---
license: apache-2.0
base_model: facebook/detr-resnet-101
tags:
- generated_from_trainer
datasets:
- imagefolder
model-index:
- name: detr-resnet-101_rmsprop_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_rmsprop_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: 2.9853

## 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: 4
- 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 5.8836        | 0.77  | 50   | 4.5609          |
| 3.9193        | 1.54  | 100  | 3.5764          |
| 3.2186        | 2.31  | 150  | 3.2685          |
| 2.8952        | 3.08  | 200  | 3.1941          |
| 2.8565        | 3.85  | 250  | 3.1280          |
| 2.7563        | 4.62  | 300  | 3.0448          |
| 2.668         | 5.38  | 350  | 3.0325          |
| 2.6474        | 6.15  | 400  | 2.9764          |
| 2.6463        | 6.92  | 450  | 2.9752          |
| 2.6616        | 7.69  | 500  | 3.0352          |
| 2.5155        | 8.46  | 550  | 2.9928          |
| 2.5778        | 9.23  | 600  | 2.9603          |
| 2.5876        | 10.0  | 650  | 2.9502          |
| 2.513         | 10.77 | 700  | 3.0151          |
| 2.5598        | 11.54 | 750  | 3.0011          |
| 2.491         | 12.31 | 800  | 3.0134          |
| 2.5103        | 13.08 | 850  | 2.9825          |
| 2.5497        | 13.85 | 900  | 3.0169          |
| 2.5738        | 14.62 | 950  | 2.9853          |


### Framework versions

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