---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- image_folder
metrics:
- accuracy
base_model: facebook/convnext-tiny-224
model-index:
- name: convnext-tiny-224-finetuned-eurosat-albumentations
  results:
  - task:
      type: image-classification
      name: Image Classification
    dataset:
      name: image_folder
      type: image_folder
      args: default
    metrics:
    - type: accuracy
      value: 0.9748148148148148
      name: Accuracy
---

<!-- 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. -->

# convnext-tiny-224-finetuned-eurosat-albumentations

This model is a fine-tuned version of [facebook/convnext-tiny-224](https://huggingface.co/facebook/convnext-tiny-224) on the image_folder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0727
- Accuracy: 0.9748

## 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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.141         | 1.0   | 190  | 0.1496          | 0.9544   |
| 0.0736        | 2.0   | 380  | 0.0958          | 0.9719   |
| 0.0568        | 3.0   | 570  | 0.0727          | 0.9748   |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.10.0+cu111
- Datasets 2.0.0
- Tokenizers 0.11.6