---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: convnextv2-tiny-22k-224-finetuned-eurosat-50
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: Augmented-Final
      split: train
      args: Augmented-Final
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8273381294964028
---

<!-- 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. -->

# convnextv2-tiny-22k-224-finetuned-eurosat-50

This model is a fine-tuned version of [facebook/convnextv2-tiny-22k-224](https://huggingface.co/facebook/convnextv2-tiny-22k-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5332
- Accuracy: 0.8273

## 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-06
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.9
- num_epochs: 12

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.0127        | 1.0   | 122  | 1.9838          | 0.1942   |
| 1.8499        | 2.0   | 244  | 1.8667          | 0.2456   |
| 1.8024        | 3.0   | 366  | 1.7247          | 0.3792   |
| 1.5952        | 4.0   | 488  | 1.5540          | 0.4861   |
| 1.3867        | 5.0   | 610  | 1.3568          | 0.5550   |
| 1.1846        | 6.0   | 732  | 1.1521          | 0.6372   |
| 1.0063        | 7.0   | 854  | 0.9649          | 0.6824   |
| 0.8932        | 8.0   | 976  | 0.8284          | 0.7307   |
| 0.7576        | 9.0   | 1098 | 0.7217          | 0.7780   |
| 0.6742        | 10.0  | 1220 | 0.6412          | 0.7924   |
| 0.6398        | 11.0  | 1342 | 0.5679          | 0.8160   |
| 0.6243        | 12.0  | 1464 | 0.5332          | 0.8273   |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3