---
library_name: transformers
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: 0.958904109589041
---

<!-- 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: 0.2746
- Accuracy: 0.9589

## 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 |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 0.0418        | 0.9362  | 11   | 0.2497          | 0.9041   |
| 0.0349        | 1.9574  | 23   | 0.2377          | 0.9041   |
| 0.0231        | 2.9787  | 35   | 0.2695          | 0.8904   |
| 0.0154        | 4.0     | 47   | 0.2185          | 0.9041   |
| 0.0061        | 4.9362  | 58   | 0.2810          | 0.9178   |
| 0.0023        | 5.9574  | 70   | 0.2905          | 0.9315   |
| 0.0029        | 6.9787  | 82   | 0.2052          | 0.9315   |
| 0.0013        | 8.0     | 94   | 0.2333          | 0.9178   |
| 0.0009        | 8.9362  | 105  | 0.2262          | 0.9315   |
| 0.008         | 9.9574  | 117  | 0.2247          | 0.9178   |
| 0.0014        | 10.9787 | 129  | 0.3200          | 0.9041   |
| 0.0005        | 12.0    | 141  | 0.2643          | 0.9178   |
| 0.0006        | 12.9362 | 152  | 0.2911          | 0.9178   |
| 0.0007        | 13.9574 | 164  | 0.2567          | 0.9178   |
| 0.0009        | 14.9787 | 176  | 0.3170          | 0.9178   |
| 0.0052        | 16.0    | 188  | 0.2435          | 0.9315   |
| 0.0005        | 16.9362 | 199  | 0.2746          | 0.9589   |
| 0.0004        | 17.9574 | 211  | 0.2347          | 0.9315   |
| 0.002         | 18.9787 | 223  | 0.2999          | 0.9178   |
| 0.0021        | 20.0    | 235  | 0.2648          | 0.9178   |
| 0.0003        | 20.9362 | 246  | 0.2609          | 0.9178   |
| 0.0002        | 21.9574 | 258  | 0.2709          | 0.9315   |
| 0.0004        | 22.9787 | 270  | 0.2359          | 0.9315   |
| 0.005         | 24.0    | 282  | 0.2484          | 0.9178   |
| 0.0011        | 24.9362 | 293  | 0.3019          | 0.9178   |
| 0.0012        | 25.9574 | 305  | 0.2715          | 0.9178   |
| 0.0003        | 26.9787 | 317  | 0.2486          | 0.9315   |
| 0.0009        | 28.0    | 329  | 0.2472          | 0.9315   |
| 0.0002        | 28.9362 | 340  | 0.2449          | 0.9315   |
| 0.0002        | 29.9574 | 352  | 0.2480          | 0.9315   |
| 0.0002        | 30.9787 | 364  | 0.2520          | 0.9315   |
| 0.0002        | 32.0    | 376  | 0.2528          | 0.9315   |
| 0.0001        | 32.9362 | 387  | 0.2520          | 0.9315   |
| 0.0002        | 33.9574 | 399  | 0.2503          | 0.9315   |
| 0.0001        | 34.9787 | 411  | 0.2508          | 0.9315   |
| 0.0001        | 36.0    | 423  | 0.2493          | 0.9315   |
| 0.0008        | 36.9362 | 434  | 0.2558          | 0.9315   |
| 0.0001        | 37.9574 | 446  | 0.2616          | 0.9315   |
| 0.0001        | 38.9787 | 458  | 0.2623          | 0.9315   |
| 0.0011        | 40.0    | 470  | 0.2617          | 0.9315   |
| 0.0002        | 40.9362 | 481  | 0.2532          | 0.9315   |
| 0.0001        | 41.9574 | 493  | 0.2495          | 0.9315   |
| 0.0001        | 42.9787 | 505  | 0.2478          | 0.9315   |
| 0.0001        | 44.0    | 517  | 0.2479          | 0.9315   |
| 0.0001        | 44.9362 | 528  | 0.2481          | 0.9315   |
| 0.0001        | 45.9574 | 540  | 0.2481          | 0.9315   |
| 0.002         | 46.8085 | 550  | 0.2475          | 0.9315   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1