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library_name: transformers
license: apache-2.0
base_model: microsoft/conditional-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 [microsoft/conditional-detr-resnet-50](https://huggingface.co/microsoft/conditional-detr-resnet-50) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1482
- Map: 0.3013
- Map 50: 0.6037
- Map 75: 0.2625
- Map Small: 0.0935
- Map Medium: 0.2354
- Map Large: 0.4705
- Mar 1: 0.293
- Mar 10: 0.4358
- Mar 100: 0.4539
- Mar Small: 0.2086
- Mar Medium: 0.3954
- Mar Large: 0.6332
- Map Coverall: 0.5417
- Mar 100 Coverall: 0.6608
- Map Face Shield: 0.3015
- Mar 100 Face Shield: 0.4709
- Map Gloves: 0.1881
- Mar 100 Gloves: 0.3589
- Map Goggles: 0.1751
- Mar 100 Goggles: 0.3723
- Map Mask: 0.2998
- Mar 100 Mask: 0.4067
## 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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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 | 1.3103 | 0.2366 | 0.5251 | 0.1954 | 0.0483 | 0.1595 | 0.4051 | 0.2415 | 0.372 | 0.3916 | 0.0973 | 0.3279 | 0.5894 | 0.5019 | 0.6234 | 0.1952 | 0.3873 | 0.1421 | 0.3067 | 0.1166 | 0.3123 | 0.2272 | 0.328 |
| No log | 2.0 | 214 | 1.2553 | 0.2407 | 0.5311 | 0.1895 | 0.0818 | 0.1888 | 0.3807 | 0.2457 | 0.4052 | 0.4239 | 0.2015 | 0.3461 | 0.6037 | 0.4952 | 0.6351 | 0.2002 | 0.4405 | 0.1491 | 0.317 | 0.1145 | 0.3508 | 0.2445 | 0.376 |
| No log | 3.0 | 321 | 1.2643 | 0.2545 | 0.5418 | 0.2059 | 0.0836 | 0.1862 | 0.4223 | 0.2582 | 0.4086 | 0.4288 | 0.1915 | 0.354 | 0.6306 | 0.4996 | 0.6315 | 0.2537 | 0.4911 | 0.1503 | 0.3174 | 0.1181 | 0.34 | 0.2506 | 0.364 |
| No log | 4.0 | 428 | 1.2615 | 0.2529 | 0.5449 | 0.2072 | 0.0696 | 0.1878 | 0.4059 | 0.2609 | 0.3967 | 0.4207 | 0.1807 | 0.3445 | 0.6116 | 0.5063 | 0.6261 | 0.2257 | 0.438 | 0.1622 | 0.3304 | 0.1233 | 0.3385 | 0.247 | 0.3707 |
| 0.809 | 5.0 | 535 | 1.2607 | 0.2579 | 0.531 | 0.2227 | 0.073 | 0.2017 | 0.3961 | 0.2645 | 0.4083 | 0.4268 | 0.1903 | 0.372 | 0.5884 | 0.4998 | 0.6248 | 0.2598 | 0.4519 | 0.1353 | 0.304 | 0.1357 | 0.3677 | 0.2589 | 0.3858 |
| 0.809 | 6.0 | 642 | 1.2593 | 0.2519 | 0.5188 | 0.1991 | 0.0871 | 0.1865 | 0.3902 | 0.2603 | 0.3996 | 0.4208 | 0.2027 | 0.3592 | 0.5902 | 0.493 | 0.6302 | 0.2515 | 0.443 | 0.1459 | 0.3241 | 0.1331 | 0.3538 | 0.2359 | 0.3529 |
| 0.809 | 7.0 | 749 | 1.2608 | 0.2343 | 0.5174 | 0.1746 | 0.0704 | 0.1827 | 0.359 | 0.2465 | 0.3923 | 0.4159 | 0.1648 | 0.3577 | 0.5925 | 0.4923 | 0.6392 | 0.2226 | 0.419 | 0.143 | 0.3121 | 0.0839 | 0.3462 | 0.2296 | 0.3631 |
| 0.809 | 8.0 | 856 | 1.2420 | 0.2518 | 0.5359 | 0.2112 | 0.0678 | 0.1871 | 0.3933 | 0.2665 | 0.4027 | 0.4247 | 0.1816 | 0.3587 | 0.6093 | 0.5093 | 0.6333 | 0.2541 | 0.457 | 0.161 | 0.304 | 0.1149 | 0.3708 | 0.2194 | 0.3582 |
