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library_name: transformers
license: apache-2.0
base_model: facebook/detr-resnet-50-dc5
tags:
- generated_from_trainer
model-index:
- name: DETR
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
This model is a fine-tuned version of [facebook/detr-resnet-50-dc5](https://huggingface.co/facebook/detr-resnet-50-dc5) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6175
- Map: 0.0235
- Map 50: 0.0454
- Map 75: 0.0236
- Map Small: 0.0
- Map Medium: 0.0065
- Map Large: 0.0651
- Mar 1: 0.0428
- Mar 10: 0.1393
- Mar 100: 0.3049
- Mar Small: 0.0
- Mar Medium: 0.2244
- Mar Large: 0.4274
- Map D10: 0.0131
- Mar 100 D10: 0.3508
- Map D20: 0.0574
- Mar 100 D20: 0.564
- Map D40: 0.0
- Mar 100 D40: 0.0
## 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: 1e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- training_steps: 10000
- mixed_precision_training: Native AMP
### 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 D0 | Mar 100 D0 | Map D10 | Mar 100 D10 | Map D20 | Mar 100 D20 | Map D40 | Mar 100 D40 |
|:-------------:|:------:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:----------:|:---------:|:------:|:------:|:-------:|:---------:|:----------:|:---------:|:------:|:----------:|:-------:|:-----------:|:-------:|:-----------:|:-------:|:-----------:|
| 5.176 | 0.1238 | 200 | 4.6596 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0003 | 0.0 | 0.0 | 0.0015 | -1.0 | -1.0 | 0.0 | 0.0008 | 0.0 | 0.0 | 0.0 | 0.0 |
| 3.0396 | 0.2475 | 400 | 3.5515 | 0.0 | 0.0001 | 0.0 | 0.0 | 0.0001 | 0.0001 | 0.0 | 0.0067 | 0.0307 | 0.0 | 0.0333 | 0.045 | -1.0 | -1.0 | 0.0 | 0.0 | 0.0001 | 0.092 | 0.0 | 0.0 |
| 2.95 | 0.3713 | 600 | 3.2961 | 0.0001 | 0.0003 | 0.0 | 0.0 | 0.0 | 0.0003 | 0.0 | 0.0027 | 0.0613 | 0.0 | 0.0 | 0.115 | 0.0 | 0.0 | 0.0002 | 0.184 | 0.0 | 0.0 |
| 2.6609 | 0.4950 | 800 | 3.3303 | 0.0001 | 0.0006 | 0.0 | 0.0 | 0.0001 | 0.0003 | 0.0 | 0.008 | 0.072 | 0.0 | 0.0467 | 0.1175 | 0.0 | 0.0 | 0.0004 | 0.216 | 0.0 | 0.0 |
