---
license: apache-2.0
base_model: microsoft/conditional-detr-resnet-50
tags:
- generated_from_trainer
datasets:
- imagefolder
model-index:
- name: conditional-detr-resnet-50_adamw_hf_finetuned_food-roboflow
  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. -->

# conditional-detr-resnet-50_adamw_hf_finetuned_food-roboflow

This model is a fine-tuned version of [microsoft/conditional-detr-resnet-50](https://huggingface.co/microsoft/conditional-detr-resnet-50) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 10.2661

## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 4448.7409     | 0.77  | 50   | 2784.9878       |
| 2312.7831     | 1.54  | 100  | 1275.4084       |
| 1139.5262     | 2.31  | 150  | 825.0410        |
| 857.6314      | 3.08  | 200  | 626.2924        |
| 630.5604      | 3.85  | 250  | 492.9028        |
| 518.8461      | 4.62  | 300  | 391.5704        |
| 418.3785      | 5.38  | 350  | 312.8008        |
| 331.9224      | 6.15  | 400  | 250.7763        |
| 261.2112      | 6.92  | 450  | 201.8681        |
| 207.421       | 7.69  | 500  | 163.3361        |
| 172.0157      | 8.46  | 550  | 132.3763        |
| 140.2059      | 9.23  | 600  | 108.1960        |
| 110.3696      | 10.0  | 650  | 89.2497         |
| 95.9428       | 10.77 | 700  | 73.2426         |
| 78.812        | 11.54 | 750  | 61.4362         |
| 64.1493       | 12.31 | 800  | 51.2599         |
| 56.184        | 13.08 | 850  | 43.4741         |
| 46.7644       | 13.85 | 900  | 37.4028         |
| 38.1726       | 14.62 | 950  | 32.6764         |
| 34.7277       | 15.38 | 1000 | 28.1207         |
| 29.9978       | 16.15 | 1050 | 25.0045         |
| 27.5957       | 16.92 | 1100 | 22.3012         |
| 23.6549       | 17.69 | 1150 | 19.9766         |
| 21.4961       | 18.46 | 1200 | 18.2427         |
| 19.3312       | 19.23 | 1250 | 16.8829         |
| 17.8215       | 20.0  | 1300 | 15.5794         |
| 16.2877       | 20.77 | 1350 | 14.5258         |
| 16.0017       | 21.54 | 1400 | 13.5888         |
| 14.6977       | 22.31 | 1450 | 13.0312         |
| 13.9111       | 23.08 | 1500 | 12.4389         |
| 13.5826       | 23.85 | 1550 | 11.8718         |
| 12.5621       | 24.62 | 1600 | 11.6370         |
| 12.1993       | 25.38 | 1650 | 11.1523         |
| 12.2491       | 26.15 | 1700 | 10.8586         |
| 11.5879       | 26.92 | 1750 | 10.6795         |
| 11.4736       | 27.69 | 1800 | 10.5273         |
| 11.5405       | 28.46 | 1850 | 10.4190         |
| 11.5894       | 29.23 | 1900 | 10.3225         |
| 11.0308       | 30.0  | 1950 | 10.2661         |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1