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---
library_name: transformers
license: apache-2.0
base_model: facebook/detr-resnet-101
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-101](https://huggingface.co/facebook/detr-resnet-101) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3826
- Map: 0.2211
- Map 50: 0.4433
- Map 75: 0.1865
- Map Small: 0.085
- Map Medium: 0.1852
- Map Large: 0.3102
- Mar 1: 0.2358
- Mar 10: 0.4196
- Mar 100: 0.4395
- Mar Small: 0.1924
- Mar Medium: 0.3868
- Mar Large: 0.5751
- Map Coverall: 0.52
- Mar 100 Coverall: 0.677
- Map Face Shield: 0.1426
- Mar 100 Face Shield: 0.3924
- Map Gloves: 0.1344
- Mar 100 Gloves: 0.4192
- Map Goggles: 0.0746
- Mar 100 Goggles: 0.3277
- Map Mask: 0.2339
- Mar 100 Mask: 0.3813
## 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: 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 | 107 | 2.4478 | 0.0132 | 0.0346 | 0.0085 | 0.0053 | 0.0142 | 0.013 | 0.0439 | 0.1138 | 0.1523 | 0.0478 | 0.1121 | 0.1613 | 0.0558 | 0.486 | 0.0 | 0.0 | 0.0029 | 0.1638 | 0.0 | 0.0 | 0.0073 | 0.1116 |
| No log | 2.0 | 214 | 2.7727 | 0.009 | 0.028 | 0.0041 | 0.0058 | 0.0185 | 0.0072 | 0.0337 | 0.0875 | 0.1368 | 0.0323 | 0.1066 | 0.1435 | 0.0264 | 0.4171 | 0.0 | 0.0 | 0.0113 | 0.1304 | 0.0 | 0.0 | 0.0073 | 0.1364 |
| No log | 3.0 | 321 | 2.6495 | 0.0134 | 0.044 | 0.0056 | 0.0068 | 0.0143 | 0.0141 | 0.0294 | 0.1063 | 0.1269 | 0.0467 | 0.1156 | 0.1424 | 0.0355 | 0.3099 | 0.0 | 0.0 | 0.0126 | 0.1464 | 0.0 | 0.0 | 0.019 | 0.1782 |
| No log | 4.0 | 428 | 2.1866 | 0.0354 | 0.0933 | 0.0234 | 0.0103 | 0.0208 | 0.0367 | 0.0535 | 0.1521 | 0.1742 | 0.0574 | 0.1331 | 0.1925 | 0.1323 | 0.4878 | 0.0 | 0.0 | 0.015 | 0.1871 | 0.0 | 0.0 | 0.0296 | 0.196 |
| 2.1646 | 5.0 | 535 | 1.9950 | 0.0496 | 0.1249 | 0.0335 | 0.0092 | 0.0338 | 0.057 | 0.0665 | 0.1721 | 0.2044 | 0.0729 | 0.1567 | 0.2354 | 0.1684 | 0.5369 | 0.0025 | 0.0114 | 0.0244 | 0.2201 | 0.0 | 0.0 | 0.0527 | 0.2533 |
| 2.1646 | 6.0 | 642 | 2.0231 | 0.0467 | 0.1218 | 0.0301 | 0.0146 | 0.0459 | 0.0611 | 0.0725 | 0.1786 | 0.2064 | 0.078 | 0.1636 | 0.2389 | 0.1419 | 0.5495 | 0.0018 | 0.0342 | 0.0194 | 0.2076 | 0.0 | 0.0 | 0.0705 | 0.2404 |
| 2.1646 | 7.0 | 749 | 1.9400 | 0.0551 | 0.1336 | 0.04 | 0.022 | 0.0467 | 0.0727 | 0.0946 | 0.1933 | 0.2233 | 0.1013 | 0.1747 | 0.2636 | 0.1717 | 0.5207 | 0.0075 | 0.0823 | 0.0229 | 0.2455 | 0.0059 | 0.0046 | 0.0673 | 0.2636 |
| 2.1646 | 8.0 | 856 | 1.9149 | 0.07 | 0.1803 | 0.0523 | 0.037 | 0.0521 | 0.0903 | 0.0986 | 0.1937 | 0.223 | 0.0892 | 0.1663 | 0.2716 | 0.2104 | 0.5694 | 0.0096 | 0.062 | 0.03 | 0.229 | 0.0015 | 0.0077 | 0.0987 | 0.2467 |