| 3.2776 | 0.6188 | 1000 | 3.0383 | 0.0002 | 0.0007 | 0.0 | 0.0 | 0.0002 | 0.0003 | 0.0 | 0.008 | 0.0733 | 0.0 | 0.0467 | 0.12 | 0.0 | 0.0 | 0.0005 | 0.22 | 0.0 | 0.0 |
| 2.7712 | 0.7426 | 1200 | 2.9071 | 0.0004 | 0.0015 | 0.0 | 0.0 | 0.0022 | 0.0006 | 0.0 | 0.0253 | 0.0627 | 0.0 | 0.0333 | 0.105 | 0.0 | 0.0 | 0.0011 | 0.188 | 0.0 | 0.0 |
| 2.4005 | 0.8663 | 1400 | 2.7352 | 0.001 | 0.0069 | 0.0001 | 0.0 | 0.0023 | 0.0018 | 0.0013 | 0.0227 | 0.0907 | 0.0 | 0.06 | 0.1475 | 0.0 | 0.0 | 0.003 | 0.272 | 0.0 | 0.0 |
| 2.6812 | 0.9901 | 1600 | 2.5448 | 0.0009 | 0.0037 | 0.0001 | 0.0 | 0.0005 | 0.0016 | 0.004 | 0.0267 | 0.0987 | 0.0 | 0.06 | 0.1625 | 0.0 | 0.0 | 0.0026 | 0.296 | 0.0 | 0.0 |
| 1.8313 | 1.1139 | 1800 | 2.3839 | 0.0009 | 0.003 | 0.0 | 0.0 | 0.0002 | 0.0018 | 0.008 | 0.02 | 0.1173 | 0.0 | 0.1067 | 0.18 | 0.0 | 0.0 | 0.0028 | 0.352 | 0.0 | 0.0 |
| 2.6377 | 1.2376 | 2000 | 2.3837 | 0.0013 | 0.0033 | 0.0004 | 0.0 | 0.0001 | 0.0023 | 0.0 | 0.0347 | 0.1253 | 0.0 | 0.0667 | 0.21 | 0.0 | 0.0 | 0.0038 | 0.376 | 0.0 | 0.0 |
| 1.919 | 1.3614 | 2200 | 2.4226 | 0.0021 | 0.0078 | 0.0001 | 0.0 | 0.0001 | 0.0039 | 0.004 | 0.028 | 0.1227 | 0.0 | 0.0467 | 0.2125 | 0.0 | 0.0 | 0.0064 | 0.368 | 0.0 | 0.0 |
| 2.1093 | 1.4851 | 2400 | 2.3144 | 0.006 | 0.0232 | 0.0011 | 0.0 | 0.0 | 0.0109 | 0.0093 | 0.0307 | 0.12 | 0.0 | 0.0533 | 0.205 | 0.0 | 0.0 | 0.0179 | 0.36 | 0.0 | 0.0 |
| 2.4712 | 1.6089 | 2600 | 2.1712 | 0.0045 | 0.0271 | 0.0002 | 0.0 | 0.0001 | 0.0082 | 0.0061 | 0.0381 | 0.1355 | 0.0 | 0.0811 | 0.2225 | 0.0001 | 0.0024 | 0.0135 | 0.404 | 0.0 | 0.0 |
| 1.6899 | 1.7327 | 2800 | 2.1685 | 0.0053 | 0.0234 | 0.0004 | 0.0 | 0.0002 | 0.0096 | 0.0123 | 0.0456 | 0.1269 | 0.0 | 0.0689 | 0.21 | 0.0001 | 0.0048 | 0.0158 | 0.376 | 0.0 | 0.0 |
| 2.2178 | 1.8564 | 3000 | 2.0968 | 0.0049 | 0.0198 | 0.0004 | 0.0 | 0.0002 | 0.0087 | 0.0104 | 0.0291 | 0.1344 | 0.0 | 0.0748 | 0.2225 | 0.0001 | 0.0032 | 0.0145 | 0.4 | 0.0 | 0.0 |
| 1.8933 | 1.9802 | 3200 | 2.0313 | 0.0083 | 0.025 | 0.0006 | 0.0 | 0.0007 | 0.0145 | 0.0144 | 0.0429 | 0.1535 | 0.0 | 0.0847 | 0.245 | 0.0011 | 0.0246 | 0.024 | 0.436 | 0.0 | 0.0 |
