---
license: apache-2.0
base_model: facebook/convnextv2-tiny-22k-384
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: convnext-tiny-upgrade-384-batch-32
  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: 0.9297619047619048
---

<!-- 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-upgrade-384-batch-32

This model is a fine-tuned version of [facebook/convnextv2-tiny-22k-384](https://huggingface.co/facebook/convnextv2-tiny-22k-384) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2521
- Accuracy: 0.9298

## 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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.9343        | 1.0   | 550  | 0.5732          | 0.8410   |
| 0.6456        | 2.0   | 1100 | 0.4130          | 0.8843   |
| 0.5478        | 3.0   | 1650 | 0.3537          | 0.9026   |
| 0.466         | 4.0   | 2200 | 0.3012          | 0.9181   |
| 0.4619        | 5.0   | 2750 | 0.3031          | 0.9141   |
| 0.4046        | 6.0   | 3300 | 0.2971          | 0.9157   |
| 0.3852        | 7.0   | 3850 | 0.2763          | 0.9205   |
| 0.3346        | 8.0   | 4400 | 0.2712          | 0.9225   |
| 0.3386        | 9.0   | 4950 | 0.2672          | 0.9221   |
| 0.3462        | 10.0  | 5500 | 0.2655          | 0.9245   |


### Framework versions

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