---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: convnext-large-224-finetuned-eurosat
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: mio_Dataset2
      split: validation
      args: mio_Dataset2
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.7485380116959064
---

<!-- 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-large-224-finetuned-eurosat

This model is a fine-tuned version of [facebook/convnext-large-224](https://huggingface.co/facebook/convnext-large-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6440
- Accuracy: 0.7485

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- 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: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 19   | 1.0763          | 0.4386   |
| No log        | 2.0   | 38   | 0.9918          | 0.5322   |
| No log        | 3.0   | 57   | 0.8919          | 0.6725   |
| No log        | 4.0   | 76   | 0.8088          | 0.7135   |
| No log        | 5.0   | 95   | 0.7502          | 0.7368   |
| No log        | 6.0   | 114  | 0.7037          | 0.7310   |
| No log        | 7.0   | 133  | 0.6792          | 0.7427   |
| No log        | 8.0   | 152  | 0.6507          | 0.7368   |
| No log        | 9.0   | 171  | 0.6440          | 0.7485   |
| No log        | 10.0  | 190  | 0.6415          | 0.7485   |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3