| 1.853 | 2.1040 | 3400 | 2.0302 | 0.0068 | 0.0188 | 0.0045 | 0.0 | 0.0008 | 0.0119 | 0.0088 | 0.0455 | 0.161 | 0.0 | 0.1331 | 0.2325 | 0.0007 | 0.0429 | 0.0196 | 0.44 | 0.0 | 0.0 |
| 2.0421 | 2.2277 | 3600 | 1.9522 | 0.0207 | 0.0411 | 0.0193 | 0.0 | 0.0011 | 0.0369 | 0.0243 | 0.0638 | 0.1649 | 0.0 | 0.0889 | 0.2475 | 0.0018 | 0.0627 | 0.0603 | 0.432 | 0.0 | 0.0 |
| 1.8444 | 2.3515 | 3800 | 2.0036 | 0.0147 | 0.0308 | 0.02 | 0.0 | 0.0013 | 0.0268 | 0.0227 | 0.0788 | 0.1709 | 0.0 | 0.1521 | 0.2219 | 0.0016 | 0.1008 | 0.0425 | 0.412 | 0.0 | 0.0 |
| 1.6694 | 2.4752 | 4000 | 1.9610 | 0.0219 | 0.0511 | 0.0122 | 0.0 | 0.0019 | 0.0398 | 0.0232 | 0.0776 | 0.1888 | 0.0 | 0.1421 | 0.2569 | 0.0034 | 0.1063 | 0.0624 | 0.46 | 0.0 | 0.0 |
| 2.3946 | 2.5990 | 4200 | 2.0770 | 0.0108 | 0.0275 | 0.0083 | 0.0 | 0.0018 | 0.0197 | 0.0197 | 0.0792 | 0.1907 | 0.0 | 0.1258 | 0.2709 | 0.0033 | 0.1 | 0.029 | 0.472 | 0.0 | 0.0 |
| 2.4217 | 2.7228 | 4400 | 1.9638 | 0.021 | 0.0442 | 0.0115 | 0.0 | 0.004 | 0.0464 | 0.041 | 0.1054 | 0.2092 | 0.0 | 0.1873 | 0.2597 | 0.0047 | 0.1675 | 0.0583 | 0.46 | 0.0 | 0.0 |
| 1.6397 | 2.8465 | 4600 | 1.9357 | 0.0216 | 0.0519 | 0.0047 | 0.0 | 0.0031 | 0.048 | 0.0341 | 0.0923 | 0.2212 | 0.0 | 0.1441 | 0.3116 | 0.0055 | 0.1476 | 0.0592 | 0.516 | 0.0 | 0.0 |
| 1.9243 | 2.9703 | 4800 | 1.8502 | 0.016 | 0.0432 | 0.0039 | 0.0 | 0.0034 | 0.0347 | 0.0226 | 0.0791 | 0.231 | 0.0 | 0.1428 | 0.3194 | 0.0072 | 0.1929 | 0.041 | 0.5 | 0.0 | 0.0 |
| 1.6861 | 3.0941 | 5000 | 1.9368 | 0.0189 | 0.0463 | 0.0114 | 0.0 | 0.0031 | 0.0368 | 0.0296 | 0.0848 | 0.2233 | 0.0 | 0.1311 | 0.3112 | 0.0063 | 0.1619 | 0.0505 | 0.508 | 0.0 | 0.0 |
| 1.9067 | 3.2178 | 5200 | 1.8978 | 0.0169 | 0.0433 | 0.0074 | 0.0 | 0.0041 | 0.0449 | 0.0309 | 0.081 | 0.2381 | 0.0 | 0.1179 | 0.3378 | 0.0084 | 0.2143 | 0.0422 | 0.5 | 0.0 | 0.0 |
| 2.3952 | 3.3416 | 5400 | 1.8205 | 0.0156 | 0.0393 | 0.0099 | 0.0 | 0.0037 | 0.0402 | 0.0234 | 0.0938 | 0.2529 | 0.0 | 0.214 | 0.3157 | 0.0077 | 0.2508 | 0.0391 | 0.508 | 0.0 | 0.0 |
| 1.7741 | 3.4653 | 5600 | 1.7616 | 0.0256 | 0.057 | 0.0269 | 0.0 | 0.0045 | 0.0726 | 0.0301 | 0.0879 | 0.2614 | 0.0 | 0.1933 | 0.3504 | 0.0097 | 0.2563 | 0.067 | 0.528 | 0.0 | 0.0 |
