---
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:
- eval_loss: 6.5817
- eval_map: 0.6377
- eval_map_50: 0.9261
- eval_map_75: 0.7461
- eval_map_small: 0.5601
- eval_map_medium: 0.781
- eval_map_large: 0.7309
- eval_mar_1: 0.235
- eval_mar_10: 0.5687
- eval_mar_100: 0.7408
- eval_mar_small: 0.6721
- eval_mar_medium: 0.855
- eval_mar_large: 0.8479
- eval_map_checked-unchecked: -1.0
- eval_mar_100_checked-unchecked: -1.0
- eval_map_checked: 0.6635
- eval_mar_100_checked: 0.7876
- eval_map_unchecked: 0.6118
- eval_mar_100_unchecked: 0.694
- eval_runtime: 7.4046
- eval_samples_per_second: 17.151
- eval_steps_per_second: 2.161
- epoch: 11.0
- step: 990

## 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_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: 40

### Framework versions

- Transformers 4.56.0
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.0