---
license: apache-2.0
base_model: facebook/convnextv2-tiny-1k-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: convnext-tiny-upgrade-1k-224-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: 0.8850894632206759
---

<!-- 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-1k-224-batch-32

This model is a fine-tuned version of [facebook/convnextv2-tiny-1k-224](https://huggingface.co/facebook/convnextv2-tiny-1k-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4287
- Accuracy: 0.8851

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.5523        | 1.0   | 550  | 1.2083          | 0.7010   |
| 1.0852        | 2.0   | 1100 | 0.7955          | 0.7960   |
| 0.9179        | 3.0   | 1650 | 0.6425          | 0.8258   |
| 0.7621        | 4.0   | 2200 | 0.5426          | 0.8549   |
| 0.7506        | 5.0   | 2750 | 0.5018          | 0.8624   |
| 0.6774        | 6.0   | 3300 | 0.4792          | 0.8684   |
| 0.6364        | 7.0   | 3850 | 0.4526          | 0.8744   |
| 0.5961        | 8.0   | 4400 | 0.4362          | 0.8799   |
| 0.602         | 9.0   | 4950 | 0.4316          | 0.8827   |
| 0.5896        | 10.0  | 5500 | 0.4287          | 0.8851   |


### Framework versions

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