---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: convnextv2-base-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: 0.9146968139773896
---

<!-- 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-base-22k-224-finetuned-eurosat-50

This model is a fine-tuned version of [facebook/convnextv2-base-22k-224](https://huggingface.co/facebook/convnextv2-base-22k-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2875
- Accuracy: 0.9147

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.9019        | 1.0   | 122  | 1.9510          | 0.1727   |
| 1.7782        | 2.0   | 244  | 1.8239          | 0.3073   |
| 1.6214        | 3.0   | 366  | 1.6121          | 0.4913   |
| 1.3495        | 4.0   | 488  | 1.3064          | 0.6238   |
| 1.0994        | 5.0   | 610  | 1.0243          | 0.7163   |
| 0.8866        | 6.0   | 732  | 0.8165          | 0.7564   |
| 0.7282        | 7.0   | 854  | 0.6637          | 0.7996   |
| 0.6211        | 8.0   | 976  | 0.5623          | 0.8160   |
| 0.5114        | 9.0   | 1098 | 0.4681          | 0.8551   |
| 0.3835        | 10.0  | 1220 | 0.3917          | 0.8787   |
| 0.3543        | 11.0  | 1342 | 0.3122          | 0.9013   |
| 0.3534        | 12.0  | 1464 | 0.2875          | 0.9147   |


### Framework versions

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