---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- image_folder
metrics:
- accuracy
model-index:
- name: vit-base-patch16-224-in21k-finetuned-eurosat
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: image_folder
      type: image_folder
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9016949152542373
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# vit-base-patch16-224-in21k-finetuned-eurosat

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 image_folder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3648
- Accuracy: 0.9017

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.91  | 5    | 0.5982          | 0.7492   |
| 0.645         | 1.91  | 10   | 0.4862          | 0.7593   |
| 0.645         | 2.91  | 15   | 0.4191          | 0.7966   |
| 0.465         | 3.91  | 20   | 0.3803          | 0.8780   |
| 0.465         | 4.91  | 25   | 0.3648          | 0.9017   |


### Framework versions

- Transformers 4.17.0
- Pytorch 1.11.0+cpu
- Datasets 2.2.0
- Tokenizers 0.12.1