---
library_name: transformers
license: apache-2.0
base_model: PekingU/rtdetr_v2_r18vd
tags:
- generated_from_trainer
model-index:
- name: rt-detr-v2_barcode-detection
  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-detr-v2_barcode-detection

This model is a fine-tuned version of [PekingU/rtdetr_v2_r18vd](https://huggingface.co/PekingU/rtdetr_v2_r18vd) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 5.0340
- Map: 0.6583
- Map 50: 0.8036
- Map 75: 0.7156
- Map Small: 0.2754
- Map Medium: 0.7152
- Map Large: 0.747
- Mar 1: 0.3589
- Mar 10: 0.833
- Mar 100: 0.8673
- Mar Small: 0.6183
- Mar Medium: 0.8656
- Mar Large: 0.8872
- Map Barcode: 0.6583
- Mar 100 Barcode: 0.8673

## 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: 16
- 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_steps: 300
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Map    | Map 50 | Map 75 | Map Barcode | Map Large | Map Medium | Map Small | Mar 1  | Mar 10 | Mar 100 | Mar 100 Barcode | Mar Large | Mar Medium | Mar Small |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:-----------:|:---------:|:----------:|:---------:|:------:|:------:|:-------:|:---------------:|:---------:|:----------:|:---------:|
| 7.43          | 1.0   | 1636  | 5.0547          | 0.623  | 0.7756 | 0.6841 | 0.623       | 0.6594    | 0.6674     | 0.2648    | 0.3542 | 0.8117 | 0.8521  | 0.8521          | 0.8749    | 0.8552     | 0.5325    |
| 6.9538        | 2.0   | 3272  | 4.9508          | 0.6297 | 0.7829 | 0.6878 | 0.6297      | 0.7109    | 0.6449     | 0.261     | 0.3612 | 0.8238 | 0.8604  | 0.8604          | 0.8794    | 0.8624     | 0.5972    |
| 6.6733        | 3.0   | 4908  | 5.0056          | 0.6553 | 0.8073 | 0.7122 | 0.6553      | 0.7359    | 0.6782     | 0.2319    | 0.3481 | 0.8201 | 0.8542  | 0.8542          | 0.8712    | 0.8573     | 0.6107    |
| 6.5783        | 4.0   | 6544  | 5.0493          | 0.6524 | 0.808  | 0.711  | 0.6524      | 0.7472    | 0.6782     | 0.2391    | 0.3581 | 0.8268 | 0.8629  | 0.8629          | 0.8819    | 0.8639     | 0.6066    |
| 6.4986        | 5.0   | 8180  | 5.0208          | 0.6944 | 0.8578 | 0.7542 | 0.6944      | 0.7651    | 0.7135     | 0.2808    | 0.3706 | 0.8307 | 0.8611  | 0.8611          | 0.879     | 0.863      | 0.6131    |
| 6.4056        | 6.0   | 9816  | 5.0116          | 0.6843 | 0.8399 | 0.7445 | 0.6843      | 0.7607    | 0.7126     | 0.3026    | 0.371  | 0.8374 | 0.8664  | 0.8664          | 0.8864    | 0.8646     | 0.6176    |
| 6.4074        | 7.0   | 11452 | 5.0229          | 0.653  | 0.7989 | 0.7106 | 0.2768      | 0.7112    | 0.731      | 0.3513    | 0.8326 | 0.8694 | 0.619   | 0.8675          | 0.8896    | 0.653      | 0.8694    |
| 6.2576        | 8.0   | 13088 | 5.0340          | 0.6583 | 0.8036 | 0.7156 | 0.2754      | 0.7152    | 0.747      | 0.3589    | 0.833  | 0.8673 | 0.6183  | 0.8656          | 0.8872    | 0.6583     | 0.8673    |


### Framework versions

- Transformers 4.57.3
- Pytorch 2.9.0+cu126
- Datasets 4.4.2
- Tokenizers 0.22.1