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---
license: apache-2.0
base_model: facebook/detr-resnet-50
tags:
- generated_from_trainer
model-index:
- name: Vehicle_Detection_Model_Zoom
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. -->
# Vehicle_Detection_Model_Zoom
This model is a fine-tuned version of [facebook/detr-resnet-50](https://huggingface.co/facebook/detr-resnet-50) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7673
- Map: 0.0853
- Map 50: 0.1613
- Map 75: 0.0814
- Map Small: 0.452
- Map Medium: 0.1098
- Map Large: 0.0
- Mar 1: 0.1187
- Mar 10: 0.1824
- Mar 100: 0.1934
- Mar Small: 0.5946
- Mar Medium: 0.1984
- Mar Large: 0.0
- Map Camping car: 0.0353
- Mar 100 Camping car: 0.35
- Map Car: 0.4678
- Mar 100 Car: 0.6103
- Map Other: 0.0
- Mar 100 Other: 0.0
- Map Pickup: 0.0088
- Mar 100 Pickup: 0.2
- Map Truck: 0.0
- Mar 100 Truck: 0.0
- Map Van: 0.0
- Mar 100 Van: 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: 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 Camping car | Mar 100 Camping car | Map Car | Mar 100 Car | Map Other | Mar 100 Other | Map Pickup | Mar 100 Pickup | Map Truck | Mar 100 Truck | Map Van | Mar 100 Van |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:----------:|:---------:|:------:|:------:|:-------:|:---------:|:----------:|:---------:|:---------------:|:-------------------:|:-------:|:-----------:|:---------:|:-------------:|:----------:|:--------------:|:---------:|:-------------:|:-------:|:-----------:|
| No log | 1.0 | 232 | 1.2888 | 0.0179 | 0.0435 | 0.0095 | 0.118 | 0.0187 | 0.0 | 0.0175 | 0.0527 | 0.0838 | 0.4665 | 0.0955 | 0.0 | 0.0 | 0.0 | 0.1073 | 0.5028 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| No log | 2.0 | 464 | 1.1028 | 0.0308 | 0.0792 | 0.0172 | 0.2225 | 0.0267 | 0.0 | 0.0233 | 0.0637 | 0.0818 | 0.4346 | 0.0998 | 0.0 | 0.0 | 0.0 | 0.1851 | 0.4907 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.5836 | 3.0 | 696 | 1.0727 | 0.0509 | 0.1216 | 0.0268 | 0.3118 | 0.0531 | 0.0 | 0.0278 | 0.0702 | 0.0781 | 0.4362 | 0.0884 | 0.0 | 0.0 | 0.0 | 0.3055 | 0.4683 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.5836 | 4.0 | 928 | 1.1038 | 0.0467 | 0.1199 | 0.0193 | 0.2617 | 0.0543 | 0.0 | 0.0249 | 0.0679 | 0.0772 | 0.4357 | 0.0861 | 0.0 | 0.0 | 0.0 | 0.2803 | 0.4633 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.1611 | 5.0 | 1160 | 1.0186 | 0.057 | 0.13 | 0.0335 | 0.3254 | 0.0643 | 0.0 | 0.0281 | 0.0721 | 0.0819 | 0.4735 | 0.0877 | 0.0 | 0.0 | 0.0 | 0.3422 | 0.4915 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.1611 | 6.0 | 1392 | 1.0468 | 0.0541 | 0.1255 | 0.029 | 0.3094 | 0.0612 | 0.0 | 0.0288 | 0.0735 | 0.0816 | 0.4557 | 0.0925 | 0.0 | 0.0 | 0.0 | 0.3249 | 0.4897 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.1009 | 7.0 | 1624 | 0.9479 | 0.063 | 0.1366 | 0.0467 | 0.3682 | 0.0676 | 0.0 | 0.0312 | 0.0789 | 0.0905 | 0.507 | 0.1019 | 0.0 | 0.0 | 0.0 | 0.3781 | 0.5427 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.1009 | 8.0 | 1856 | 0.9808 | 0.0556 | 0.1305 | 0.0355 | 0.3103 | 0.0652 | 0.0 | 0.0295 | 0.074 | 0.0858 | 0.4789 | 0.0974 | 0.0 | 0.0 | 0.0 | 0.3338 | 0.5149 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.043 | 9.0 | 2088 | 1.0168 | 0.0504 | 0.1232 | 0.0248 | 0.2652 | 0.0654 | 0.0 | 0.0271 | 0.0716 | 0.0815 | 0.4443 | 0.0958 | 0.0 | 0.0 | 0.0 | 0.3022 | 0.489 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.043 | 10.0 | 2320 | 0.9497 | 0.0536 | 0.1207 | 0.0312 | 0.2924 | 0.0715 | 0.0 | 0.0299 | 0.0755 | 0.0888 | 0.4968 | 0.1003 | 0.0 | 0.0 | 0.0 | 0.3218 | 0.5327 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.026 | 11.0 | 2552 | 0.9826 | 0.0844 | 0.1826 | 0.0374 | 0.3582 | 0.0936 | 0.0 | 0.0727 | 0.1434 | 0.1534 | 0.4795 | 0.1667 | 0.0 | 0.127 | 0.4 | 0.3792 | 0.5206 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 1.026 | 12.0 | 2784 | 0.9282 | 0.0615 | 0.1396 | 0.0422 | 0.3292 | 0.0758 | 0.0 | 0.0809 | 0.1281 | 0.1357 | 0.4784 | 0.1472 | 0.0 | 0.0202 | 0.3 | 0.3487 | 0.5142 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.9794 | 13.0 | 3016 | 0.8976 | 0.0663 | 0.1368 | 0.0541 | 0.3854 | 0.0748 | 0.0 | 0.0317 | 0.0821 | 0.0942 | 0.5389 | 0.1026 | 0.0 | 0.0 | 0.0 | 0.3977 | 0.5651 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.9794 | 14.0 | 3248 | 0.8970 | 0.0633 | 0.1358 | 0.0474 | 0.3519 | 0.0754 | 0.0 | 0.0315 | 0.0799 | 0.0929 | 0.5151 | 0.1066 | 0.0 | 0.0 | 0.0 | 0.3798 | 0.5577 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.9794 | 15.0 | 3480 | 0.8418 | 0.0677 | 0.1368 | 0.052 | 0.3737 | 0.0807 | 0.0 | 0.0328 | 0.0837 | 0.0935 | 0.5265 | 0.1045 | 0.0 | 0.0 | 0.0 | 0.4063 | 0.5609 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.9189 | 16.0 | 3712 | 0.8709 | 0.0677 | 0.1414 | 0.055 | 0.3733 | 0.0808 | 0.0 | 0.066 | 0.1151 | 0.1261 | 0.5308 | 0.1344 | 0.0 | 0.0033 | 0.2 | 0.4031 | 0.5566 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.9189 | 17.0 | 3944 | 0.9095 | 0.0657 | 0.1386 | 0.048 | 0.3734 | 0.0746 | 0.0 | 0.0444 | 0.0925 | 0.1004 | 0.4935 | 0.1139 | 0.0 | 0.0 | 0.0 | 0.3918 | 0.5356 | 0.0 | 0.0 | 0.0024 | 0.0667 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.8933 | 18.0 | 4176 | 0.8832 | 0.0651 | 0.1416 | 0.046 | 0.3467 | 0.0809 | 0.0 | 0.1021 | 0.1488 | 0.1594 | 0.5076 | 0.1698 | 0.0 | 0.0151 | 0.3 | 0.3708 | 0.5399 | 0.0 | 0.0 | 0.0045 | 0.1167 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.8933 | 19.0 | 4408 | 0.8459 | 0.0707 | 0.1444 | 0.0527 | 0.4093 | 0.0782 | 0.0 | 0.043 | 0.0914 | 0.1017 | 0.5405 | 0.1082 | 0.0 | 0.0 | 0.0 | 0.4231 | 0.5605 | 0.0 | 0.0 | 0.0013 | 0.05 