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---
license: apache-2.0
base_model: facebook/detr-resnet-50
tags:
- generated_from_trainer
model-index:
- name: facebook_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. -->
# facebook_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: 1.5232
- Map: 0.2143
- Map 50: 0.4481
- Map 75: 0.1932
- Map Small: 0.0595
- Map Medium: 0.1238
- Map Large: 0.3317
- Mar 1: 0.2418
- Mar 10: 0.4177
- Mar 100: 0.4387
- Mar Small: 0.1234
- Mar Medium: 0.3182
- Mar Large: 0.5933
- Map Coverall: 0.4858
- Mar 100 Coverall: 0.6766
- Map Face Shield: 0.1639
- Mar 100 Face Shield: 0.4278
- Map Gloves: 0.1388
- Mar 100 Gloves: 0.3763
- Map Goggles: 0.0716
- Mar 100 Goggles: 0.3538
- Map Mask: 0.2112
- Mar 100 Mask: 0.3587
## 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 | 107 | 2.6056 | 0.02 | 0.0483 | 0.0156 | 0.0017 | 0.0019 | 0.0219 | 0.0344 | 0.1171 | 0.1547 | 0.0387 | 0.0674 | 0.2003 | 0.092 | 0.4671 | 0.0 | 0.0 | 0.0046 | 0.1647 | 0.0 | 0.0 | 0.0034 | 0.1418 |
| No log | 2.0 | 214 | 2.3184 | 0.036 | 0.0808 | 0.0265 | 0.0098 | 0.0135 | 0.0403 | 0.0512 | 0.1513 | 0.1976 | 0.1004 | 0.1414 | 0.2133 | 0.1389 | 0.518 | 0.0 | 0.0 | 0.0319 | 0.2384 | 0.0 | 0.0 | 0.0091 | 0.2316 |
| No log | 3.0 | 321 | 2.2718 | 0.0351 | 0.0849 | 0.0248 | 0.0082 | 0.0168 | 0.0345 | 0.0589 | 0.1499 | 0.1965 | 0.0592 | 0.112 | 0.2353 | 0.1366 | 0.5689 | 0.0 | 0.0 | 0.0195 | 0.2018 | 0.0 | 0.0 | 0.0193 | 0.2116 |
| No log | 4.0 | 428 | 2.2070 | 0.0665 | 0.1472 | 0.053 | 0.0093 | 0.0147 | 0.0715 | 0.0796 | 0.1709 | 0.199 | 0.077 | 0.1116 | 0.2313 | 0.2774 | 0.541 | 0.0 | 0.0 | 0.0167 | 0.2232 | 0.0 | 0.0 | 0.0384 | 0.2307 |
| 2.2509 | 5.0 | 535 | 2.0817 | 0.0753 | 0.1631 | 0.0643 | 0.0205 | 0.0263 | 0.0774 | 0.0833 | 0.184 | 0.2081 | 0.0762 | 0.1151 | 0.2439 | 0.3053 | 0.5653 | 0.0007 | 0.0152 | 0.0296 | 0.2576 | 0.0 | 0.0 | 0.0407 | 0.2022 |
| 2.2509 | 6.0 | 642 | 2.1124 | 0.0897 | 0.1778 | 0.0786 | 0.0128 | 0.0293 | 0.0976 | 0.0862 | 0.1932 | 0.2194 | 0.0752 | 0.1139 | 0.2658 | 0.3802 | 0.6324 | 0.007 | 0.0215 | 0.028 | 0.2277 | 0.0 | 0.0 | 0.0331 | 0.2156 |
| 2.2509 | 7.0 | 749 | 1.9497 | 0.1018 | 0.2201 | 0.0729 | 0.0331 | 0.0416 | 0.1097 | 0.1105 | 0.2187 | 0.2405 | 0.076 | 0.1336 | 0.2967 | 0.3631 | 0.627 | 0.0265 | 0.0873 | 0.0394 | 0.2518 | 0.0 | 0.0 | 0.0801 | 0.2364 |
| 2.2509 | 8.0 | 856 | 2.0218 | 0.1065 | 0.2185 | 0.0902 | 0.02 | 0.0531 | 0.1221 | 0.1329 | 0.244 | 0.2662 | 0.0686 | 0.1606 | 0.3382 | 0.3752 | 0.6221 | 0.0345 | 0.1658 | 0.0367 | 0.2442 | 0.0129 | 0.02 | 0.0734 | 0.2791 |
