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---
library_name: transformers
license: apache-2.0
base_model: facebook/detr-resnet-50
tags:
- generated_from_trainer
model-index:
- name: detr_finetuned_cppe5
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. -->
# detr_finetuned_cppe5
This model is a fine-tuned version of [facebook/detr-resnet-50](https://huggingface.co/facebook/detr-resnet-50) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2803
- Map: 0.2236
- Map 50: 0.4243
- Map 75: 0.206
- Map Small: 0.087
- Map Medium: 0.2507
- Map Large: 0.2808
- Mar 1: 0.28
- Mar 10: 0.4603
- Mar 100: 0.4703
- Mar Small: 0.2619
- Mar Medium: 0.4212
- Mar Large: 0.5738
- Map Coverall: 0.5876
- Mar 100 Coverall: 0.7507
- Map Face Shield: 0.0978
- Mar 100 Face Shield: 0.5019
- Map Gloves: 0.1088
- Mar 100 Gloves: 0.3443
- Map Goggles: 0.0251
- Mar 100 Goggles: 0.3109
- Map Mask: 0.2988
- Mar 100 Mask: 0.4436
## 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: cosine
- 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 | 101 | 2.2664 | 0.0299 | 0.0624 | 0.0218 | 0.008 | 0.0698 | 0.0295 | 0.081 | 0.1593 | 0.1948 | 0.0526 | 0.1853 | 0.2126 | 0.1248 | 0.642 | 0.0 | 0.0 | 0.0053 | 0.0805 | 0.0 | 0.0 | 0.0193 | 0.2517 |
| No log | 2.0 | 202 | 2.0505 | 0.0534 | 0.1073 | 0.0505 | 0.0065 | 0.095 | 0.0546 | 0.0986 | 0.1795 | 0.2122 | 0.0649 | 0.2148 | 0.2305 | 0.2306 | 0.67 | 0.0 | 0.0 | 0.0054 | 0.1437 | 0.0 | 0.0 | 0.0311 | 0.2471 |
| No log | 3.0 | 303 | 1.9191 | 0.0388 | 0.0853 | 0.032 | 0.0069 | 0.0715 | 0.0418 | 0.1113 | 0.2058 | 0.2444 | 0.0838 | 0.2401 | 0.2708 | 0.1412 | 0.6947 | 0.0 | 0.0 | 0.0138 | 0.1943 | 0.0 | 0.0 | 0.0391 | 0.3331 |
| No log | 4.0 | 404 | 1.9140 | 0.0689 | 0.1334 | 0.0686 | 0.0119 | 0.1069 | 0.0613 | 0.1073 | 0.2019 | 0.2281 | 0.1048 | 0.2354 | 0.2333 | 0.2665 | 0.6 | 0.0184 | 0.05 | 0.015 | 0.1828 | 0.0 | 0.0 | 0.0445 | 0.3076 |
| 2.2885 | 5.0 | 505 | 1.8535 | 0.065 | 0.1347 | 0.0579 | 0.0107 | 0.109 | 0.0681 | 0.1064 | 0.1994 | 0.2271 | 0.0641 | 0.2213 | 0.2554 | 0.2582 | 0.6707 | 0.0022 | 0.0426 | 0.0233 | 0.15 | 0.0 | 0.0 | 0.0414 | 0.2721 |
| 2.2885 | 6.0 | 606 | 1.6854 | 0.106 | 0.2131 | 0.0866 | 0.0174 | 0.154 | 0.1124 | 0.1623 | 0.2819 | 0.2947 | 0.1207 | 0.2903 | 0.3191 | 0.3878 | 0.6953 | 0.0273 | 0.2389 | 0.0375 | 0.2167 | 0.0 | 0.0 | 0.0772 | 0.3227 |
| 2.2885 | 7.0 | 707 | 1.7142 | 0.1321 | 0.2588 | 0.1213 | 0.0287 | 0.1694 | 0.1454 | 0.155 | 0.2548 | 0.2629 | 0.104 | 0.2571 | 0.2894 | 0.4419 | 0.6727 | 0.0194 | 0.1111 | 0.0291 | 0.1684 | 0.0158 | 0.0145 | 0.1541 | 0.3477 |
