | 0.1714 | 0.0842 | 0.1028 | 0.0561 | 0.1558 | 0.168 | 0.3546 | 0.4261 | 0.2402 | 0.3345 | 0.5601 | 0.1759 | 0.6977 | 0.0739 | 0.508 | 0.1338 | 0.5059 | 0.0708 | 0.4187 | 0.0 | 0.0 |
| No log | 4.0 | 424 | 15.9325 | 0.1186 | 0.2136 | 0.1107 | 0.0801 | 0.0859 | 0.2414 | 0.1884 | 0.3751 | 0.4496 | 0.262 | 0.3839 | 0.5603 | 0.2001 | 0.7092 | 0.0708 | 0.5373 | 0.1727 | 0.5123 | 0.1493 | 0.4891 | 0.0 | 0.0 |
| 46.7509 | 5.0 | 530 | 15.7219 | 0.1652 | 0.2835 | 0.1715 | 0.1035 | 0.13 | 0.2798 | 0.2215 | 0.3943 | 0.4835 | 0.3143 | 0.4257 | 0.58 | 0.2815 | 0.7286 | 0.1155 | 0.616 | 0.2126 | 0.5466 | 0.2163 | 0.5266 | 0.0 | 0.0 |
| 46.7509 | 6.0 | 636 | 15.2971 | 0.1521 | 0.2608 | 0.1585 | 0.1615 | 0.107 | 0.3026 | 0.2048 | 0.3936 | 0.4832 | 0.3281 | 0.4196 | 0.5982 | 0.2162 | 0.7461 | 0.1248 | 0.608 | 0.2377 | 0.5525 | 0.1817 | 0.5094 | 0.0 | 0.0 |
| 46.7509 | 7.0 | 742 | 14.7975 | 0.1739 | 0.3033 | 0.1663 | 0.1774 | 0.1249 | 0.2946 | 0.22 | 0.4152 | 0.4941 | 0.3349 | 0.4265 | 0.6162 | 0.2714 | 0.7359 | 0.1555 | 0.64 | 0.2563 | 0.5648 | 0.1865 | 0.5297 | 0.0 | 0.0 |
| 46.7509 | 8.0 | 848 | 14.0780 | 0.173 | 0.3097 | 0.17 | 0.1574 | 0.1366 | 0.3098 | 0.2273 | 0.4161 | 0.491 | 0.3402 | 0.4332 | 0.6074 | 0.2117 | 0.7401 | 0.1694 | 0.6413 | 0.2664 | 0.5626 | 0.2175 | 0.5109 | 0.0 | 0.0 |
| 46.7509 | 9.0 | 954 | 14.7545 | 0.1838 | 0.3225 | 0.1884 | 0.1876 | 0.1506 | 0.3254 | 0.2366 | 0.4295 | 0.5001 | 0.3676 | 0.4306 | 0.6197 | 0.2092 | 0.7424 | 0.1855 | 0.648 | 0.2837 | 0.563 | 0.2407 | 0.5469 | 0.0 | 0.0 |
| 15.0328 | 10.0 | 1060 | 14.8555 | 0.1901 | 0.3198 | 0.1947 | 0.1801 | 0.1621 | 0.3094 | 0.2376 | 0.4254 | 0.4966 | 0.3667 | 0.4266 | 0.6081 | 0.2333 | 0.7355 | 0.2159 | 0.6267 | 0.274 | 0.5676 | 0.2271 | 0.5531 | 0.0 | 0.0 |
| 15.0328 | 11.0 | 1166 | 14.5398 | 0.2122 | 0.3554 | 0.2155 | 0.1985 | 0.1684 | 0.3698 | 0.2458 | 0.4265 | 0.5005 | 0.3759 | 0.4312 | 0.6075 | 0.3117 | 0.7475 | 0.2296 | 0.6307 | 0.2706 | 0.5667 | 0.2489 | 0.5578 | 0.0 | 0.0 |
| 15.0328 | 12.0 | 1272 | 13.9358 | 0.2154 | 0.3669 | 0.2171 | 0.1878 | 0.1602 | 0.3618 | 0.2421 | 0.4238 | 0.5003 | 0.3679 | 0.4206 | 0.6028 | 0.2657 | 0.7433 | 0.2847 | 0.6507 | 0.2909 | 0.5763 | 0.2358 | 0.5312 | 0.0 | 0.0 |
