---
license: apache-2.0
base_model: facebook/convnextv2-nano-22k-384
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: convnext-nano-1e-4-augment
  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: 0.9275793650793651
---

<!-- 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-1e-4-augment

This model is a fine-tuned version of [facebook/convnextv2-nano-22k-384](https://huggingface.co/facebook/convnextv2-nano-22k-384) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2728
- Accuracy: 0.9276

## 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: 0.0001
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.8282        | 1.0   | 275  | 0.5148          | 0.8537   |
| 0.5209        | 2.0   | 550  | 0.4151          | 0.8839   |
| 0.3867        | 3.0   | 825  | 0.3643          | 0.9010   |
| 0.3183        | 4.0   | 1100 | 0.3241          | 0.9050   |
| 0.2679        | 5.0   | 1375 | 0.3290          | 0.9046   |
| 0.2364        | 6.0   | 1650 | 0.3088          | 0.9137   |
| 0.1981        | 7.0   | 1925 | 0.2982          | 0.9137   |
| 0.1704        | 8.0   | 2200 | 0.2899          | 0.9169   |
| 0.1572        | 9.0   | 2475 | 0.2868          | 0.9201   |
| 0.168         | 10.0  | 2750 | 0.2866          | 0.9205   |


### Framework versions

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