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.8732 | 20.0 | 4640 | 0.8352 | 0.0719 | 0.151 | 0.0581 | 0.3987 | 0.0853 | 0.0 | 0.0699 | 0.1257 | 0.1366 | 0.5459 | 0.1443 | 0.0 | 0.001 | 0.05 | 0.4198 | 0.5698 | 0.0 | 0.0 | 0.0106 | 0.2 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.8732 | 21.0 | 4872 | 0.8110 | 0.077 | 0.1574 | 0.0657 | 0.407 | 0.0938 | 0.0 | 0.1345 | 0.1896 | 0.2005 | 0.5638 | 0.2078 | 0.0 | 0.0104 | 0.3 | 0.4317 | 0.5865 | 0.0 | 0.0 | 0.0201 | 0.3167 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.8261 | 22.0 | 5104 | 0.8235 | 0.074 | 0.1564 | 0.0561 | 0.4045 | 0.0867 | 0.0 | 0.0842 | 0.1682 | 0.1776 | 0.5422 | 0.1851 | 0.0 | 0.0066 | 0.15 | 0.4229 | 0.5655 | 0.0 | 0.0 | 0.0144 | 0.35 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.8261 | 23.0 | 5336 | 0.8116 | 0.0817 | 0.1636 | 0.0731 | 0.4237 | 0.0965 | 0.0 | 0.1115 | 0.1724 | 0.1822 | 0.5557 | 0.1889 | 0.0 | 0.0433 | 0.3 | 0.4392 | 0.5765 | 0.0 | 0.0 | 0.0074 | 0.2167 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.8213 | 24.0 | 5568 | 0.7748 | 0.0841 | 0.1619 | 0.0746 | 0.4393 | 0.1182 | 0.0 | 0.1244 | 0.1874 | 0.197 | 0.58 | 0.2031 | 0.0 | 0.0393 | 0.35 | 0.457 | 0.5989 | 0.0 | 0.0 | 0.0085 | 0.2333 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.8213 | 25.0 | 5800 | 0.7782 | 0.0893 | 0.1678 | 0.0802 | 0.4418 | 0.1555 | 0.0 | 0.1376 | 0.2022 | 0.2134 | 0.5795 | 0.2191 | 0.0 | 0.0683 | 0.45 | 0.4583 | 0.5972 | 0.0 | 0.0 | 0.009 | 0.2333 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.794 | 26.0 | 6032 | 0.7822 | 0.082 | 0.1585 | 0.0738 | 0.4368 | 0.1026 | 0.0 | 0.118 | 0.191 | 0.2021 | 0.5773 | 0.208 | 0.0 | 0.0324 | 0.4 | 0.4519 | 0.5957 | 0.0 | 0.0 | 0.0074 | 0.2167 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.794 | 27.0 | 6264 | 0.7735 | 0.0888 | 0.1683 | 0.0879 | 0.4533 | 0.1188 | 0.0 | 0.1404 | 0.1981 | 0.2087 | 0.5865 | 0.2137 | 0.0 | 0.0505 | 0.35 | 0.4672 | 0.6021 | 0.0 | 0.0 | 0.0153 | 0.3 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.794 | 28.0 | 6496 | 0.7680 | 0.0852 | 0.1608 | 0.0842 | 0.4557 | 0.109 | 0.0 | 0.1186 | 0.1821 | 0.1924 | 0.5892 | 0.1974 | 0.0 | 0.0321 | 0.35 | 0.4705 | 0.6046 | 0.0 | 0.0 | 0.0088 | 0.2 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.7843 | 29.0 | 6728 | 0.7678 | 0.0852 | 0.1614 | 0.0817 | 0.4516 | 0.1095 | 0.0 | 0.1185 | 0.1821 | 0.1931 | 0.593 | 0.1981 | 0.0 | 0.0353 | 0.35 | 0.4673 | 0.6085 | 0.0 | 0.0 | 0.0088 | 0.2 | 0.0 | 0.0 | 0.0 | 0.0 |
| 0.7843 | 30.0 | 6960 | 0.7673 | 0.0853 | 0.1613 | 0.0814 | 0.452 | 0.1098 | 0.0 | 0.1187 | 0.1824 | 0.1934 | 0.5946 | 0.1984 | 0.0 | 0.0353 | 0.35 | 0.4678 | 0.6103 | 0.0 | 0.0 | 0.0088 | 0.2 | 0.0 | 0.0 | 0.0 | 0.0 |
### Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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