---
license: apache-2.0
tags:
- image-classification
- vision
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: moon-detector-v5
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9949622166246851
---

<!-- 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. -->

# moon-detector-v5

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0238
- Accuracy: 0.9950

## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 1337
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0548        | 1.0   | 281  | 0.0616          | 0.9798   |
| 0.1366        | 2.0   | 562  | 0.0340          | 0.9899   |
| 0.0218        | 3.0   | 843  | 0.0430          | 0.9874   |
| 0.0403        | 4.0   | 1124 | 0.0406          | 0.9874   |
| 0.0184        | 5.0   | 1405 | 0.0238          | 0.9950   |


### Framework versions

- Transformers 4.30.0.dev0
- Pytorch 2.0.1+cpu
- Datasets 2.12.0
- Tokenizers 0.13.3