---
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: 11.9610
- Map: 0.3649
- Map 50: 0.6413
- Map 75: 0.3314
- Map Small: 0.3681
- Map Medium: 0.3514
- Map Large: 0.5909
- Mar 1: 0.315
- Mar 10: 0.5779
- Mar 100: 0.6508
- Mar Small: 0.4932
- Mar Medium: 0.5762
- Mar Large: 0.784
- Map Coverall: 0.5504
- Mar 100 Coverall: 0.8538
- Map Face Shield: 0.3497
- Mar 100 Face Shield: 0.7471
- Map Gloves: 0.2505
- Mar 100 Gloves: 0.4915
- Map Goggles: 0.2357
- Mar 100 Goggles: 0.5655
- Map Mask: 0.4385
- Mar 100 Mask: 0.5961

## 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: 5

### 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  | 55.3917         | 0.0232 | 0.0485 | 0.0213 | 0.0       | 0.0062     | 0.0249    | 0.04   | 0.0855 | 0.0943  | 0.0       | 0.0516     | 0.1121    | 0.1087       | 0.3068           | 0.0004          | 0.0519              | 0.0001     | 0.0085         | 0.0         | 0.0277          | 0.0069   | 0.0769       |
| No log        | 2.0   | 214  | 28.9185         | 0.1144 | 0.2063 | 0.1092 | 0.0122    | 0.0769     | 0.1746    | 0.1466 | 0.267  | 0.2858  | 0.0174    | 0.2233     | 0.5011    | 0.3659       | 0.6144           | 0.0255          | 0.238               | 0.0138     | 0.1277         | 0.0502      | 0.2092          | 0.1164   | 0.2396       |
| No log        | 3.0   | 321  | 19.5631         | 0.1944 | 0.363  | 0.1809 | 0.1027    | 0.1483     | 0.2848    | 0.2424 | 0.4058 | 0.4504  | 0.2156    | 0.4032     | 0.654     | 0.4834       | 0.6883           | 0.0884          | 0.4747              | 0.0624     | 0.2429         | 0.0624      | 0.3692          | 0.2753   | 0.4769       |
| No log        | 4.0   | 428  | 15.2810         | 0.2345 | 0.4587 | 0.2098 | 0.1045    | 0.1855     | 0.4544    | 0.2525 | 0.4567 | 0.5091  | 0.2361    | 0.4726     | 0.734     | 0.551        | 0.7279           | 0.1186          | 0.543               | 0.1237     | 0.417          | 0.1106      | 0.3846          | 0.2685   | 0.4729       |
| 55.6421       | 5.0   | 535  | 14.7773         | 0.2391 | 0.4678 | 0.2144 | 0.0671    | 0.1875     | 0.447     | 0.2633 | 0.4649 | 0.5141  | 0.2299    | 0.4817     | 0.7456    | 0.5519       | 0.7369           | 0.1398          | 0.5443              | 0.114      | 0.3906         | 0.1052      | 0.4262          | 0.2844   | 0.4724       |


### Framework versions

- Transformers 4.50.0.dev0
- Pytorch 2.6.0+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0