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---
library_name: transformers
license: apache-2.0
base_model: PekingU/rtdetr_v2_r50vd
tags:
- generated_from_trainer
model-index:
- name: rt_detrv2_finetuned_trashify_box_detector_v1
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. -->
# rt_detrv2_finetuned_trashify_box_detector_v1
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: 9.1849
- Map: 0.4434
- Map 50: 0.5945
- Map 75: 0.5133
- Map Small: 0.0
- Map Medium: 0.2517
- Map Large: 0.4539
- Mar 1: 0.4959
- Mar 10: 0.7238
- Mar 100: 0.7536
- Mar Small: 0.0
- Mar Medium: 0.6084
- Mar Large: 0.7678
- Map Bin: 0.7782
- Mar 100 Bin: 0.882
- Map Hand: 0.5971
- Mar 100 Hand: 0.8338
- Map Not Bin: 0.1267
- Mar 100 Not Bin: 0.6091
- Map Not Hand: 0.0133
- Mar 100 Not Hand: 0.6667
- Map Not Trash: 0.2197
- Mar 100 Not Trash: 0.623
- Map Trash: 0.6299
- Mar 100 Trash: 0.8319
- Map Trash Arm: 0.7385
- Mar 100 Trash Arm: 0.8286
## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 10
- 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 Bin | Mar 100 Bin | Map Hand | Mar 100 Hand | Map Not Bin | Mar 100 Not Bin | Map Not Hand | Mar 100 Not Hand | Map Not Trash | Mar 100 Not Trash | Map Trash | Mar 100 Trash | Map Trash Arm | Mar 100 Trash Arm |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:----------:|:---------:|:------:|:------:|:-------:|:---------:|:----------:|:---------:|:-------:|:-----------:|:--------:|:------------:|:-----------:|:---------------:|:------------:|:----------------:|:-------------:|:-----------------:|:---------:|:-------------:|:-------------:|:-----------------:|
| 53.6652 | 1.0 | 99 | 12.6070 | 0.2868 | 0.426 | 0.3096 | 0.06 | 0.1591 | 0.2961 | 0.3889 | 0.5988 | 0.676 | 0.15 | 0.4608 | 0.7078 | 0.6044 | 0.8801 | 0.4455 | 0.7755 | 0.0112 | 0.5429 | -1.0 | -1.0 | 0.123 | 0.5222 | 0.5357 | 0.7354 | 0.001 | 0.6 |
| 19.3483 | 2.0 | 198 | 10.0845 | 0.3512 | 0.4978 | 0.3906 | 0.0221 | 0.1881 | 0.3675 | 0.378 | 0.5818 | 0.7372 | 0.3 | 0.5415 | 0.7631 | 0.7322 | 0.8553 | 0.5916 | 0.8059 | 0.0227 | 0.6071 | -1.0 | -1.0 | 0.1747 | 0.5639 | 0.5779 | 0.7575 | 0.0081 | 0.8333 |
| 16.3978 | 3.0 | 297 | 9.6624 | 0.4525 | 0.6069 | 0.5171 | 0.1167 | 0.3226 | 0.4676 | 0.5155 | 0.6747 | 0.7306 | 0.3 | 0.5983 | 0.7486 | 0.7497 | 0.8582 | 0.5793 | 0.8108 | 0.0369 | 0.4857 | -1.0 | -1.0 | 0.1842 | 0.6167 | 0.6207 | 0.8124 | 0.5441 | 0.8 |
| 14.6914 | 4.0 | 396 | 9.1117 | 0.4881 | 0.6719 | 0.5648 | 0.025 | 0.4183 | 0.5028 | 0.5307 | 0.7189 | 0.7619 | 0.15 | 0.642 | 0.7877 | 0.7998 | 0.883 | 0.6391 | 0.8147 | 0.093 | 0.7143 | -1.0 | -1.0 | 0.2148 | 0.6014 | 0.6111 | 0.7912 | 0.5706 | 0.7667 |
| 13.587 | 5.0 | 495 | 8.6400 | 0.4979 | 0.6803 | 0.5742 | 0.13 | 0.361 | 0.5183 | 0.5577 | 0.7337 | 0.7692 | 0.45 | 0.629 | 0.7986 | 0.8062 | 0.8908 | 0.6529 | 0.8265 | 0.1603 | 0.6714 | -1.0 | -1.0 | 0.2569 | 0.6472 | 0.6335 | 0.8124 | 0.4775 | 0.7667 |
| 12.472 | 6.0 | 594 | 8.9166 | 0.5336 | 0.7177 | 0.61 | 0.04 | 0.3907 | 0.5568 | 0.5598 | 0.7275 | 0.77 | 0.2 | 0.5852 | 0.8043 | 0.8053 | 0.8823 | 0.6221 | 0.8137 | 0.1712 | 0.7143 | -1.0 | -1.0 | 0.2475 | 0.6028 | 0.6142 | 0.8071 | 0.7411 | 0.8 |
| 11.3489 | 7.0 | 693 | 9.0591 | 0.5186 | 0.6943 | 0.5951 | 0.0014 | 0.4297 | 0.5424 | 0.5712 | 0.7099 | 0.7713 | 0.25 | 0.6119 | 0.8034 | 0.7968 | 0.8745 | 0.6237 | 0.8216 | 0.1237 | 0.6786 | -1.0 | -1.0 | 0.2614 | 0.6139 | 0.6321 | 0.8062 | 0.6738 | 0.8333 |
| 10.5027 | 8.0 | 792 | 9.1905 | 0.5222 | 0.7064 | 0.5981 | 0.0013 | 0.4192 | 0.5439 | 0.5557 | 0.7153 | 0.7746 | 0.2 | 0.5858 | 0.8092 | 0.8037 | 0.8851 | 0.5848 | 0.8039 | 0.2072 | 0.6857 | -1.0 | -1.0 | 0.2512 | 0.6292 | 0.6126 | 0.8106 | 0.6739 | 0.8333 |
| 9.7544 | 9.0 | 891 | 9.2007 | 0.5269 | 0.7186 | 0.6215 | 0.0 | 0.4556 | 0.5493 | 0.573 | 0.7131 | 0.759 | 0.0 | 0.6006 | 0.7926 | 0.8137 | 0.8773 | 0.5771 | 0.7863 | 0.1994 | 0.6643 | -1.0 | -1.0 | 0.2514 | 0.5875 | 0.6119 | 0.8053 | 0.7079 | 0.8333 |
| 9.2386 | 10.0 | 990 | 9.3179 | 0.5199 | 0.7161 | 0.6089 | 0.0028 | 0.4486 | 0.5426 | 0.562 | 0.7123 | 0.7571 | 0.05 | 0.5886 | 0.7925 | 0.8059 | 0.8738 | 0.579 | 0.7961 | 0.1759 | 0.6429 | -1.0 | -1.0 | 0.2393 | 0.5875 | 0.6114 | 0.8088 | 0.708 | 0.8333 |
### Framework versions
- Transformers 4.57.2
- Pytorch 2.9.0+cu126
- Datasets 4.4.1
- Tokenizers 0.22.1
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