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---
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: 1.2111
- Map: 0.321
- Map 50: 0.5918
- Map 75: 0.3184
- Map Small: 0.0907
- Map Medium: 0.2843
- Map Large: 0.5134
- Mar 1: 0.3198
- Mar 10: 0.4825
- Mar 100: 0.5039
- Mar Small: 0.2107
- Mar Medium: 0.4607
- Mar Large: 0.7011
- Map Coverall: 0.6194
- Mar 100 Coverall: 0.7227
- Map Face Shield: 0.3136
- Mar 100 Face Shield: 0.5069
- Map Gloves: 0.2044
- Mar 100 Gloves: 0.3771
- Map Goggles: 0.1251
- Mar 100 Goggles: 0.4545
- Map Mask: 0.3424
- Mar 100 Mask: 0.4585
## 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 | 2.3407 | 0.0426 | 0.0978 | 0.0326 | 0.0074 | 0.0354 | 0.0395 | 0.0973 | 0.2336 | 0.2754 | 0.0681 | 0.227 | 0.2954 | 0.1332 | 0.4977 | 0.0115 | 0.2514 | 0.0099 | 0.2297 | 0.0067 | 0.0523 | 0.0518 | 0.3462 |
| No log | 2.0 | 214 | 2.0573 | 0.0833 | 0.1634 | 0.0709 | 0.0181 | 0.0454 | 0.0882 | 0.1315 | 0.268 | 0.3119 | 0.1127 | 0.2675 | 0.3681 | 0.3125 | 0.639 | 0.0058 | 0.1472 | 0.0167 | 0.2656 | 0.0176 | 0.15 | 0.0637 | 0.3579 |
| No log | 3.0 | 321 | 1.8604 | 0.1146 | 0.2275 | 0.0986 | 0.0195 | 0.0708 | 0.1337 | 0.1584 | 0.3363 | 0.3769 | 0.1369 | 0.2901 | 0.4995 | 0.3902 | 0.6802 | 0.0154 | 0.2514 | 0.0284 | 0.2891 | 0.0073 | 0.2545 | 0.1319 | 0.4092 |
| No log | 4.0 | 428 | 1.7289 | 0.1378 | 0.2881 | 0.1121 | 0.0253 | 0.0842 | 0.1814 | 0.1651 | 0.3436 | 0.3859 | 0.1215 | 0.3017 | 0.5579 | 0.4459 | 0.6605 | 0.0237 | 0.3333 | 0.0459 | 0.2958 | 0.0152 | 0.2545 | 0.1581 | 0.3851 |
| 3.3191 | 5.0 | 535 | 1.6097 | 0.1723 | 0.3541 | 0.1494 | 0.0463 | 0.1274 | 0.2006 | 0.1869 | 0.3909 | 0.4249 | 0.1537 | 0.37 | 0.5833 | 0.5099 | 0.7023 | 0.0445 | 0.3319 | 0.064 | 0.3187 | 0.053 | 0.325 | 0.19 | 0.4467 |
| 3.3191 | 6.0 | 642 | 1.6111 | 0.1731 | 0.3782 | 0.1364 | 0.048 | 0.1325 | 0.2384 | 0.209 | 0.3909 | 0.4184 | 0.1485 | 0.3428 | 0.6139 | 0.4833 | 0.6465 | 0.0555 | 0.375 | 0.0952 | 0.3359 | 0.0366 | 0.2977 | 0.1948 | 0.4369 |
| 3.3191 | 7.0 | 749 | 1.4938 | 0.2079 | 0.4225 | 0.1832 | 0.0505 | 0.1639 | 0.2836 | 0.2305 | 0.4168 | 0.4429 | 0.1665 | 0.3838 | 0.6407 | 0.5325 | 0.711 | 0.0848 | 0.4 | 0.1284 | 0.3443 | 0.0486 | 0.3045 | 0.2453 | 0.4549 |
| 3.3191 | 8.0 | 856 | 1.4541 | 0.2245 | 0.4604 | 0.1805 | 0.06 | 0.1831 | 0.3044 | 0.2417 | 0.4187 | 0.438 | 0.1518 | 0.3741 | 0.6534 | 0.5497 | 0.711 | 0.0936 | 0.3889 | 0.1453 | 0.349 | 0.0642 | 0.3068 | 0.2697 | 0.4344 |
