---
license: apache-2.0
base_model: facebook/convnext-tiny-224
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: 0.5
---

<!-- 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 [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: 1.3086
- Accuracy: 0.5

## 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: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 5    | 2.0663          | 0.1562   |
| 2.0637        | 2.0   | 10   | 2.0571          | 0.1812   |
| 2.0637        | 3.0   | 15   | 2.0389          | 0.1938   |
| 2.0295        | 4.0   | 20   | 2.0109          | 0.2437   |
| 2.0295        | 5.0   | 25   | 1.9754          | 0.2875   |
| 1.9452        | 6.0   | 30   | 1.9335          | 0.2938   |
| 1.9452        | 7.0   | 35   | 1.8869          | 0.275    |
| 1.8289        | 8.0   | 40   | 1.8378          | 0.2812   |
| 1.8289        | 9.0   | 45   | 1.7800          | 0.3563   |
| 1.7075        | 10.0  | 50   | 1.7231          | 0.3563   |
| 1.7075        | 11.0  | 55   | 1.6730          | 0.3625   |
| 1.5909        | 12.0  | 60   | 1.6253          | 0.3688   |
| 1.5909        | 13.0  | 65   | 1.5897          | 0.3875   |
| 1.4997        | 14.0  | 70   | 1.5604          | 0.4      |
| 1.4997        | 15.0  | 75   | 1.5336          | 0.425    |
| 1.4066        | 16.0  | 80   | 1.5147          | 0.425    |
| 1.4066        | 17.0  | 85   | 1.4923          | 0.425    |
| 1.3344        | 18.0  | 90   | 1.4744          | 0.4375   |
| 1.3344        | 19.0  | 95   | 1.4615          | 0.4437   |
| 1.2545        | 20.0  | 100  | 1.4479          | 0.4437   |
| 1.2545        | 21.0  | 105  | 1.4311          | 0.45     |
| 1.1789        | 22.0  | 110  | 1.4222          | 0.475    |
| 1.1789        | 23.0  | 115  | 1.4099          | 0.4813   |
| 1.1186        | 24.0  | 120  | 1.3926          | 0.4688   |
| 1.1186        | 25.0  | 125  | 1.3835          | 0.4625   |
| 1.0685        | 26.0  | 130  | 1.3747          | 0.4625   |
| 1.0685        | 27.0  | 135  | 1.3622          | 0.4625   |
| 0.9935        | 28.0  | 140  | 1.3523          | 0.4688   |
| 0.9935        | 29.0  | 145  | 1.3514          | 0.45     |
| 0.9453        | 30.0  | 150  | 1.3413          | 0.4688   |
| 0.9453        | 31.0  | 155  | 1.3334          | 0.45     |
| 0.9162        | 32.0  | 160  | 1.3239          | 0.45     |
| 0.9162        | 33.0  | 165  | 1.3177          | 0.475    |
| 0.8637        | 34.0  | 170  | 1.3090          | 0.475    |
| 0.8637        | 35.0  | 175  | 1.3078          | 0.4938   |
| 0.8298        | 36.0  | 180  | 1.3086          | 0.5      |
| 0.8298        | 37.0  | 185  | 1.2990          | 0.5      |
| 0.7801        | 38.0  | 190  | 1.2975          | 0.4938   |
| 0.7801        | 39.0  | 195  | 1.2946          | 0.4938   |
| 0.7691        | 40.0  | 200  | 1.2921          | 0.4875   |
| 0.7691        | 41.0  | 205  | 1.2913          | 0.4938   |
| 0.7409        | 42.0  | 210  | 1.2902          | 0.4875   |
| 0.7409        | 43.0  | 215  | 1.2886          | 0.4875   |
| 0.7223        | 44.0  | 220  | 1.2860          | 0.4938   |
| 0.7223        | 45.0  | 225  | 1.2849          | 0.4875   |
| 0.7091        | 46.0  | 230  | 1.2849          | 0.4875   |
| 0.7091        | 47.0  | 235  | 1.2854          | 0.4875   |
| 0.6915        | 48.0  | 240  | 1.2845          | 0.4875   |
| 0.6915        | 49.0  | 245  | 1.2842          | 0.4875   |
| 0.6917        | 50.0  | 250  | 1.2840          | 0.4875   |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1