| 2.2509 | 9.0 | 963 | 1.9220 | 0.1125 | 0.2452 | 0.0979 | 0.0353 | 0.057 | 0.1411 | 0.132 | 0.2557 | 0.2703 | 0.078 | 0.1537 | 0.3563 | 0.3765 | 0.5878 | 0.0368 | 0.2063 | 0.0474 | 0.2487 | 0.0018 | 0.02 | 0.0997 | 0.2884 |
| 1.734 | 10.0 | 1070 | 1.8888 | 0.1342 | 0.284 | 0.1133 | 0.0278 | 0.0755 | 0.1591 | 0.1551 | 0.2793 | 0.2984 | 0.0525 | 0.1895 | 0.3834 | 0.447 | 0.6649 | 0.0624 | 0.2241 | 0.0505 | 0.2629 | 0.0101 | 0.0723 | 0.1011 | 0.268 |
| 1.734 | 11.0 | 1177 | 1.8868 | 0.1016 | 0.2399 | 0.0731 | 0.0231 | 0.0587 | 0.1282 | 0.1332 | 0.2687 | 0.2891 | 0.0759 | 0.2153 | 0.3802 | 0.3322 | 0.5811 | 0.0331 | 0.2405 | 0.047 | 0.2518 | 0.0102 | 0.1292 | 0.0856 | 0.2427 |
| 1.734 | 12.0 | 1284 | 1.7685 | 0.1412 | 0.3049 | 0.1177 | 0.0469 | 0.0695 | 0.183 | 0.1704 | 0.3233 | 0.3389 | 0.0818 | 0.2284 | 0.4528 | 0.4338 | 0.6293 | 0.0626 | 0.3051 | 0.0604 | 0.2839 | 0.0246 | 0.18 | 0.1244 | 0.2964 |
| 1.734 | 13.0 | 1391 | 1.7098 | 0.1508 | 0.3145 | 0.1249 | 0.039 | 0.0923 | 0.2026 | 0.1742 | 0.3351 | 0.3524 | 0.0892 | 0.2417 | 0.4757 | 0.4381 | 0.6559 | 0.0799 | 0.3076 | 0.083 | 0.3085 | 0.0079 | 0.1738 | 0.1452 | 0.3164 |
| 1.734 | 14.0 | 1498 | 1.6927 | 0.1617 | 0.3458 | 0.1351 | 0.0405 | 0.0958 | 0.2241 | 0.1852 | 0.3496 | 0.366 | 0.1014 | 0.2475 | 0.4904 | 0.4484 | 0.6581 | 0.1058 | 0.3329 | 0.0674 | 0.2906 | 0.0361 | 0.2323 | 0.1507 | 0.316 |
| 1.5105 | 15.0 | 1605 | 1.6452 | 0.1748 | 0.3717 | 0.145 | 0.0578 | 0.11 | 0.2376 | 0.2036 | 0.3582 | 0.376 | 0.1233 | 0.2797 | 0.4991 | 0.4443 | 0.6432 | 0.1282 | 0.3241 | 0.0984 | 0.3259 | 0.0301 | 0.26 | 0.1727 | 0.3267 |
| 1.5105 | 16.0 | 1712 | 1.6752 | 0.1706 | 0.3672 | 0.1338 | 0.0475 | 0.1048 | 0.2499 | 0.1987 | 0.3623 | 0.3886 | 0.1158 | 0.2733 | 0.5125 | 0.4261 | 0.6392 | 0.1294 | 0.3367 | 0.0981 | 0.3562 | 0.0378 | 0.2708 | 0.1616 | 0.34 |
| 1.5105 | 17.0 | 1819 | 1.6004 | 0.1867 | 0.3897 | 0.1547 | 0.045 | 0.1158 | 0.2696 | 0.2178 | 0.38 | 0.4003 | 0.1071 | 0.2849 | 0.5289 | 0.4534 | 0.6586 | 0.125 | 0.3557 | 0.1058 | 0.3598 | 0.0683 | 0.2892 | 0.1812 | 0.3382 |
| 1.5105 | 18.0 | 1926 | 1.5693 | 0.1823 | 0.3801 | 0.1584 | 0.0578 | 0.1034 | 0.2637 | 0.2152 | 0.3791 | 0.4006 | 0.1198 | 0.2829 | 0.5342 | 0.4645 | 0.6676 | 0.1157 | 0.3557 | 0.1143 | 0.3683 | 0.0421 | 0.2754 | 0.1748 | 0.336 |
| 1.3533 | 19.0 | 2033 | 1.5891 | 0.1895 | 0.4061 | 0.1638 | 0.0519 | 0.1144 | 0.2796 | 0.2145 | 0.3878 | 0.406 | 0.1355 | 0.2999 | 0.5346 | 0.4632 | 0.655 | 0.1435 | 0.357 | 0.1196 | 0.3647 | 0.0407 | 0.32 | 0.1808 | 0.3333 |