| 3.3191 | 9.0 | 963 | 1.4065 | 0.2315 | 0.4382 | 0.2109 | 0.0486 | 0.2036 | 0.3422 | 0.2501 | 0.435 | 0.4574 | 0.1815 | 0.4242 | 0.6164 | 0.5825 | 0.7163 | 0.1096 | 0.3889 | 0.1283 | 0.3562 | 0.0722 | 0.3795 | 0.2648 | 0.4462 |
| 1.4973 | 10.0 | 1070 | 1.3990 | 0.2593 | 0.5115 | 0.2569 | 0.0656 | 0.2132 | 0.3844 | 0.2975 | 0.4597 | 0.486 | 0.1816 | 0.4145 | 0.7054 | 0.5545 | 0.6971 | 0.1929 | 0.4514 | 0.1595 | 0.3797 | 0.0941 | 0.4364 | 0.2955 | 0.4656 |
| 1.4973 | 11.0 | 1177 | 1.3687 | 0.2472 | 0.4996 | 0.2141 | 0.0636 | 0.2021 | 0.395 | 0.2777 | 0.4438 | 0.4769 | 0.1755 | 0.4489 | 0.6849 | 0.5717 | 0.718 | 0.1489 | 0.4458 | 0.1599 | 0.3698 | 0.0891 | 0.4159 | 0.2662 | 0.4349 |
| 1.4973 | 12.0 | 1284 | 1.3334 | 0.2544 | 0.5158 | 0.2178 | 0.0721 | 0.212 | 0.4027 | 0.2841 | 0.4611 | 0.48 | 0.1934 | 0.4503 | 0.6624 | 0.5714 | 0.6977 | 0.1812 | 0.4556 | 0.1648 | 0.3745 | 0.0668 | 0.4227 | 0.2879 | 0.4497 |
| 1.4973 | 13.0 | 1391 | 1.3249 | 0.2501 | 0.4985 | 0.2084 | 0.0496 | 0.2238 | 0.4004 | 0.2832 | 0.4529 | 0.485 | 0.1911 | 0.4504 | 0.6732 | 0.5983 | 0.7203 | 0.1515 | 0.4667 | 0.156 | 0.3651 | 0.0548 | 0.4114 | 0.2899 | 0.4615 |
| 1.4973 | 14.0 | 1498 | 1.2735 | 0.2822 | 0.5366 | 0.2586 | 0.0787 | 0.2395 | 0.4652 | 0.313 | 0.4716 | 0.4955 | 0.1955 | 0.4434 | 0.7144 | 0.6008 | 0.7076 | 0.2116 | 0.4708 | 0.1843 | 0.3745 | 0.09 | 0.4614 | 0.3242 | 0.4631 |
| 1.2609 | 15.0 | 1605 | 1.2748 | 0.286 | 0.5519 | 0.2749 | 0.0813 | 0.2349 | 0.469 | 0.3004 | 0.4682 | 0.4893 | 0.181 | 0.4281 | 0.7042 | 0.5954 | 0.707 | 0.1981 | 0.5167 | 0.1918 | 0.374 | 0.1184 | 0.4159 | 0.3265 | 0.4328 |
| 1.2609 | 16.0 | 1712 | 1.2785 | 0.2918 | 0.565 | 0.2654 | 0.0996 | 0.2501 | 0.453 | 0.3002 | 0.4744 | 0.4916 | 0.2085 | 0.4362 | 0.6911 | 0.5878 | 0.6948 | 0.2662 | 0.5097 | 0.1865 | 0.3583 | 0.1005 | 0.4477 | 0.3181 | 0.4477 |
| 1.2609 | 17.0 | 1819 | 1.2680 | 0.2985 | 0.5593 | 0.2776 | 0.0911 | 0.2461 | 0.4957 | 0.31 | 0.4819 | 0.5055 | 0.2127 | 0.4349 | 0.7159 | 0.5999 | 0.7081 | 0.2304 | 0.4917 | 0.1759 | 0.3677 | 0.1424 | 0.4864 | 0.3437 | 0.4738 |
| 1.2609 | 18.0 | 1926 | 1.2360 | 0.3045 | 0.5657 | 0.2744 | 0.0839 | 0.2549 | 0.5003 | 0.3054 | 0.4863 | 0.5062 | 0.2052 | 0.454 | 0.7213 | 0.6091 | 0.7209 | 0.2405 | 0.5111 | 0.1883 | 0.3693 | 0.1392 | 0.475 | 0.3452 | 0.4549 |
| 1.1171 | 19.0 | 2033 | 1.2404 | 0.3022 | 0.5737 | 0.2743 | 0.0765 | 0.259 | 0.4799 | 0.3044 | 0.4796 | 0.5043 | 0.209 | 0.4614 | 0.6987 | 0.603 | 0.714 | 0.2509 | 0.4986 | 0.1882 | 0.3729 | 0.1231 | 0.4636 | 0.3459 | 0.4723 |
