---
library_name: transformers
license: apache-2.0
base_model: microsoft/conditional-detr-resnet-50
tags:
- generated_from_trainer
model-index:
- name: detr-cppe5-ppe-detector
  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-ppe-detector

This model is a fine-tuned version of [microsoft/conditional-detr-resnet-50](https://huggingface.co/microsoft/conditional-detr-resnet-50) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1687

## 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: cosine
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 1.0   | 106  | 1.9109          |
| No log        | 2.0   | 212  | 1.7408          |
| No log        | 3.0   | 318  | 1.7527          |
| No log        | 4.0   | 424  | 1.5295          |
| 3.5859        | 5.0   | 530  | 1.5355          |
| 3.5859        | 6.0   | 636  | 1.5048          |
| 3.5859        | 7.0   | 742  | 1.4679          |
| 3.5859        | 8.0   | 848  | 1.4037          |
| 3.5859        | 9.0   | 954  | 1.4161          |
| 1.3248        | 10.0  | 1060 | 1.3470          |
| 1.3248        | 11.0  | 1166 | 1.3197          |
| 1.3248        | 12.0  | 1272 | 1.3047          |
| 1.3248        | 13.0  | 1378 | 1.3000          |
| 1.3248        | 14.0  | 1484 | 1.2670          |
| 1.1606        | 15.0  | 1590 | 1.2603          |
| 1.1606        | 16.0  | 1696 | 1.2669          |
| 1.1606        | 17.0  | 1802 | 1.2255          |
| 1.1606        | 18.0  | 1908 | 1.2329          |
| 1.0363        | 19.0  | 2014 | 1.1964          |
| 1.0363        | 20.0  | 2120 | 1.1991          |
| 1.0363        | 21.0  | 2226 | 1.1966          |
| 1.0363        | 22.0  | 2332 | 1.1834          |
| 1.0363        | 23.0  | 2438 | 1.1747          |
| 0.938         | 24.0  | 2544 | 1.1785          |
| 0.938         | 25.0  | 2650 | 1.1752          |
| 0.938         | 26.0  | 2756 | 1.1718          |
| 0.938         | 27.0  | 2862 | 1.1747          |
| 0.938         | 28.0  | 2968 | 1.1736          |
| 0.8943        | 29.0  | 3074 | 1.1734          |
| 0.8943        | 30.0  | 3180 | 1.1687          |


### Framework versions

- Transformers 4.49.0
- Pytorch 2.11.0+cu128
- Datasets 2.21.0
- Tokenizers 0.21.4