| 1.3533 | 20.0 | 2140 | 1.5850 | 0.1969 | 0.3947 | 0.1688 | 0.0549 | 0.1237 | 0.2798 | 0.2333 | 0.3976 | 0.4146 | 0.1077 | 0.3041 | 0.544 | 0.4706 | 0.6486 | 0.1459 | 0.3987 | 0.1287 | 0.3496 | 0.0448 | 0.3323 | 0.1945 | 0.344 |
| 1.3533 | 21.0 | 2247 | 1.5667 | 0.1971 | 0.3975 | 0.1752 | 0.0607 | 0.1162 | 0.2984 | 0.23 | 0.3969 | 0.4131 | 0.1131 | 0.3001 | 0.5511 | 0.4826 | 0.6626 | 0.1445 | 0.3937 | 0.1247 | 0.3536 | 0.0408 | 0.3123 | 0.1927 | 0.3436 |
| 1.3533 | 22.0 | 2354 | 1.5281 | 0.2048 | 0.4147 | 0.1843 | 0.0513 | 0.1217 | 0.3206 | 0.2292 | 0.3961 | 0.4149 | 0.1068 | 0.314 | 0.5566 | 0.4892 | 0.6698 | 0.1538 | 0.3772 | 0.1308 | 0.367 | 0.0526 | 0.3169 | 0.1977 | 0.3436 |
| 1.3533 | 23.0 | 2461 | 1.5632 | 0.206 | 0.423 | 0.1755 | 0.0558 | 0.1123 | 0.3259 | 0.2358 | 0.3957 | 0.4222 | 0.1182 | 0.3006 | 0.5721 | 0.4882 | 0.6739 | 0.1507 | 0.3937 | 0.1371 | 0.3688 | 0.055 | 0.3308 | 0.1992 | 0.344 |
| 1.2451 | 24.0 | 2568 | 1.5177 | 0.2083 | 0.4356 | 0.1778 | 0.0506 | 0.1205 | 0.3281 | 0.2387 | 0.4117 | 0.4344 | 0.1286 | 0.3056 | 0.5865 | 0.4806 | 0.6802 | 0.1463 | 0.4139 | 0.1384 | 0.3768 | 0.0577 | 0.34 | 0.2183 | 0.3613 |
| 1.2451 | 25.0 | 2675 | 1.5367 | 0.2092 | 0.427 | 0.1808 | 0.0553 | 0.1202 | 0.3256 | 0.2386 | 0.4115 | 0.4347 | 0.1224 | 0.3102 | 0.5915 | 0.4732 | 0.6748 | 0.1508 | 0.4203 | 0.1399 | 0.3795 | 0.0613 | 0.3354 | 0.2208 | 0.3636 |
| 1.2451 | 26.0 | 2782 | 1.5130 | 0.2093 | 0.4378 | 0.1884 | 0.0558 | 0.1225 | 0.3295 | 0.2394 | 0.4179 | 0.439 | 0.1442 | 0.3167 | 0.5958 | 0.4743 | 0.6761 | 0.1552 | 0.4228 | 0.1382 | 0.3759 | 0.0656 | 0.3615 | 0.2131 | 0.3587 |
| 1.2451 | 27.0 | 2889 | 1.5194 | 0.2122 | 0.4448 | 0.1893 | 0.0592 | 0.1231 | 0.3307 | 0.2405 | 0.4172 | 0.4352 | 0.1247 | 0.3171 | 0.5864 | 0.4826 | 0.6739 | 0.1597 | 0.4203 | 0.1384 | 0.3696 | 0.0692 | 0.3585 | 0.2108 | 0.3538 |
| 1.2451 | 28.0 | 2996 | 1.5213 | 0.2123 | 0.4451 | 0.1918 | 0.059 | 0.1221 | 0.3282 | 0.2426 | 0.4157 | 0.4347 | 0.1234 | 0.3165 | 0.5867 | 0.4856 | 0.677 | 0.1588 | 0.4177 | 0.1397 | 0.3754 | 0.0692 | 0.3508 | 0.208 | 0.3524 |
| 1.18 | 29.0 | 3103 | 1.5214 | 0.2135 | 0.4461 | 0.1923 | 0.0595 | 0.1228 | 0.3305 | 0.2414 | 0.4191 | 0.4392 | 0.1234 | 0.3189 | 0.5921 | 0.4857 | 0.6775 | 0.1626 | 0.4304 | 0.1393 | 0.3759 | 0.07 | 0.3569 | 0.2098 | 0.3551 |
| 1.18 | 30.0 | 3210 | 1.5232 | 0.2143 | 0.4481 | 0.1932 | 0.0595 | 0.1238 | 0.3317 | 0.2418 | 0.4177 | 0.4387 | 0.1234 | 0.3182 | 0.5933 | 0.4858 | 0.6766 | 0.1639 | 0.4278 | 0.1388 | 0.3763 | 0.0716 | 0.3538 | 0.2112 | 0.3587 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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