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---
library_name: transformers
license: apache-2.0
base_model: PekingU/rtdetr_v2_r50vd
tags:
- generated_from_trainer
model-index:
- name: rtdetr-v2-r50-kitti2-finetune-2
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. -->
# rtdetr-v2-r50-kitti2-finetune-2
This model is a fine-tuned version of [PekingU/rtdetr_v2_r50vd](https://huggingface.co/PekingU/rtdetr_v2_r50vd) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 10.8052
- Map: 0.3423
- Map 50: 0.5623
- Map 75: 0.3606
- Map Small: 0.2161
- Map Medium: 0.3631
- Map Large: 0.4172
- Mar 1: 0.2926
- Mar 10: 0.5137
- Mar 100: 0.5886
- Mar Small: 0.4156
- Mar Medium: 0.5976
- Mar Large: 0.6841
- Map Car: 0.6052
- Mar 100 Car: 0.7464
- Map Pedestrian: 0.3483
- Mar 100 Pedestrian: 0.5172
- Map Cyclist: 0.2062
- Mar 100 Cyclist: 0.4523
- Map Van: 0.5231
- Mar 100 Van: 0.7377
- Map Truck: 0.6026
- Mar 100 Truck: 0.7417
- Map Misc: 0.1678
- Mar 100 Misc: 0.516
- Map Tram: 0.3851
- Mar 100 Tram: 0.6984
- Map Person Sitting: 0.1978
- Mar 100 Person Sitting: 0.5314
- Map Dontcare: 0.0442
- Mar 100 Dontcare: 0.3566
## 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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 300
- num_epochs: 10
### 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 Car | Mar 100 Car | Map Pedestrian | Mar 100 Pedestrian | Map Cyclist | Mar 100 Cyclist | Map Van | Mar 100 Van | Map Truck | Mar 100 Truck | Map Misc | Mar 100 Misc | Map Tram | Mar 100 Tram | Map Person Sitting | Mar 100 Person Sitting | Map Dontcare | Mar 100 Dontcare |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:----------:|:---------:|:------:|:------:|:-------:|:---------:|:----------:|:---------:|:-------:|:-----------:|:--------------:|:------------------:|:-----------:|:---------------:|:-------:|:-----------:|:---------:|:-------------:|:--------:|:------------:|:--------:|:------------:|:------------------:|:----------------------:|:------------:|:----------------:|
| 34.3989 | 1.0 | 655 | 10.4608 | 0.2538 | 0.4309 | 0.2527 | 0.1757 | 0.2643 | 0.3546 | 0.2566 | 0.4571 | 0.5322 | 0.3842 | 0.5368 | 0.6569 | 0.6141 | 0.743 | 0.2816 | 0.4418 | 0.1456 | 0.4579 | 0.4092 | 0.6612 | 0.4751 | 0.7195 | 0.0566 | 0.4101 | 0.133 | 0.6307 | 0.1334 | 0.4357 | 0.0356 | 0.2902 |
| 15.6516 | 2.0 | 1310 | 10.8110 | 0.3342 | 0.5511 | 0.3468 | 0.2589 | 0.3513 | 0.4378 | 0.2863 | 0.5125 | 0.5775 | 0.4382 | 0.5818 | 0.7005 | 0.6159 | 0.7491 | 0.3197 | 0.4894 | 0.249 | 0.4594 | 0.4919 | 0.6995 | 0.6118 | 0.7552 | 0.1736 | 0.502 | 0.3949 | 0.7102 | 0.1077 | 0.4786 | 0.0433 | 0.354 |
| 14.1316 | 3.0 | 1965 | 11.9174 | 0.3267 | 0.5128 | 0.3591 | 0.2156 | 0.3255 | 0.4735 | 0.2828 | 0.5065 | 0.5748 | 0.4402 | 0.5811 | 0.7018 | 0.5899 | 0.7322 | 0.3121 | 0.4754 | 0.2163 | 0.4766 | 0.4165 | 0.6865 | 0.5878 | 0.7526 | 0.1879 | 0.5507 | 0.429 | 0.6807 | 0.1537 | 0.45 | 0.0474 | 0.3687 |
| 12.9222 | 4.0 | 2620 | 12.5913 | 0.3124 | 0.4931 | 0.3376 | 0.2457 | 0.3275 | 0.46 | 0.279 | 0.4928 | 0.5516 | 0.4054 | 0.5606 | 0.688 | 0.5478 | 0.7176 | 0.2902 | 0.4381 | 0.13 | 0.413 | 0.4401 | 0.6785 | 0.5964 | 0.7468 | 0.2421 | 0.5601 | 0.4089 | 0.7057 | 0.108 | 0.3429 | 0.0482 | 0.3613 |
| 12.6036 | 5.0 | 3275 | 13.0327 | 0.3117 | 0.4742 | 0.3476 | 0.2483 | 0.3282 | 0.4539 | 0.2901 | 0.4865 | 0.5418 | 0.4431 | 0.5536 | 0.6582 | 0.5549 | 0.7381 | 0.292 | 0.4435 | 0.1428 | 0.3874 | 0.4093 | 0.6968 | 0.5729 | 0.7494 | 0.2757 | 0.6088 | 0.4991 | 0.6989 | 0.0056 | 0.1714 | 0.0528 | 0.3825 |
| 12.2062 | 6.0 | 3930 | 13.2957 | 0.3151 | 0.4824 | 0.3456 | 0.2292 | 0.3166 | 0.465 | 0.2908 | 0.4839 | 0.5362 | 0.4192 | 0.5437 | 0.663 | 0.5304 | 0.7357 | 0.2899 | 0.4352 | 0.1494 | 0.3556 | 0.4531 | 0.6872 | 0.5778 | 0.7442 | 0.3199 | 0.598 | 0.4628 | 0.7034 | 0.004 | 0.1714 | 0.0491 | 0.3949 |
| 11.847 | 7.0 | 4585 | 13.1970 | 0.309 | 0.4753 | 0.3435 | 0.2333 | 0.3199 | 0.4422 | 0.2983 | 0.4868 | 0.5398 | 0.4161 | 0.5544 | 0.6635 | 0.5359 | 0.7321 | 0.2909 | 0.4272 | 0.099 | 0.359 | 0.4248 | 0.6806 | 0.5835 | 0.7247 | 0.2946 | 0.6203 | 0.4941 | 0.7102 | 0.0087 | 0.2214 | 0.0495 | 0.3826 |
### Framework versions
- Transformers 4.50.0.dev0
- Pytorch 2.6.0+cu124
- Datasets 3.4.0
- Tokenizers 0.21.1
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