---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- image_folder
metrics:
- accuracy
model-index:
- name: vitmae-large-funnydataset
  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: 0.49783549783549785
---

<!-- 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-large-funnydataset

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: nan
- Accuracy: 0.4978

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0           | 0.55  | 100  | nan             | 0.4978   |
| 0.0           | 1.1   | 200  | nan             | 0.4978   |
| 0.0           | 1.66  | 300  | nan             | 0.4978   |
| 0.0           | 2.21  | 400  | nan             | 0.4978   |
| 0.0           | 2.76  | 500  | nan             | 0.4978   |
| 0.0           | 3.31  | 600  | nan             | 0.4978   |
| 0.0           | 3.87  | 700  | nan             | 0.4978   |


### Framework versions

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