---
license: apache-2.0
base_model: facebook/convnextv2-base-22k-384
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: convnext-base-8e-5-15ep
  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: 0.9369047619047619
---

<!-- 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-base-8e-5-15ep

This model is a fine-tuned version of [facebook/convnextv2-base-22k-384](https://huggingface.co/facebook/convnextv2-base-22k-384) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3097
- Accuracy: 0.9369

## 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: 8e-05
- train_batch_size: 16
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.5403        | 1.0   | 1099  | 0.4231          | 0.8744   |
| 0.4376        | 2.0   | 2198  | 0.3817          | 0.8899   |
| 0.3601        | 3.0   | 3297  | 0.3818          | 0.9018   |
| 0.3202        | 4.0   | 4396  | 0.3153          | 0.9201   |
| 0.2463        | 5.0   | 5495  | 0.3216          | 0.9229   |
| 0.2051        | 6.0   | 6594  | 0.3338          | 0.9213   |
| 0.2108        | 7.0   | 7693  | 0.3224          | 0.9272   |
| 0.1568        | 8.0   | 8792  | 0.3127          | 0.9356   |
| 0.1491        | 9.0   | 9891  | 0.3258          | 0.9352   |
| 0.0998        | 10.0  | 10990 | 0.3257          | 0.9348   |
| 0.0728        | 11.0  | 12089 | 0.3289          | 0.9368   |
| 0.0872        | 12.0  | 13188 | 0.3288          | 0.9408   |
| 0.0731        | 13.0  | 14287 | 0.3320          | 0.9408   |
| 0.0693        | 14.0  | 15386 | 0.3270          | 0.9423   |
| 0.0586        | 15.0  | 16485 | 0.3251          | 0.9427   |


### Framework versions

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