---
license: apache-2.0
base_model: facebook/detr-resnet-101
tags:
- generated_from_trainer
datasets:
- imagefolder
model-index:
- name: detr-resnet-101_adafactor_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. -->

# detr-resnet-101_adafactor_finetuned_food-roboflow

This model is a fine-tuned version of [facebook/detr-resnet-101](https://huggingface.co/facebook/detr-resnet-101) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 3.1003

## 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: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 6.5311        | 0.77  | 50   | 6.4188          |
| 5.6597        | 1.54  | 100  | 5.8132          |
| 5.1568        | 2.31  | 150  | 5.1265          |
| 4.4672        | 3.08  | 200  | 4.3264          |
| 3.8033        | 3.85  | 250  | 3.9444          |
| 3.2053        | 4.62  | 300  | 3.6319          |
| 3.127         | 5.38  | 350  | 3.3079          |
| 2.9082        | 6.15  | 400  | 3.1760          |
| 2.8546        | 6.92  | 450  | 3.1659          |
| 2.8393        | 7.69  | 500  | 3.0233          |
| 2.6973        | 8.46  | 550  | 3.0817          |
| 2.7047        | 9.23  | 600  | 3.0849          |
| 2.673         | 10.0  | 650  | 3.1122          |
| 2.6781        | 10.77 | 700  | 3.0709          |
| 2.5901        | 11.54 | 750  | 3.0382          |
| 2.6568        | 12.31 | 800  | 3.0246          |
| 2.5929        | 13.08 | 850  | 3.0384          |
| 2.5709        | 13.85 | 900  | 2.9862          |
| 2.5784        | 14.62 | 950  | 3.1003          |


### Framework versions

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