---
license: apache-2.0
base_model: facebook/convnextv2-base-22k-384
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- f1
model-index:
- name: convnextv2-base-22k-384
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: train
      args: default
    metrics:
    - name: F1
      type: f1
      value: 0.9913113141099743
---

<!-- 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. -->

# convnextv2-base-22k-384

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: 0.0069
- F1: 0.9913

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.1521        | 1.0   | 202  | 0.0982          | 0.8278 |
| 0.0664        | 2.0   | 404  | 0.0626          | 0.9079 |
| 0.1053        | 3.0   | 606  | 0.0356          | 0.9537 |
| 0.0432        | 4.0   | 808  | 0.0302          | 0.9703 |
| 0.0552        | 5.0   | 1010 | 0.0114          | 0.9827 |
| 0.0352        | 6.0   | 1212 | 0.0131          | 0.9824 |
| 0.0221        | 7.0   | 1414 | 0.0063          | 0.9943 |
| 0.0018        | 8.0   | 1616 | 0.0169          | 0.9824 |
| 0.0283        | 9.0   | 1818 | 0.0028          | 0.9971 |
| 0.0429        | 10.0  | 2020 | 0.0069          | 0.9913 |


### Framework versions

- Transformers 4.37.2
- Pytorch 1.12.1+cu102
- Datasets 2.16.1
- Tokenizers 0.15.1