| 1.1171 | 20.0 | 2140 | 1.2419 | 0.2969 | 0.5527 | 0.2677 | 0.081 | 0.256 | 0.4772 | 0.3108 | 0.4842 | 0.5123 | 0.2301 | 0.459 | 0.7114 | 0.6033 | 0.7262 | 0.2605 | 0.4861 | 0.176 | 0.3797 | 0.1112 | 0.5159 | 0.3336 | 0.4538 |
| 1.1171 | 21.0 | 2247 | 1.2257 | 0.3178 | 0.5774 | 0.3081 | 0.0885 | 0.2836 | 0.4843 | 0.3157 | 0.4932 | 0.5152 | 0.2269 | 0.4768 | 0.7 | 0.6221 | 0.7326 | 0.3063 | 0.5125 | 0.1964 | 0.3849 | 0.1316 | 0.4909 | 0.3329 | 0.4554 |
| 1.1171 | 22.0 | 2354 | 1.2236 | 0.3217 | 0.588 | 0.3084 | 0.0973 | 0.2854 | 0.4703 | 0.3136 | 0.4828 | 0.5101 | 0.2142 | 0.4775 | 0.7127 | 0.6213 | 0.7285 | 0.3186 | 0.5319 | 0.2022 | 0.3854 | 0.1269 | 0.45 | 0.3396 | 0.4549 |
| 1.1171 | 23.0 | 2461 | 1.2148 | 0.3234 | 0.587 | 0.3118 | 0.0949 | 0.2848 | 0.5036 | 0.3235 | 0.4904 | 0.5139 | 0.2189 | 0.4787 | 0.7177 | 0.6277 | 0.7279 | 0.3078 | 0.5208 | 0.2024 | 0.3865 | 0.14 | 0.4795 | 0.3392 | 0.4549 |
| 1.0261 | 24.0 | 2568 | 1.2210 | 0.3128 | 0.5754 | 0.2984 | 0.0833 | 0.2851 | 0.4986 | 0.3248 | 0.484 | 0.5096 | 0.2128 | 0.4715 | 0.7037 | 0.6269 | 0.7297 | 0.2899 | 0.4986 | 0.1942 | 0.3807 | 0.1136 | 0.4818 | 0.3394 | 0.4574 |
| 1.0261 | 25.0 | 2675 | 1.2124 | 0.3237 | 0.5872 | 0.3141 | 0.0916 | 0.2888 | 0.5151 | 0.3203 | 0.4906 | 0.5153 | 0.2202 | 0.4732 | 0.7165 | 0.6276 | 0.7285 | 0.3158 | 0.5222 | 0.2006 | 0.3854 | 0.1314 | 0.4795 | 0.3431 | 0.461 |
| 1.0261 | 26.0 | 2782 | 1.2167 | 0.3207 | 0.5852 | 0.313 | 0.0903 | 0.2815 | 0.5109 | 0.3216 | 0.4863 | 0.5081 | 0.213 | 0.4583 | 0.7085 | 0.6185 | 0.7221 | 0.3061 | 0.5 | 0.2048 | 0.3828 | 0.1317 | 0.4773 | 0.3423 | 0.4585 |
| 1.0261 | 27.0 | 2889 | 1.2110 | 0.3192 | 0.5864 | 0.3102 | 0.0881 | 0.2833 | 0.5117 | 0.3208 | 0.485 | 0.5074 | 0.2112 | 0.464 | 0.7048 | 0.62 | 0.7215 | 0.3094 | 0.5028 | 0.2006 | 0.3807 | 0.1225 | 0.4705 | 0.3437 | 0.4615 |
| 1.0261 | 28.0 | 2996 | 1.2109 | 0.3207 | 0.5939 | 0.3087 | 0.089 | 0.2832 | 0.5126 | 0.3202 | 0.4819 | 0.5033 | 0.2093 | 0.4588 | 0.6984 | 0.6203 | 0.7233 | 0.3128 | 0.5042 | 0.2048 | 0.376 | 0.1256 | 0.4568 | 0.34 | 0.4564 |
| 0.97 | 29.0 | 3103 | 1.2112 | 0.321 | 0.5919 | 0.3185 | 0.0909 | 0.2843 | 0.5132 | 0.3205 | 0.4825 | 0.5039 | 0.211 | 0.4603 | 0.701 | 0.6191 | 0.7221 | 0.3136 | 0.5069 | 0.2034 | 0.3755 | 0.1267 | 0.4568 | 0.342 | 0.4579 |
| 0.97 | 30.0 | 3210 | 1.2111 | 0.321 | 0.5918 | 0.3184 | 0.0907 | 0.2843 | 0.5134 | 0.3198 | 0.4825 | 0.5039 | 0.2107 | 0.4607 | 0.7011 | 0.6194 | 0.7227 | 0.3136 | 0.5069 | 0.2044 | 0.3771 | 0.1251 | 0.4545 | 0.3424 | 0.4585 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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