---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: convnext-tiny-224-finetuned-eurosat-albumentations
  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: 0.0
---

<!-- 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 [paom/convnext-tiny-224-finetuned-eurosat-albumentations](https://huggingface.co/paom/convnext-tiny-224-finetuned-eurosat-albumentations) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6948
- Accuracy: 0.0

## 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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 1    | 0.6948          | 0.0      |
| No log        | 2.0   | 2    | 0.5057          | 0.0      |
| No log        | 3.0   | 3    | 0.2286          | 0.0      |
| No log        | 4.0   | 4    | 0.0823          | 0.0      |
| No log        | 5.0   | 5    | 0.0320          | 0.0      |
| No log        | 6.0   | 6    | 0.0489          | 0.0      |
| No log        | 7.0   | 7    | 0.0881          | 0.0      |
| No log        | 8.0   | 8    | 0.1134          | 0.0      |
| No log        | 9.0   | 9    | 0.1179          | 0.0      |
| 0.0638        | 10.0  | 10   | 0.1054          | 0.0      |
| 0.0638        | 11.0  | 11   | 0.0826          | 0.0      |
| 0.0638        | 12.0  | 12   | 0.0587          | 0.0      |
| 0.0638        | 13.0  | 13   | 0.0386          | 0.0      |
| 0.0638        | 14.0  | 14   | 0.0241          | 0.0      |
| 0.0638        | 15.0  | 15   | 0.0158          | 0.0      |
| 0.0638        | 16.0  | 16   | 0.0115          | 0.0      |
| 0.0638        | 17.0  | 17   | 0.0096          | 0.0      |
| 0.0638        | 18.0  | 18   | 0.0087          | 0.0      |
| 0.0638        | 19.0  | 19   | 0.0084          | 0.0      |
| 0.0048        | 20.0  | 20   | 0.0083          | 0.0      |


### Framework versions

- Transformers 4.29.0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3