| 0.809 | 9.0 | 963 | 1.2877 | 0.2389 | 0.5124 | 0.1925 | 0.0765 | 0.1861 | 0.3552 | 0.2418 | 0.3911 | 0.4139 | 0.1845 | 0.3416 | 0.5759 | 0.4878 | 0.6405 | 0.2406 | 0.457 | 0.16 | 0.3219 | 0.0767 | 0.3154 | 0.2292 | 0.3347 |
| 0.8045 | 10.0 | 1070 | 1.2622 | 0.2465 | 0.5363 | 0.1849 | 0.0681 | 0.1901 | 0.3804 | 0.2551 | 0.3944 | 0.4152 | 0.1688 | 0.347 | 0.5884 | 0.4993 | 0.6248 | 0.235 | 0.419 | 0.1353 | 0.325 | 0.1121 | 0.3323 | 0.2506 | 0.3751 |
| 0.8045 | 11.0 | 1177 | 1.2450 | 0.2567 | 0.5325 | 0.212 | 0.0769 | 0.2089 | 0.3991 | 0.2561 | 0.4013 | 0.4236 | 0.1756 | 0.38 | 0.583 | 0.5152 | 0.6311 | 0.2205 | 0.4228 | 0.1471 | 0.3152 | 0.1476 | 0.3892 | 0.2528 | 0.3596 |
| 0.8045 | 12.0 | 1284 | 1.2581 | 0.2482 | 0.5347 | 0.1968 | 0.0744 | 0.1923 | 0.3948 | 0.2679 | 0.4031 | 0.4202 | 0.1677 | 0.365 | 0.5949 | 0.511 | 0.6423 | 0.2382 | 0.443 | 0.1513 | 0.3107 | 0.1024 | 0.3523 | 0.2383 | 0.3524 |
| 0.8045 | 13.0 | 1391 | 1.2723 | 0.2523 | 0.5343 | 0.1932 | 0.0752 | 0.1776 | 0.4016 | 0.2564 | 0.3901 | 0.413 | 0.1807 | 0.3553 | 0.5787 | 0.5103 | 0.6374 | 0.2291 | 0.4165 | 0.1744 | 0.3304 | 0.1068 | 0.3308 | 0.2407 | 0.3502 |
| 0.8045 | 14.0 | 1498 | 1.2605 | 0.2557 | 0.5429 | 0.2066 | 0.064 | 0.2004 | 0.4036 | 0.26 | 0.3913 | 0.4058 | 0.1734 | 0.349 | 0.5638 | 0.506 | 0.6284 | 0.2267 | 0.4101 | 0.1439 | 0.283 | 0.1458 | 0.3431 | 0.2562 | 0.3644 |
| 0.7483 | 15.0 | 1605 | 1.1914 | 0.2745 | 0.5581 | 0.2287 | 0.0771 | 0.2257 | 0.436 | 0.2752 | 0.418 | 0.4318 | 0.182 | 0.3714 | 0.5948 | 0.5256 | 0.6437 | 0.265 | 0.4506 | 0.1654 | 0.3304 | 0.1388 | 0.3508 | 0.2776 | 0.3836 |
| 0.7483 | 16.0 | 1712 | 1.2263 | 0.2707 | 0.5439 | 0.2323 | 0.0806 | 0.2134 | 0.4229 | 0.271 | 0.4093 | 0.4281 | 0.2211 | 0.353 | 0.5989 | 0.5228 | 0.6329 | 0.2682 | 0.438 | 0.1485 | 0.3138 | 0.1464 | 0.3769 | 0.2675 | 0.3787 |
| 0.7483 | 17.0 | 1819 | 1.1937 | 0.2768 | 0.5753 | 0.2219 | 0.0905 | 0.2061 | 0.4351 | 0.2744 | 0.4158 | 0.4374 | 0.1936 | 0.3639 | 0.6148 | 0.5191 | 0.6464 | 0.2555 | 0.4582 | 0.175 | 0.3348 | 0.1594 | 0.3646 | 0.2752 | 0.3831 |
| 0.7483 | 18.0 | 1926 | 1.1891 | 0.2819 | 0.5779 | 0.2195 | 0.0856 | 0.2146 | 0.4421 | 0.2804 | 0.4272 | 0.4425 | 0.1994 | 0.3761 | 0.6186 | 0.528 | 0.6491 | 0.2863 | 0.4797 | 0.1772 | 0.3366 | 0.1458 | 0.3646 | 0.2721 | 0.3822 |
| 0.6667 | 19.0 | 2033 | 1.1921 | 0.2873 | 0.5852 | 0.2319 | 0.0904 | 0.2222 | 0.4537 | 0.2785 | 0.4251 | 0.4483 | 0.1838 | 0.4064 | 0.6159 | 0.539 | 0.6568 | 0.2849 | 0.4747 | 0.1765 | 0.3411 | 0.1539 | 0.3754 | 0.2821 | 0.3938 |
