---
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: 15.7596
- Map: 0.243
- Map 50: 0.4016
- Map 75: 0.2288
- Map Small: 0.1622
- Map Medium: 0.1679
- Map Large: 0.4047
- Mar 1: 0.2498
- Mar 10: 0.5329
- Mar 100: 0.6054
- Mar Small: 0.4114
- Mar Medium: 0.5602
- Mar Large: 0.781
- Map Coverall: 0.4109
- Mar 100 Coverall: 0.7821
- Map Face Shield: 0.1194
- Mar 100 Face Shield: 0.6471
- Map Gloves: 0.2443
- Mar 100 Gloves: 0.4508
- Map Goggles: 0.065
- Mar 100 Goggles: 0.4586
- Map Mask: 0.3754
- Mar 100 Mask: 0.6882

## 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: 2

### 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 Coverall | Mar 100 Coverall | Map Face Shield | Mar 100 Face Shield | Map Gloves | Mar 100 Gloves | Map Goggles | Mar 100 Goggles | Map Mask | Mar 100 Mask |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:----------:|:---------:|:------:|:------:|:-------:|:---------:|:----------:|:---------:|:------------:|:----------------:|:---------------:|:-------------------:|:----------:|:--------------:|:-----------:|:---------------:|:--------:|:------------:|
| No log        | 1.0   | 107  | 35.1046         | 0.0395 | 0.0911 | 0.0256 | 0.0015    | 0.0104     | 0.0475    | 0.0733 | 0.1851 | 0.2494  | 0.0421    | 0.1906     | 0.365     | 0.1668       | 0.5491           | 0.0207          | 0.2278              | 0.0068     | 0.1759         | 0.0007      | 0.0877          | 0.0024   | 0.2062       |
| No log        | 2.0   | 214  | 18.0639         | 0.1779 | 0.3283 | 0.1719 | 0.0679    | 0.1        | 0.2844    | 0.2053 | 0.4086 | 0.4734  | 0.2576    | 0.3816     | 0.7174    | 0.4958       | 0.7032           | 0.0485          | 0.4873              | 0.1107     | 0.3246         | 0.0257      | 0.3754          | 0.2086   | 0.4764       |


### Framework versions

- Transformers 4.50.0.dev0
- Pytorch 2.6.0+cu124
- Datasets 3.4.1
- Tokenizers 0.21.1