---
library_name: transformers
license: apache-2.0
base_model: microsoft/conditional-detr-resnet-50
tags:
- generated_from_trainer
model-index:
- name: detr_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_finetuned_cppe5

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: 1.1909

## 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: cosine
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 1.0   | 107  | 1.9270          |
| No log        | 2.0   | 214  | 1.7725          |
| No log        | 3.0   | 321  | 1.6696          |
| No log        | 4.0   | 428  | 1.6196          |
| 2.6515        | 5.0   | 535  | 1.5855          |
| 2.6515        | 6.0   | 642  | 1.5091          |
| 2.6515        | 7.0   | 749  | 1.4790          |
| 2.6515        | 8.0   | 856  | 1.4786          |
| 2.6515        | 9.0   | 963  | 1.3819          |
| 1.3311        | 10.0  | 1070 | 1.3668          |
| 1.3311        | 11.0  | 1177 | 1.3966          |
| 1.3311        | 12.0  | 1284 | 1.3492          |
| 1.3311        | 13.0  | 1391 | 1.3223          |
| 1.3311        | 14.0  | 1498 | 1.2781          |
| 1.1672        | 15.0  | 1605 | 1.2749          |
| 1.1672        | 16.0  | 1712 | 1.2671          |
| 1.1672        | 17.0  | 1819 | 1.2488          |
| 1.1672        | 18.0  | 1926 | 1.2500          |
| 1.0429        | 19.0  | 2033 | 1.2274          |
| 1.0429        | 20.0  | 2140 | 1.2308          |
| 1.0429        | 21.0  | 2247 | 1.2249          |
| 1.0429        | 22.0  | 2354 | 1.2157          |
| 1.0429        | 23.0  | 2461 | 1.2147          |
| 0.9595        | 24.0  | 2568 | 1.1956          |
| 0.9595        | 25.0  | 2675 | 1.1880          |
| 0.9595        | 26.0  | 2782 | 1.1912          |
| 0.9595        | 27.0  | 2889 | 1.1916          |
| 0.9595        | 28.0  | 2996 | 1.1921          |
| 0.9097        | 29.0  | 3103 | 1.1912          |
| 0.9097        | 30.0  | 3210 | 1.1909          |


### Framework versions

- Transformers 4.56.2
- Pytorch 2.8.0
- Datasets 4.1.1
- Tokenizers 0.22.1