---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- image_folder
metrics:
- accuracy
model-index:
- name: vitmae_largeFunny5
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: image_folder
      type: image_folder
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.683083511777302
---

<!-- 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. -->

# vitmae_largeFunny5

This model is a fine-tuned version of [facebook/vit-mae-large](https://huggingface.co/facebook/vit-mae-large) on the image_folder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6622
- Accuracy: 0.6831

## 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: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6984        | 0.52  | 100  | 0.6662          | 0.5974   |
| 0.6214        | 1.04  | 200  | 0.6404          | 0.6081   |
| 0.6203        | 1.56  | 300  | 0.6205          | 0.6638   |
| 0.5689        | 2.08  | 400  | 0.6171          | 0.6745   |
| 0.5278        | 2.6   | 500  | 0.6377          | 0.6788   |
| 0.4602        | 3.12  | 600  | 0.6414          | 0.6895   |
| 0.373         | 3.65  | 700  | 0.6622          | 0.6831   |


### Framework versions

- Transformers 4.30.1
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3