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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: 9.5442
- Map: 0.4922
- Map 50: 0.6651
- Map 75: 0.5738
- Map Small: 0.0437
- Map Medium: 0.2434
- Map Large: 0.5161
- Mar 1: 0.5643
- Mar 10: 0.7132
- Mar 100: 0.784
- Mar Small: 0.35
- Mar Medium: 0.5574
- Mar Large: 0.8171
- Map Bin: 0.7493
- Mar 100 Bin: 0.9121
- Map Hand: 0.6106
- Mar 100 Hand: 0.8304
- Map Not Bin: 0.1567
- Mar 100 Not Bin: 0.6857
- Map Not Hand: -1.0
- Mar 100 Not Hand: -1.0
- Map Not Trash: 0.2247
- Mar 100 Not Trash: 0.6514
- Map Trash: 0.6532
- Mar 100 Trash: 0.7912
- Map Trash Arm: 0.5585
- Mar 100 Trash Arm: 0.8333
## 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: 16
- 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_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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:----------:|:---------:|:------:|:------:|:-------:|:---------:|:----------:|:---------:|:-------:|:-----------:|:--------:|:------------:|:-----------:|:---------------:|:------------:|:----------------:|:-------------:|:-----------------:|:---------:|:-------------:|:-------------:|:-----------------:|
| 67.0877 | 1.0 | 50 | 19.3209 | 0.1877 | 0.2836 | 0.2027 | 0.0 | 0.0275 | 0.1918 | 0.2507 | 0.386 | 0.461 | 0.0 | 0.2591 | 0.491 | 0.5792 | 0.8638 | 0.4197 | 0.7284 | 0.0003 | 0.1357 | -1.0 | -1.0 | 0.0082 | 0.3806 | 0.1191 | 0.6575 | 0.0 | 0.0 |
| 25.8229 | 2.0 | 100 | 11.8619 | 0.4038 | 0.5531 | 0.4491 | 0.0125 | 0.1542 | 0.4196 | 0.4788 | 0.6431 | 0.7361 | 0.05 | 0.55 | 0.7718 | 0.6978 | 0.9028 | 0.6071 | 0.8353 | 0.0384 | 0.6357 | -1.0 | -1.0 | 0.1366 | 0.5569 | 0.5997 | 0.7858 | 0.3432 | 0.7 |
| 18.4735 | 3.0 | 150 | 10.5653 | 0.4672 | 0.6372 | 0.4977 | 0.075 | 0.1303 | 0.4887 | 0.5061 | 0.6781 | 0.7422 | 0.15 | 0.5006 | 0.7848 | 0.7205 | 0.8993 | 0.5618 | 0.801 | 0.1122 | 0.6571 | -1.0 | -1.0 | 0.1551 | 0.5861 | 0.6429 | 0.7761 | 0.6109 | 0.7333 |
| 16.1638 | 4.0 | 200 | 9.9060 | 0.5041 | 0.6605 | 0.5598 | 0.325 | 0.2294 | 0.528 | 0.5501 | 0.7139 | 0.7795 | 0.4 | 0.5562 | 0.818 | 0.748 | 0.9071 | 0.6237 | 0.8294 | 0.13 | 0.6286 | -1.0 | -1.0 | 0.1967 | 0.5958 | 0.6512 | 0.8159 | 0.675 | 0.9 |
| 14.7136 | 5.0 | 250 | 9.9183 | 0.4965 | 0.6616 | 0.5754 | 0.1583 | 0.1233 | 0.5236 | 0.5357 | 0.7272 | 0.7758 | 0.35 | 0.4563 | 0.8224 | 0.7495 | 0.9043 | 0.6082 | 0.8284 | 0.1446 | 0.6571 | -1.0 | -1.0 | 0.2102 | 0.6069 | 0.6404 | 0.7912 | 0.6261 | 0.8667 |
| 13.5916 | 6.0 | 300 | 9.7900 | 0.4673 | 0.648 | 0.5194 | 0.0836 | 0.1523 | 0.4919 | 0.5113 | 0.7207 | 0.7754 | 0.4 | 0.5989 | 0.8027 | 0.7366 | 0.9078 | 0.5901 | 0.8284 | 0.1261 | 0.6714 | -1.0 | -1.0 | 0.2205 | 0.65 | 0.6566 | 0.7947 | 0.4737 | 0.8 |
| 12.7902 | 7.0 | 350 | 9.6513 | 0.4951 | 0.6667 | 0.5719 | 0.31 | 0.1765 | 0.5194 | 0.5423 | 0.7193 | 0.7883 | 0.35 | 0.5205 | 0.821 | 0.7423 | 0.9085 | 0.6048 | 0.8284 | 0.1127 | 0.6357 | -1.0 | -1.0 | 0.2368 | 0.6222 | 0.6626 | 0.8018 | 0.6116 | 0.9333 |
| 12.0119 | 8.0 | 400 | 9.4572 | 0.4887 | 0.6694 | 0.5403 | 0.1214 | 0.2586 | 0.5161 | 0.5487 | 0.7362 | 0.7912 | 0.35 | 0.5631 | 0.8232 | 0.7694 | 0.9071 | 0.6146 | 0.8373 | 0.1538 | 0.6929 | -1.0 | -1.0 | 0.2326 | 0.6361 | 0.6609 | 0.8071 | 0.5008 | 0.8667 |
| 11.3795 | 9.0 | 450 | 9.6143 | 0.4856 | 0.6607 | 0.5713 | 0.0488 | 0.2222 | 0.5081 | 0.5622 | 0.6976 | 0.7705 | 0.3 | 0.5205 | 0.8049 | 0.7433 | 0.8993 | 0.6103 | 0.8333 | 0.1385 | 0.6714 | -1.0 | -1.0 | 0.2177 | 0.6347 | 0.6453 | 0.7841 | 0.5585 | 0.8 |
| 11.0061 | 10.0 | 500 | 9.5442 | 0.4922 | 0.6651 | 0.5738 | 0.0437 | 0.2434 | 0.5161 | 0.5643 | 0.7132 | 0.784 | 0.35 | 0.5574 | 0.8171 | 0.7493 | 0.9121 | 0.6106 | 0.8304 | 0.1567 | 0.6857 | -1.0 | -1.0 | 0.2247 | 0.6514 | 0.6532 | 0.7912 | 0.5585 | 0.8333 |
### Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1
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