---
license: apache-2.0
base_model: microsoft/resnet-50
tags:
- image-classification
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: camera-type
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: validation
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9382716049382716
---

<!-- 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. -->

# camera-type

This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1654
- Accuracy: 0.9383

## 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: 0.0001
- train_batch_size: 10
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4597        | 0.5   | 200  | 0.2801          | 0.9242   |
| 0.1375        | 0.99  | 400  | 0.1654          | 0.9383   |
| 0.0795        | 1.49  | 600  | 0.1904          | 0.9383   |
| 0.0686        | 1.98  | 800  | 0.1810          | 0.9453   |
| 0.026         | 2.48  | 1000 | 0.2216          | 0.9400   |
| 0.0495        | 2.97  | 1200 | 0.2096          | 0.9453   |
| 0.0487        | 3.47  | 1400 | 0.2174          | 0.9436   |
| 0.0268        | 3.96  | 1600 | 0.2304          | 0.9453   |
| 0.0254        | 4.46  | 1800 | 0.2574          | 0.9400   |
| 0.0186        | 4.95  | 2000 | 0.3212          | 0.9383   |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3