---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: convnext-tiny-224-finetuned-eurosat-att-auto
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9506172839506173
---

<!-- 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-att-auto

This model is a fine-tuned version of [facebook/convnext-tiny-224](https://huggingface.co/facebook/convnext-tiny-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5076
- Accuracy: 0.9506

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.5583        | 0.97  | 23   | 1.6008          | 0.7160   |
| 1.2953        | 1.97  | 46   | 1.2957          | 0.7531   |
| 0.9488        | 2.97  | 69   | 1.0720          | 0.8148   |
| 0.7036        | 3.97  | 92   | 0.8965          | 0.8642   |
| 0.5446        | 4.97  | 115  | 0.7574          | 0.9383   |
| 0.4113        | 5.97  | 138  | 0.6522          | 0.9383   |
| 0.2259        | 6.97  | 161  | 0.5720          | 0.9383   |
| 0.1863        | 7.97  | 184  | 0.5076          | 0.9506   |
| 0.1443        | 8.97  | 207  | 0.4795          | 0.9383   |
| 0.1289        | 9.97  | 230  | 0.4685          | 0.9383   |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.7.1
- Tokenizers 0.13.2