| 0.6667 | 20.0 | 2140 | 1.1818 | 0.293 | 0.5831 | 0.2489 | 0.091 | 0.2229 | 0.4721 | 0.2877 | 0.4307 | 0.448 | 0.2008 | 0.3913 | 0.6292 | 0.5318 | 0.6536 | 0.3021 | 0.4886 | 0.1806 | 0.3496 | 0.1786 | 0.3662 | 0.2721 | 0.3822 |
| 0.6667 | 21.0 | 2247 | 1.1679 | 0.2914 | 0.5889 | 0.2375 | 0.0971 | 0.2219 | 0.4566 | 0.2834 | 0.4302 | 0.4503 | 0.1951 | 0.3953 | 0.6284 | 0.5388 | 0.6577 | 0.2947 | 0.4608 | 0.1848 | 0.3567 | 0.1545 | 0.3815 | 0.2844 | 0.3947 |
| 0.6667 | 22.0 | 2354 | 1.1684 | 0.2901 | 0.5869 | 0.2451 | 0.0909 | 0.2182 | 0.4556 | 0.284 | 0.4314 | 0.4457 | 0.2025 | 0.375 | 0.6275 | 0.5342 | 0.6568 | 0.2854 | 0.4608 | 0.1817 | 0.3473 | 0.1645 | 0.3677 | 0.2848 | 0.396 |
| 0.6667 | 23.0 | 2461 | 1.1606 | 0.2927 | 0.5861 | 0.2426 | 0.0869 | 0.2221 | 0.4582 | 0.2868 | 0.4278 | 0.4471 | 0.2063 | 0.3833 | 0.6147 | 0.546 | 0.6568 | 0.292 | 0.4709 | 0.1828 | 0.3522 | 0.1601 | 0.3646 | 0.2825 | 0.3911 |
| 0.5873 | 24.0 | 2568 | 1.1582 | 0.2924 | 0.5898 | 0.2543 | 0.0918 | 0.2298 | 0.4546 | 0.2898 | 0.4311 | 0.4497 | 0.2008 | 0.3965 | 0.6166 | 0.5473 | 0.6653 | 0.2906 | 0.4747 | 0.1811 | 0.346 | 0.149 | 0.3662 | 0.2939 | 0.3964 |
| 0.5873 | 25.0 | 2675 | 1.1534 | 0.2987 | 0.6015 | 0.2658 | 0.0897 | 0.2329 | 0.4705 | 0.2899 | 0.4312 | 0.4515 | 0.2032 | 0.3874 | 0.6358 | 0.5507 | 0.6653 | 0.2975 | 0.4797 | 0.186 | 0.3536 | 0.1632 | 0.3569 | 0.2963 | 0.4018 |
| 0.5873 | 26.0 | 2782 | 1.1536 | 0.2976 | 0.5984 | 0.2627 | 0.093 | 0.2331 | 0.4708 | 0.2882 | 0.4335 | 0.4536 | 0.2074 | 0.3973 | 0.6307 | 0.5414 | 0.6604 | 0.2947 | 0.4785 | 0.1831 | 0.3562 | 0.1733 | 0.3708 | 0.2955 | 0.4022 |
| 0.5873 | 27.0 | 2889 | 1.1492 | 0.2992 | 0.6031 | 0.2633 | 0.0931 | 0.2331 | 0.4692 | 0.2913 | 0.4358 | 0.4528 | 0.2119 | 0.3922 | 0.6313 | 0.5442 | 0.6617 | 0.2975 | 0.4785 | 0.185 | 0.3558 | 0.174 | 0.3662 | 0.2951 | 0.4018 |
| 0.5873 | 28.0 | 2996 | 1.1491 | 0.3007 | 0.6027 | 0.2606 | 0.0927 | 0.2337 | 0.4742 | 0.2928 | 0.4342 | 0.4528 | 0.2026 | 0.3965 | 0.6313 | 0.5406 | 0.6581 | 0.2982 | 0.4709 | 0.1881 | 0.358 | 0.1799 | 0.3738 | 0.2965 | 0.4031 |
| 0.5379 | 29.0 | 3103 | 1.1484 | 0.301 | 0.6039 | 0.2632 | 0.0932 | 0.2356 | 0.4706 | 0.2935 | 0.4356 | 0.4532 | 0.2035 | 0.395 | 0.6327 | 0.541 | 0.6599 | 0.3019 | 0.4696 | 0.1885 | 0.3589 | 0.1739 | 0.3723 | 0.2995 | 0.4053 |
| 0.5379 | 30.0 | 3210 | 1.1482 | 0.3013 | 0.6037 | 0.2625 | 0.0935 | 0.2354 | 0.4705 | 0.293 | 0.4358 | 0.4539 | 0.2086 | 0.3954 | 0.6332 | 0.5417 | 0.6608 | 0.3015 | 0.4709 | 0.1881 | 0.3589 | 0.1751 | 0.3723 | 0.2998 | 0.4067 |
### Framework versions
- Transformers 4.55.4
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.21.4
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