---
license: apache-2.0
base_model: WKLI22/detr-resnet-50_finetuned_cppe5
tags:
- generated_from_trainer
model-index:
- name: detr-resnet-50_finetuned_cppe5
  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-resnet-50_finetuned_cppe5

This model is a fine-tuned version of [WKLI22/detr-resnet-50_finetuned_cppe5](https://huggingface.co/WKLI22/detr-resnet-50_finetuned_cppe5) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4986

## 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: 17
- eval_batch_size: 17
- seed: 42
- gradient_accumulation_steps: 6
- total_train_batch_size: 102
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.4724        | 0.07  | 2    | 0.5355          |
| 0.4907        | 0.14  | 4    | 0.5277          |
| 0.498         | 0.21  | 6    | 0.5214          |
| 0.534         | 0.28  | 8    | 0.5274          |
| 0.5305        | 0.36  | 10   | 0.5294          |
| 0.5096        | 0.43  | 12   | 0.5273          |
| 0.5149        | 0.5   | 14   | 0.5158          |
| 0.5099        | 0.57  | 16   | 0.5163          |
| 0.5308        | 0.64  | 18   | 0.5217          |
| 0.5164        | 0.71  | 20   | 0.5076          |
| 0.4932        | 0.78  | 22   | 0.5050          |
| 0.5151        | 0.85  | 24   | 0.5102          |
| 0.4982        | 0.92  | 26   | 0.5044          |
| 0.526         | 0.99  | 28   | 0.5096          |
| 0.5034        | 1.07  | 30   | 0.4980          |
| 0.5155        | 1.14  | 32   | 0.5067          |
| 0.513         | 1.21  | 34   | 0.5011          |
| 0.5019        | 1.28  | 36   | 0.5066          |
| 0.4704        | 1.35  | 38   | 0.5094          |
| 0.5404        | 1.42  | 40   | 0.5126          |
| 0.5263        | 1.49  | 42   | 0.5062          |
| 0.4729        | 1.56  | 44   | 0.5223          |
| 0.5032        | 1.63  | 46   | 0.5073          |
| 0.476         | 1.7   | 48   | 0.5111          |
| 0.4823        | 1.78  | 50   | 0.5094          |
| 0.5223        | 1.85  | 52   | 0.5042          |
| 0.4855        | 1.92  | 54   | 0.4962          |
| 0.5038        | 1.99  | 56   | 0.5006          |
| 0.5196        | 2.06  | 58   | 0.5022          |
| 0.4847        | 2.13  | 60   | 0.4943          |
| 0.4697        | 2.2   | 62   | 0.5007          |
| 0.4893        | 2.27  | 64   | 0.5041          |
| 0.4939        | 2.34  | 66   | 0.4910          |
| 0.5093        | 2.41  | 68   | 0.4974          |
| 0.4884        | 2.49  | 70   | 0.4962          |
| 0.5087        | 2.56  | 72   | 0.5081          |
| 0.4889        | 2.63  | 74   | 0.4974          |
| 0.486         | 2.7   | 76   | 0.5003          |
| 0.4747        | 2.77  | 78   | 0.4917          |
| 0.5028        | 2.84  | 80   | 0.4849          |
| 0.5366        | 2.91  | 82   | 0.4931          |
| 0.5083        | 2.98  | 84   | 0.4986          |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2