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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-cppe5-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-cppe5-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: 10.6505
- Map: 0.4323
- Map 50: 0.8963
- Map 75: 0.3219
- Map Small: 0.3756
- Map Medium: 0.5476
- Map Large: 0.7106
- Mar 1: 0.2852
- Mar 10: 0.4788
- Mar 100: 0.5715
- Mar Small: 0.5305
- Mar Medium: 0.6698
- Mar Large: 0.7583
- Map Football: 0.4833
- Mar 100 Football: 0.5867
- Map Player: 0.3814
- Mar 100 Player: 0.5564
## 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: 16
- 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: cosine
- lr_scheduler_warmup_steps: 300
- num_epochs: 12
### 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 Football | Mar 100 Football | Map Player | Mar 100 Player |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:----------:|:---------:|:------:|:------:|:-------:|:---------:|:----------:|:---------:|:------------:|:----------------:|:----------:|:--------------:|
| No log | 1.0 | 62 | 17.5576 | 0.1072 | 0.2555 | 0.0663 | 0.0878 | 0.1914 | 0.1325 | 0.0543 | 0.208 | 0.3404 | 0.2858 | 0.4734 | 0.5447 | 0.0102 | 0.2166 | 0.2042 | 0.4642 |
| No log | 2.0 | 124 | 9.5985 | 0.3615 | 0.8054 | 0.2547 | 0.3082 | 0.5041 | 0.5671 | 0.2189 | 0.4346 | 0.5265 | 0.4739 | 0.6782 | 0.6455 | 0.3255 | 0.4828 | 0.3975 | 0.5702 |
| No log | 3.0 | 186 | 9.6654 | 0.3647 | 0.8181 | 0.2656 | 0.3115 | 0.5271 | 0.6 | 0.2353 | 0.4404 | 0.5339 | 0.4772 | 0.685 | 0.7447 | 0.3696 | 0.5225 | 0.3597 | 0.5452 |
| No log | 4.0 | 248 | 10.0423 | 0.3637 | 0.8276 | 0.2328 | 0.3011 | 0.5362 | 0.6091 | 0.2209 | 0.4219 | 0.5103 | 0.4515 | 0.674 | 0.7477 | 0.345 | 0.474 | 0.3823 | 0.5467 |
| No log | 5.0 | 310 | 10.2540 | 0.3952 | 0.8224 | 0.3201 | 0.3304 | 0.5617 | 0.6733 | 0.2556 | 0.4589 | 0.548 | 0.4924 | 0.6929 | 0.7598 | 0.4203 | 0.5509 | 0.3702 | 0.5452 |
| No log | 6.0 | 372 | 10.4936 | 0.3862 | 0.8134 | 0.3167 | 0.3148 | 0.5569 | 0.6616 | 0.2459 | 0.4368 | 0.5254 | 0.4659 | 0.6818 | 0.797 | 0.3995 | 0.5089 | 0.373 | 0.5418 |
| No log | 7.0 | 434 | 10.6991 | 0.4119 | 0.8405 | 0.3383 | 0.348 | 0.5668 | 0.6627 | 0.2615 | 0.4528 | 0.5379 | 0.4824 | 0.6929 | 0.7515 | 0.4282 | 0.5219 | 0.3955 | 0.5539 |
| No log | 8.0 | 496 | 10.7472 | 0.4216 | 0.8338 | 0.3662 | 0.3592 | 0.5737 | 0.6884 | 0.2668 | 0.4624 | 0.5513 | 0.4966 | 0.701 | 0.7561 | 0.4488 | 0.5438 | 0.3943 | 0.5588 |
| 19.6326 | 9.0 | 558 | 10.9720 | 0.3984 | 0.8353 | 0.3183 | 0.3307 | 0.5564 | 0.7087 | 0.2605 | 0.4449 | 0.5241 | 0.4658 | 0.6661 | 0.797 | 0.4371 | 0.5302 | 0.3598 | 0.518 |
| 19.6326 | 10.0 | 620 | 10.9521 | 0.4117 | 0.8392 | 0.3436 | 0.3458 | 0.569 | 0.6785 | 0.2584 | 0.4495 | 0.5315 | 0.4753 | 0.6815 | 0.75 | 0.436 | 0.5195 | 0.3873 | 0.5435 |
| 19.6326 | 11.0 | 682 | 11.0008 | 0.4158 | 0.8449 | 0.3501 | 0.3509 | 0.5711 | 0.6707 | 0.2626 | 0.4517 | 0.5369 | 0.4837 | 0.6821 | 0.7447 | 0.4374 | 0.5237 | 0.3942 | 0.5502 |
| 19.6326 | 12.0 | 744 | 11.0544 | 0.411 | 0.8363 | 0.3415 | 0.3436 | 0.5727 | 0.6689 | 0.259 | 0.4496 | 0.5331 | 0.4775 | 0.6857 | 0.7439 | 0.4336 | 0.5225 | 0.3883 | 0.5438 |
### Framework versions
- Transformers 4.51.3
- Pytorch 2.7.0+cu126
- Datasets 3.6.0
- Tokenizers 0.21.1
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