| 15.0328 | 13.0 | 1378 | 13.4203 | 0.2098 | 0.3538 | 0.2204 | 0.1888 | 0.1669 | 0.344 | 0.25 | 0.4176 | 0.5 | 0.3465 | 0.4387 | 0.6184 | 0.2666 | 0.7558 | 0.2454 | 0.6707 | 0.3017 | 0.5813 | 0.2355 | 0.4922 | 0.0 | 0.0 |
| 15.0328 | 14.0 | 1484 | 13.6884 | 0.1899 | 0.3258 | 0.1903 | 0.1759 | 0.169 | 0.3004 | 0.2455 | 0.4249 | 0.4988 | 0.3645 | 0.4277 | 0.6163 | 0.2431 | 0.7456 | 0.25 | 0.656 | 0.2834 | 0.5877 | 0.1732 | 0.5047 | 0.0 | 0.0 |
| 13.3953 | 15.0 | 1590 | 13.1320 | 0.1898 | 0.3258 | 0.192 | 0.1843 | 0.1431 | 0.3191 | 0.2492 | 0.4182 | 0.4935 | 0.362 | 0.4115 | 0.6128 | 0.2222 | 0.7401 | 0.2256 | 0.6347 | 0.2892 | 0.5694 | 0.2119 | 0.5234 | 0.0 | 0.0 |
| 13.3953 | 16.0 | 1696 | 12.9858 | 0.2019 | 0.3335 | 0.2047 | 0.1801 | 0.1637 | 0.3552 | 0.2554 | 0.4233 | 0.5005 | 0.3673 | 0.4268 | 0.6094 | 0.2745 | 0.7498 | 0.2364 | 0.644 | 0.2863 | 0.5712 | 0.2123 | 0.5375 | 0.0 | 0.0 |
| 13.3953 | 17.0 | 1802 | 12.9965 | 0.2013 | 0.3422 | 0.1992 | 0.1809 | 0.1569 | 0.3458 | 0.248 | 0.4273 | 0.4914 | 0.3632 | 0.4103 | 0.6139 | 0.2725 | 0.7392 | 0.227 | 0.628 | 0.283 | 0.5712 | 0.2238 | 0.5188 | 0.0 | 0.0 |
| 13.3953 | 18.0 | 1908 | 12.9245 | 0.1948 | 0.3346 | 0.1923 | 0.186 | 0.1505 | 0.3242 | 0.2386 | 0.4303 | 0.5049 | 0.393 | 0.4192 | 0.6206 | 0.2743 | 0.7392 | 0.219 | 0.644 | 0.2984 | 0.574 | 0.1824 | 0.5672 | 0.0 | 0.0 |
| 12.6173 | 19.0 | 2014 | 12.9508 | 0.209 | 0.3508 | 0.2072 | 0.1722 | 0.15 | 0.3759 | 0.2444 | 0.4307 | 0.5022 | 0.3574 | 0.4338 | 0.6149 | 0.2605 | 0.7456 | 0.2698 | 0.6533 | 0.2983 | 0.584 | 0.2166 | 0.5281 | 0.0 | 0.0 |
| 12.6173 | 20.0 | 2120 | 13.3318 | 0.2137 | 0.3577 | 0.223 | 0.1887 | 0.168 | 0.3762 | 0.2458 | 0.4233 | 0.4925 | 0.3564 | 0.4209 | 0.6174 | 0.2679 | 0.7382 | 0.2664 | 0.636 | 0.2961 | 0.5662 | 0.2382 | 0.5219 | 0.0 | 0.0 |
| 12.6173 | 21.0 | 2226 | 13.0245 | 0.2147 | 0.3564 | 0.2197 | 0.1747 | 0.1795 | 0.3656 | 0.2553 | 0.4266 | 0.4976 | 0.3564 | 0.4265 | 0.6323 | 0.2778 | 0.7387 | 0.2786 | 0.6533 | 0.299 | 0.5758 | 0.2182 | 0.5203 | 0.0 | 0.0 |