| 2.2885 | 8.0 | 808 | 1.6260 | 0.1329 | 0.2764 | 0.1116 | 0.0309 | 0.1806 | 0.133 | 0.1733 | 0.2959 | 0.3231 | 0.1237 | 0.3281 | 0.3412 | 0.4414 | 0.716 | 0.0365 | 0.263 | 0.0328 | 0.2598 | 0.002 | 0.0345 | 0.1517 | 0.3424 |
| 2.2885 | 9.0 | 909 | 1.5600 | 0.144 | 0.2839 | 0.1295 | 0.0413 | 0.1806 | 0.1517 | 0.1962 | 0.34 | 0.357 | 0.1705 | 0.3582 | 0.3866 | 0.4652 | 0.6833 | 0.0401 | 0.3315 | 0.0331 | 0.2517 | 0.0346 | 0.1145 | 0.1472 | 0.4041 |
| 1.8836 | 10.0 | 1010 | 1.6155 | 0.132 | 0.2677 | 0.1157 | 0.0192 | 0.1619 | 0.1535 | 0.1793 | 0.3314 | 0.3432 | 0.1246 | 0.3549 | 0.3759 | 0.4695 | 0.6727 | 0.0321 | 0.3333 | 0.0422 | 0.2201 | 0.0156 | 0.1236 | 0.1008 | 0.3663 |
| 1.8836 | 11.0 | 1111 | 1.7756 | 0.131 | 0.273 | 0.1157 | 0.0451 | 0.1763 | 0.1382 | 0.169 | 0.2725 | 0.2772 | 0.1249 | 0.2801 | 0.2997 | 0.4245 | 0.654 | 0.0371 | 0.2019 | 0.04 | 0.1937 | 0.0051 | 0.0164 | 0.1482 | 0.3203 |
| 1.8836 | 12.0 | 1212 | 1.5594 | 0.1479 | 0.2988 | 0.1274 | 0.0357 | 0.1797 | 0.1682 | 0.1802 | 0.339 | 0.354 | 0.1872 | 0.3288 | 0.4026 | 0.4925 | 0.6933 | 0.0419 | 0.3444 | 0.0535 | 0.254 | 0.0065 | 0.0655 | 0.145 | 0.4128 |
| 1.8836 | 13.0 | 1313 | 1.5275 | 0.1686 | 0.3448 | 0.1442 | 0.0419 | 0.1905 | 0.1946 | 0.2034 | 0.3691 | 0.3835 | 0.162 | 0.3604 | 0.4459 | 0.5224 | 0.714 | 0.0573 | 0.4056 | 0.0557 | 0.2351 | 0.0319 | 0.2055 | 0.1757 | 0.3576 |
| 1.8836 | 14.0 | 1414 | 1.4658 | 0.1716 | 0.3471 | 0.1529 | 0.0615 | 0.1918 | 0.1997 | 0.234 | 0.4032 | 0.4258 | 0.244 | 0.3949 | 0.4814 | 0.5247 | 0.72 | 0.0477 | 0.4907 | 0.0605 | 0.2787 | 0.0125 | 0.2382 | 0.2126 | 0.4012 |
| 1.7112 | 15.0 | 1515 | 1.4980 | 0.1632 | 0.3423 | 0.149 | 0.0436 | 0.1925 | 0.1903 | 0.2106 | 0.3644 | 0.3841 | 0.155 | 0.3627 | 0.4528 | 0.5172 | 0.6987 | 0.0357 | 0.4056 | 0.0435 | 0.2425 | 0.023 | 0.2145 | 0.1963 | 0.3593 |
| 1.7112 | 16.0 | 1616 | 1.4760 | 0.1673 | 0.3361 | 0.1462 | 0.0639 | 0.1893 | 0.1917 | 0.2036 | 0.376 | 0.3902 | 0.1922 | 0.3695 | 0.4412 | 0.5163 | 0.6953 | 0.049 | 0.4074 | 0.0763 | 0.2816 | 0.0062 | 0.1745 | 0.1886 | 0.3919 |
| 1.7112 | 17.0 | 1717 | 1.4224 | 0.1841 | 0.3711 | 0.1608 | 0.1013 | 0.208 | 0.2253 | 0.2356 | 0.4147 | 0.4282 | 0.2339 | 0.3828 | 0.5104 | 0.5087 | 0.7247 | 0.0594 | 0.4426 | 0.0771 | 0.304 | 0.0179 | 0.2673 | 0.2575 | 0.4023 |
| 1.7112 | 18.0 | 1818 | 1.4224 | 0.1909 | 0.3743 | 0.17 | 0.082 | 0.2007 | 0.2407 | 0.2446 | 0.4147 | 0.4283 | 0.2211 | 0.3755 | 0.5219 | 0.5453 | 0.7293 | 0.0738 | 0.4833 | 0.0762 | 0.2724 | 0.0141 | 0.2745 | 0.2454 | 0.382 |
| 1.7112 | 19.0 | 1919 | 1.3652 | 0.2068 | 0.4087 | 0.1879 | 0.0874 | 0.2187 | 0.2478 | 0.2572 | 0.4189 | 0.4333 | 0.2443 | 0.4009 | 0.5066 | 0.5488 | 0.726 | 0.0785 | 0.4611 | 0.0913 | 0.3155 | 0.0226 | 0.2382 | 0.293 | 0.4256 |