| 2.1646 | 9.0 | 963 | 1.8614 | 0.0893 | 0.2058 | 0.0651 | 0.0248 | 0.0795 | 0.1176 | 0.1088 | 0.2341 | 0.2559 | 0.1075 | 0.2323 | 0.2872 | 0.259 | 0.5509 | 0.0201 | 0.1684 | 0.0383 | 0.2545 | 0.0006 | 0.0108 | 0.1285 | 0.2951 |
| 1.7395 | 10.0 | 1070 | 1.7835 | 0.1106 | 0.2638 | 0.0788 | 0.0315 | 0.1011 | 0.1466 | 0.1414 | 0.2696 | 0.297 | 0.1256 | 0.266 | 0.3475 | 0.2673 | 0.5446 | 0.0612 | 0.2494 | 0.0443 | 0.2728 | 0.015 | 0.0969 | 0.1653 | 0.3213 |
| 1.7395 | 11.0 | 1177 | 1.7088 | 0.1197 | 0.2811 | 0.0839 | 0.064 | 0.1103 | 0.1504 | 0.1524 | 0.2979 | 0.316 | 0.1231 | 0.2602 | 0.4093 | 0.314 | 0.605 | 0.0536 | 0.2557 | 0.0512 | 0.2719 | 0.0192 | 0.16 | 0.1608 | 0.2876 |
| 1.7395 | 12.0 | 1284 | 1.6845 | 0.1454 | 0.3145 | 0.1206 | 0.0385 | 0.1227 | 0.195 | 0.178 | 0.3173 | 0.3421 | 0.1181 | 0.294 | 0.443 | 0.3877 | 0.6401 | 0.0626 | 0.2772 | 0.0753 | 0.3272 | 0.0239 | 0.14 | 0.1772 | 0.3258 |
| 1.7395 | 13.0 | 1391 | 1.6600 | 0.1447 | 0.3095 | 0.1262 | 0.0529 | 0.1245 | 0.199 | 0.1701 | 0.3301 | 0.3528 | 0.11 | 0.3093 | 0.4715 | 0.4091 | 0.6437 | 0.0627 | 0.2949 | 0.0596 | 0.3259 | 0.0181 | 0.1815 | 0.1741 | 0.3178 |
| 1.7395 | 14.0 | 1498 | 1.5611 | 0.158 | 0.3529 | 0.1249 | 0.0614 | 0.1434 | 0.2098 | 0.1968 | 0.3545 | 0.3776 | 0.14 | 0.3364 | 0.4679 | 0.3879 | 0.6266 | 0.1051 | 0.3519 | 0.0666 | 0.346 | 0.039 | 0.2231 | 0.1915 | 0.3404 |
| 1.4537 | 15.0 | 1605 | 1.6226 | 0.1779 | 0.3643 | 0.1587 | 0.0609 | 0.1449 | 0.2662 | 0.2166 | 0.3661 | 0.3837 | 0.1291 | 0.3141 | 0.5235 | 0.4187 | 0.6302 | 0.0943 | 0.3519 | 0.0902 | 0.3384 | 0.0598 | 0.2385 | 0.2264 | 0.3596 |
| 1.4537 | 16.0 | 1712 | 1.5840 | 0.1641 | 0.3602 | 0.1287 | 0.0592 | 0.1294 | 0.2399 | 0.2036 | 0.3643 | 0.3828 | 0.1486 | 0.3242 | 0.4985 | 0.3993 | 0.6059 | 0.1291 | 0.3722 | 0.0768 | 0.35 | 0.0347 | 0.2631 | 0.1805 | 0.3227 |
| 1.4537 | 17.0 | 1819 | 1.4955 | 0.1812 | 0.3855 | 0.1458 | 0.0679 | 0.1367 | 0.27 | 0.2093 | 0.3732 | 0.3949 | 0.1526 | 0.3293 | 0.5173 | 0.4528 | 0.6568 | 0.1031 | 0.3468 | 0.0958 | 0.3754 | 0.051 | 0.2385 | 0.2033 | 0.3569 |
| 1.4537 | 18.0 | 1926 | 1.4729 | 0.1899 | 0.4035 | 0.1552 | 0.066 | 0.1613 | 0.2749 | 0.2106 | 0.3969 | 0.4252 | 0.1691 | 0.3685 | 0.557 | 0.4587 | 0.6775 | 0.1148 | 0.3911 | 0.1048 | 0.3982 | 0.0525 | 0.2938 | 0.2187 | 0.3653 |
| 1.2794 | 19.0 | 2033 | 1.4837 | 0.2061 | 0.423 | 0.1807 | 0.0724 | 0.1669 | 0.2828 | 0.226 | 0.4066 | 0.4308 | 0.1742 | 0.3779 | 0.5417 | 0.4828 | 0.6698 | 0.1354 | 0.3886 | 0.1249 | 0.3853 | 0.0581 | 0.3523 | 0.2291 | 0.3582 |
