---
license: apache-2.0
base_model: qgyd2021/detr_cppe5_object_detection
tags:
- generated_from_trainer
datasets:
- cppe5
model-index:
- name: detr_cppe5_object_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. -->

# detr_cppe5_object_detection

This model is a fine-tuned version of [qgyd2021/detr_cppe5_object_detection](https://huggingface.co/qgyd2021/detr_cppe5_object_detection) on the cppe5 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1300

## 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 16
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.8224        | 3.17  | 200  | 1.0183          |
| 0.8185        | 6.35  | 400  | 1.0975          |
| 0.7584        | 9.52  | 600  | 1.0917          |
| 0.7272        | 12.7  | 800  | 1.0980          |
| 0.7481        | 15.87 | 1000 | 1.1201          |
| 0.7586        | 19.05 | 1200 | 1.1300          |


### Framework versions

- Transformers 4.33.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3