---
license: apache-2.0
base_model: facebook/convnextv2-nano-22k-384
tags:
- image-classification
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: convnext-nano-15ep
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: vuongnhathien/30VNFoods
      type: imagefolder
      config: default
      split: validation
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9081349206349206
---

<!-- 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-nano-15ep

This model is a fine-tuned version of [facebook/convnextv2-nano-22k-384](https://huggingface.co/facebook/convnextv2-nano-22k-384) on the vuongnhathien/30VNFoods dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4761
- Accuracy: 0.9081

## 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: 0.0003
- train_batch_size: 64
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5814        | 1.0   | 275  | 0.5148          | 0.8477   |
| 0.2972        | 2.0   | 550  | 0.4967          | 0.8557   |
| 0.1871        | 3.0   | 825  | 0.4887          | 0.8716   |
| 0.1205        | 4.0   | 1100 | 0.5173          | 0.8688   |
| 0.0732        | 5.0   | 1375 | 0.4979          | 0.8815   |
| 0.0443        | 6.0   | 1650 | 0.5483          | 0.8815   |
| 0.0392        | 7.0   | 1925 | 0.5512          | 0.8835   |
| 0.018         | 8.0   | 2200 | 0.5102          | 0.8946   |
| 0.0043        | 9.0   | 2475 | 0.5423          | 0.8954   |
| 0.0087        | 10.0  | 2750 | 0.4903          | 0.9105   |
| 0.0035        | 11.0  | 3025 | 0.4855          | 0.9082   |
| 0.0022        | 12.0  | 3300 | 0.4874          | 0.9074   |
| 0.0019        | 13.0  | 3575 | 0.4858          | 0.9082   |
| 0.0018        | 14.0  | 3850 | 0.4857          | 0.9082   |
| 0.0018        | 15.0  | 4125 | 0.4859          | 0.9082   |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2