| 12.6173 | 22.0 | 2332 | 12.9212 | 0.2161 | 0.3697 | 0.2196 | 0.1798 | 0.1758 | 0.3509 | 0.2553 | 0.4358 | 0.5001 | 0.3676 | 0.4165 | 0.6155 | 0.2721 | 0.7355 | 0.2841 | 0.648 | 0.3008 | 0.5813 | 0.2235 | 0.5359 | 0.0 | 0.0 |
| 12.6173 | 23.0 | 2438 | 12.9598 | 0.2229 | 0.3751 | 0.2366 | 0.1823 | 0.177 | 0.3596 | 0.2533 | 0.4256 | 0.4976 | 0.3697 | 0.4193 | 0.6026 | 0.2901 | 0.7401 | 0.3074 | 0.6507 | 0.2954 | 0.5831 | 0.2218 | 0.5141 | 0.0 | 0.0 |
| 12.1016 | 24.0 | 2544 | 12.9207 | 0.2141 | 0.3637 | 0.2115 | 0.1954 | 0.1776 | 0.3447 | 0.2464 | 0.4278 | 0.4968 | 0.3665 | 0.4224 | 0.607 | 0.2536 | 0.7378 | 0.3149 | 0.6373 | 0.2955 | 0.5776 | 0.2064 | 0.5312 | 0.0 | 0.0 |
| 12.1016 | 25.0 | 2650 | 12.8912 | 0.2215 | 0.3703 | 0.2287 | 0.197 | 0.175 | 0.3619 | 0.2538 | 0.4312 | 0.4979 | 0.3657 | 0.4263 | 0.6035 | 0.2812 | 0.7465 | 0.3006 | 0.628 | 0.3082 | 0.5913 | 0.2173 | 0.5234 | 0.0 | 0.0 |
| 12.1016 | 26.0 | 2756 | 12.7256 | 0.2198 | 0.3724 | 0.2245 | 0.1926 | 0.1776 | 0.3522 | 0.2465 | 0.4341 | 0.5016 | 0.3742 | 0.4312 | 0.6073 | 0.2757 | 0.7479 | 0.2864 | 0.6333 | 0.3018 | 0.5831 | 0.2351 | 0.5437 | 0.0 | 0.0 |
| 12.1016 | 27.0 | 2862 | 12.7695 | 0.2259 | 0.3771 | 0.2409 | 0.1941 | 0.1854 | 0.3571 | 0.249 | 0.433 | 0.5027 | 0.3773 | 0.4412 | 0.591 | 0.2804 | 0.7447 | 0.3012 | 0.6333 | 0.3023 | 0.5872 | 0.2457 | 0.5484 | 0.0 | 0.0 |
| 12.1016 | 28.0 | 2968 | 12.8203 | 0.2231 | 0.3781 | 0.2333 | 0.1961 | 0.1837 | 0.3527 | 0.2492 | 0.4328 | 0.5001 | 0.3718 | 0.4331 | 0.607 | 0.2634 | 0.7456 | 0.3069 | 0.6347 | 0.3026 | 0.5872 | 0.2427 | 0.5328 | 0.0 | 0.0 |
| 11.5997 | 29.0 | 3074 | 12.7159 | 0.2205 | 0.3758 | 0.2306 | 0.194 | 0.177 | 0.3562 | 0.251 | 0.4322 | 0.5029 | 0.3882 | 0.4349 | 0.6057 | 0.258 | 0.7465 | 0.3073 | 0.6413 | 0.3037 | 0.5826 | 0.2336 | 0.5437 | 0.0 | 0.0 |
| 11.5997 | 30.0 | 3180 | 12.7243 | 0.2205 | 0.3735 | 0.2311 | 0.1938 | 0.1773 | 0.3609 | 0.2515 | 0.4326 | 0.5016 | 0.3869 | 0.4314 | 0.5982 | 0.2638 | 0.7438 | 0.2967 | 0.6347 | 0.3029 | 0.584 | 0.2393 | 0.5453 | 0.0 | 0.0 |
### Framework versions
- Transformers 4.45.0.dev0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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