---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: convnext-tiny-224-finetuned-main-gpu-20e-final
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: validation
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9875
---

<!-- 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-main-gpu-20e-final

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: 0.0349
- Accuracy: 0.9875

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.6197        | 1.0   | 551   | 0.5899          | 0.7440   |
| 0.3906        | 2.0   | 1102  | 0.3245          | 0.8717   |
| 0.3161        | 3.0   | 1653  | 0.2228          | 0.9135   |
| 0.2323        | 4.0   | 2204  | 0.1481          | 0.9446   |
| 0.2049        | 5.0   | 2755  | 0.1100          | 0.9589   |
| 0.1453        | 6.0   | 3306  | 0.0887          | 0.9671   |
| 0.1786        | 7.0   | 3857  | 0.0796          | 0.9702   |
| 0.1576        | 8.0   | 4408  | 0.0635          | 0.9767   |
| 0.1584        | 9.0   | 4959  | 0.0563          | 0.9798   |
| 0.122         | 10.0  | 5510  | 0.0570          | 0.9793   |
| 0.1138        | 11.0  | 6061  | 0.0526          | 0.9819   |
| 0.1116        | 12.0  | 6612  | 0.0498          | 0.9832   |
| 0.0876        | 13.0  | 7163  | 0.0497          | 0.9830   |
| 0.0956        | 14.0  | 7714  | 0.0403          | 0.9855   |
| 0.0892        | 15.0  | 8265  | 0.0414          | 0.9855   |
| 0.0807        | 16.0  | 8816  | 0.0425          | 0.9861   |
| 0.0959        | 17.0  | 9367  | 0.0397          | 0.9866   |
| 0.0847        | 18.0  | 9918  | 0.0373          | 0.9874   |
| 0.0962        | 19.0  | 10469 | 0.0356          | 0.9870   |
| 0.0731        | 20.0  | 11020 | 0.0349          | 0.9875   |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2