| 1.5789 | 3.5891 | 5800 | 1.8325 | 0.0216 | 0.0437 | 0.0189 | 0.0064 | 0.0032 | 0.0411 | 0.0706 | 0.137 | 0.2674 | 0.0625 | 0.1486 | 0.314 | 0.0064 | 0.2063 | 0.0542 | 0.496 | 0.0043 | 0.1 |
| 1.631 | 3.7129 | 6000 | 1.8235 | 0.0209 | 0.0442 | 0.0203 | 0.0035 | 0.0036 | 0.0411 | 0.0583 | 0.1205 | 0.2719 | 0.0375 | 0.2023 | 0.3185 | 0.0065 | 0.2198 | 0.0543 | 0.536 | 0.0019 | 0.06 |
| 1.9591 | 3.8366 | 6200 | 1.6983 | 0.0195 | 0.0438 | 0.012 | 0.0 | 0.0054 | 0.0464 | 0.0322 | 0.0967 | 0.2888 | 0.0 | 0.2202 | 0.4049 | 0.0126 | 0.2865 | 0.046 | 0.58 | 0.0 | 0.0 |
| 1.7331 | 3.9604 | 6400 | 1.7687 | 0.0193 | 0.0422 | 0.016 | 0.0 | 0.0046 | 0.0485 | 0.0314 | 0.1196 | 0.2662 | 0.0 | 0.1969 | 0.3584 | 0.0095 | 0.2627 | 0.0484 | 0.536 | 0.0 | 0.0 |
| 1.5073 | 4.0842 | 6600 | 1.7121 | 0.0211 | 0.0444 | 0.022 | 0.0 | 0.005 | 0.0472 | 0.0309 | 0.1175 | 0.2625 | 0.0 | 0.1658 | 0.3643 | 0.0107 | 0.2714 | 0.0525 | 0.516 | 0.0 | 0.0 |
| 1.9417 | 4.2079 | 6800 | 1.7394 | 0.0264 | 0.049 | 0.0244 | 0.0012 | 0.0055 | 0.0582 | 0.0461 | 0.1449 | 0.2889 | 0.0125 | 0.2006 | 0.3824 | 0.0113 | 0.2746 | 0.0671 | 0.572 | 0.0007 | 0.02 |
| 1.8069 | 4.3317 | 7000 | 1.7050 | 0.0244 | 0.0497 | 0.0223 | 0.0 | 0.0051 | 0.0641 | 0.0484 | 0.1316 | 0.2643 | 0.0 | 0.1977 | 0.3856 | 0.0118 | 0.273 | 0.0614 | 0.52 | 0.0 | 0.0 |
| 1.2717 | 4.4554 | 7200 | 1.6229 | 0.0268 | 0.0508 | 0.0255 | 0.0 | 0.0078 | 0.0583 | 0.0468 | 0.1427 | 0.293 | 0.0 | 0.2127 | 0.4259 | 0.0182 | 0.3111 | 0.0621 | 0.568 | 0.0 | 0.0 |
| 1.8009 | 4.5792 | 7400 | 1.6753 | 0.0236 | 0.0533 | 0.0115 | 0.0 | 0.0053 | 0.0566 | 0.042 | 0.1215 | 0.284 | 0.0 | 0.222 | 0.3743 | 0.011 | 0.2921 | 0.0598 | 0.56 | 0.0 | 0.0 |
| 1.8661 | 4.7030 | 7600 | 1.6594 | 0.0234 | 0.0429 | 0.0232 | 0.0 | 0.0055 | 0.06 | 0.045 | 0.1372 | 0.2938 | 0.0 | 0.2174 | 0.4115 | 0.0116 | 0.3333 | 0.0586 | 0.548 | 0.0 | 0.0 |
| 1.5983 | 4.8267 | 7800 | 1.6727 | 0.0206 | 0.0436 | 0.0123 | 0.0 | 0.0056 | 0.0529 | 0.0447 | 0.1407 | 0.2986 | 0.0 | 0.2537 | 0.3909 | 0.0108 | 0.3278 | 0.051 | 0.568 | 0.0 | 0.0 |