| 1.2794 | 20.0 | 2140 | 1.4320 | 0.2055 | 0.4205 | 0.1675 | 0.0796 | 0.1685 | 0.2868 | 0.225 | 0.4086 | 0.4311 | 0.1831 | 0.3727 | 0.5552 | 0.4733 | 0.6545 | 0.1472 | 0.4051 | 0.1114 | 0.3969 | 0.0687 | 0.3338 | 0.2268 | 0.3653 |
| 1.2794 | 21.0 | 2247 | 1.3978 | 0.2094 | 0.4321 | 0.1701 | 0.0773 | 0.1815 | 0.2968 | 0.2275 | 0.4136 | 0.436 | 0.2046 | 0.3843 | 0.5531 | 0.4764 | 0.6599 | 0.1377 | 0.3759 | 0.1259 | 0.4321 | 0.0765 | 0.3385 | 0.2307 | 0.3733 |
| 1.2794 | 22.0 | 2354 | 1.3970 | 0.2025 | 0.4224 | 0.1652 | 0.0741 | 0.1656 | 0.2877 | 0.2254 | 0.4152 | 0.4381 | 0.2127 | 0.3905 | 0.5433 | 0.4904 | 0.6608 | 0.1122 | 0.4051 | 0.1111 | 0.4107 | 0.06 | 0.3369 | 0.2389 | 0.3769 |
| 1.2794 | 23.0 | 2461 | 1.4207 | 0.2095 | 0.4378 | 0.1769 | 0.0663 | 0.1792 | 0.3028 | 0.233 | 0.4145 | 0.4326 | 0.1553 | 0.3903 | 0.5597 | 0.4918 | 0.6752 | 0.1181 | 0.3911 | 0.1302 | 0.4085 | 0.0771 | 0.3108 | 0.2304 | 0.3773 |
| 1.1354 | 24.0 | 2568 | 1.3942 | 0.214 | 0.4383 | 0.1754 | 0.0763 | 0.1737 | 0.3056 | 0.2244 | 0.4212 | 0.4427 | 0.1957 | 0.3859 | 0.5632 | 0.5148 | 0.6847 | 0.1354 | 0.4025 | 0.129 | 0.4192 | 0.0722 | 0.3323 | 0.2185 | 0.3747 |
| 1.1354 | 25.0 | 2675 | 1.3834 | 0.214 | 0.4377 | 0.1816 | 0.0783 | 0.182 | 0.3042 | 0.2307 | 0.4175 | 0.4352 | 0.1911 | 0.3845 | 0.5586 | 0.5116 | 0.6806 | 0.1269 | 0.3924 | 0.1278 | 0.4049 | 0.0702 | 0.3185 | 0.2336 | 0.3796 |
| 1.1354 | 26.0 | 2782 | 1.3870 | 0.2169 | 0.4399 | 0.1832 | 0.0788 | 0.1837 | 0.3056 | 0.2386 | 0.418 | 0.4372 | 0.1865 | 0.3921 | 0.5633 | 0.5093 | 0.6743 | 0.1476 | 0.3962 | 0.1273 | 0.4054 | 0.0698 | 0.3308 | 0.2303 | 0.3796 |
| 1.1354 | 27.0 | 2889 | 1.3859 | 0.219 | 0.4387 | 0.1816 | 0.0818 | 0.1826 | 0.3069 | 0.2352 | 0.4177 | 0.4376 | 0.1808 | 0.3857 | 0.5744 | 0.5118 | 0.6707 | 0.1416 | 0.3861 | 0.1355 | 0.4237 | 0.0727 | 0.3246 | 0.2336 | 0.3831 |
| 1.1354 | 28.0 | 2996 | 1.3814 | 0.2218 | 0.445 | 0.1878 | 0.0827 | 0.1873 | 0.311 | 0.2385 | 0.4208 | 0.44 | 0.1915 | 0.3871 | 0.5735 | 0.5222 | 0.677 | 0.1423 | 0.3962 | 0.1352 | 0.4174 | 0.0744 | 0.3262 | 0.2349 | 0.3831 |
| 1.0569 | 29.0 | 3103 | 1.3851 | 0.2213 | 0.4429 | 0.1867 | 0.0848 | 0.1858 | 0.3108 | 0.2356 | 0.4204 | 0.4396 | 0.1912 | 0.3876 | 0.5737 | 0.5193 | 0.6761 | 0.1433 | 0.3962 | 0.1343 | 0.4174 | 0.0744 | 0.3262 | 0.235 | 0.3822 |
| 1.0569 | 30.0 | 3210 | 1.3826 | 0.2211 | 0.4433 | 0.1865 | 0.085 | 0.1852 | 0.3102 | 0.2358 | 0.4196 | 0.4395 | 0.1924 | 0.3868 | 0.5751 | 0.52 | 0.677 | 0.1426 | 0.3924 | 0.1344 | 0.4192 | 0.0746 | 0.3277 | 0.2339 | 0.3813 |
### Framework versions
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.1
- Tokenizers 0.21.0
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