| 1.5736 | 20.0 | 2020 | 1.3381 | 0.2098 | 0.4139 | 0.1944 | 0.0826 | 0.2269 | 0.2571 | 0.2517 | 0.4231 | 0.437 | 0.223 | 0.4093 | 0.5108 | 0.553 | 0.7353 | 0.0926 | 0.4352 | 0.0892 | 0.2994 | 0.0241 | 0.2836 | 0.2899 | 0.4314 |
| 1.5736 | 21.0 | 2121 | 1.3366 | 0.2142 | 0.4226 | 0.1973 | 0.088 | 0.2302 | 0.2616 | 0.2574 | 0.4299 | 0.4431 | 0.2459 | 0.4053 | 0.5214 | 0.5573 | 0.72 | 0.0851 | 0.4556 | 0.0986 | 0.3034 | 0.0345 | 0.3 | 0.2958 | 0.4366 |
| 1.5736 | 22.0 | 2222 | 1.3208 | 0.2174 | 0.4119 | 0.1985 | 0.0864 | 0.2348 | 0.2689 | 0.2659 | 0.4506 | 0.4605 | 0.2751 | 0.4101 | 0.5576 | 0.5717 | 0.7447 | 0.0784 | 0.4593 | 0.108 | 0.3293 | 0.0223 | 0.3218 | 0.3066 | 0.4477 |
| 1.5736 | 23.0 | 2323 | 1.3249 | 0.216 | 0.417 | 0.195 | 0.0897 | 0.2359 | 0.2655 | 0.2734 | 0.4431 | 0.4569 | 0.2478 | 0.4077 | 0.5547 | 0.5606 | 0.744 | 0.085 | 0.4648 | 0.1042 | 0.3293 | 0.0297 | 0.3109 | 0.3006 | 0.4355 |
| 1.5736 | 24.0 | 2424 | 1.3029 | 0.2179 | 0.4165 | 0.1978 | 0.0847 | 0.2401 | 0.2718 | 0.2732 | 0.4512 | 0.4602 | 0.2515 | 0.4124 | 0.5595 | 0.5791 | 0.748 | 0.0956 | 0.4889 | 0.106 | 0.3391 | 0.028 | 0.3 | 0.2808 | 0.425 |
| 1.475 | 25.0 | 2525 | 1.3052 | 0.221 | 0.4208 | 0.2005 | 0.0787 | 0.2486 | 0.2767 | 0.2755 | 0.4533 | 0.4668 | 0.2224 | 0.4193 | 0.5809 | 0.5811 | 0.7473 | 0.0925 | 0.4796 | 0.1031 | 0.3339 | 0.0286 | 0.3291 | 0.2998 | 0.4442 |
| 1.475 | 26.0 | 2626 | 1.2998 | 0.2212 | 0.4156 | 0.2065 | 0.0826 | 0.2454 | 0.2761 | 0.2715 | 0.4538 | 0.4688 | 0.2426 | 0.4206 | 0.5781 | 0.5802 | 0.7513 | 0.0918 | 0.4981 | 0.1098 | 0.3431 | 0.0245 | 0.3109 | 0.2996 | 0.4407 |
| 1.475 | 27.0 | 2727 | 1.2836 | 0.2217 | 0.4217 | 0.202 | 0.0805 | 0.2452 | 0.2793 | 0.2791 | 0.4579 | 0.47 | 0.2482 | 0.4226 | 0.5736 | 0.581 | 0.7473 | 0.0916 | 0.4944 | 0.1094 | 0.3448 | 0.0261 | 0.3182 | 0.3003 | 0.4453 |
| 1.475 | 28.0 | 2828 | 1.2790 | 0.2238 | 0.4264 | 0.2033 | 0.0864 | 0.2524 | 0.2806 | 0.278 | 0.4589 | 0.4701 | 0.2425 | 0.4246 | 0.5751 | 0.5848 | 0.7467 | 0.098 | 0.4926 | 0.1107 | 0.3489 | 0.026 | 0.3182 | 0.2994 | 0.4442 |
| 1.475 | 29.0 | 2929 | 1.2804 | 0.2234 | 0.4256 | 0.2059 | 0.0865 | 0.2507 | 0.2808 | 0.2802 | 0.4603 | 0.4703 | 0.2614 | 0.4216 | 0.5738 | 0.5875 | 0.7507 | 0.0977 | 0.5019 | 0.1087 | 0.3431 | 0.025 | 0.3127 | 0.298 | 0.443 |
| 1.4089 | 30.0 | 3030 | 1.2803 | 0.2236 | 0.4243 | 0.206 | 0.087 | 0.2507 | 0.2808 | 0.28 | 0.4603 | 0.4703 | 0.2619 | 0.4212 | 0.5738 | 0.5876 | 0.7507 | 0.0978 | 0.5019 | 0.1088 | 0.3443 | 0.0251 | 0.3109 | 0.2988 | 0.4436 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1
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