| 2.0424 | 4.9505 | 8000 | 1.7269 | 0.0302 | 0.0571 | 0.0391 | 0.0 | 0.0062 | 0.0693 | 0.0431 | 0.1223 | 0.2887 | 0.0 | 0.2152 | 0.3659 | 0.0112 | 0.3222 | 0.0793 | 0.544 | 0.0 | 0.0 |
| 1.3068 | 5.0743 | 8200 | 1.6624 | 0.0233 | 0.0437 | 0.0233 | 0.0 | 0.0059 | 0.0579 | 0.0426 | 0.1324 | 0.293 | 0.0 | 0.2378 | 0.385 | 0.0109 | 0.319 | 0.0589 | 0.56 | 0.0 | 0.0 |
| 1.7284 | 5.1980 | 8400 | 1.6596 | 0.0286 | 0.0553 | 0.0327 | 0.0 | 0.0067 | 0.0699 | 0.0497 | 0.1385 | 0.2959 | 0.0 | 0.2515 | 0.3932 | 0.013 | 0.3278 | 0.0728 | 0.56 | 0.0 | 0.0 |
| 2.2819 | 5.3218 | 8600 | 1.6320 | 0.0221 | 0.0446 | 0.0151 | 0.0 | 0.0061 | 0.058 | 0.045 | 0.142 | 0.3095 | 0.0 | 0.2607 | 0.4043 | 0.013 | 0.3484 | 0.0533 | 0.58 | 0.0 | 0.0 |
| 1.2565 | 5.4455 | 8800 | 1.6319 | 0.0241 | 0.0507 | 0.0224 | 0.0 | 0.0057 | 0.0567 | 0.0399 | 0.1444 | 0.2943 | 0.0 | 0.2259 | 0.3918 | 0.0113 | 0.3429 | 0.061 | 0.54 | 0.0 | 0.0 |
| 2.0009 | 5.5693 | 9000 | 1.6232 | 0.0228 | 0.0461 | 0.0226 | 0.0 | 0.006 | 0.056 | 0.0405 | 0.1401 | 0.3026 | 0.0 | 0.2203 | 0.4063 | 0.0122 | 0.3437 | 0.0563 | 0.564 | 0.0 | 0.0 |
| 1.1549 | 5.6931 | 9200 | 1.6247 | 0.0241 | 0.0472 | 0.0221 | 0.0 | 0.0065 | 0.0703 | 0.0455 | 0.1297 | 0.3044 | 0.0 | 0.2236 | 0.4165 | 0.0144 | 0.3611 | 0.0579 | 0.552 | 0.0 | 0.0 |
| 1.3283 | 5.8168 | 9400 | 1.6025 | 0.0243 | 0.0497 | 0.023 | 0.0 | 0.0064 | 0.0683 | 0.0383 | 0.1299 | 0.3044 | 0.0 | 0.214 | 0.421 | 0.0137 | 0.3532 | 0.0592 | 0.56 | 0.0 | 0.0 |
| 1.9137 | 5.9406 | 9600 | 1.6489 | 0.0234 | 0.0454 | 0.024 | 0.0 | 0.0065 | 0.0713 | 0.0418 | 0.1353 | 0.3055 | 0.0 | 0.2311 | 0.4166 | 0.0127 | 0.3444 | 0.0576 | 0.572 | 0.0 | 0.0 |
| 1.8353 | 6.0644 | 9800 | 1.6261 | 0.0234 | 0.0451 | 0.0237 | 0.0 | 0.0064 | 0.0638 | 0.0426 | 0.1372 | 0.306 | 0.0 | 0.2318 | 0.4229 | 0.0127 | 0.35 | 0.0576 | 0.568 | 0.0 | 0.0 |
| 1.5491 | 6.1881 | 10000 | 1.6175 | 0.0235 | 0.0454 | 0.0236 | 0.0 | 0.0065 | 0.0651 | 0.0428 | 0.1393 | 0.3049 | 0.0 | 0.2244 | 0.4274 | 0.0131 | 0.3508 | 0.0574 | 0.564 | 0.0 | 0.0 |
### Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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