---
license: apache-2.0
base_model: facebook/convnextv2-base-22k-224
tags:
- generated_from_trainer
datasets:
- image_folder
metrics:
- accuracy
model-index:
- name: convnextv2-base-22k-224-finetuned-hand_class
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: image_folder
      type: image_folder
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.7336683417085427
---

<!-- 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-224-finetuned-hand_class

This model is a fine-tuned version of [facebook/convnextv2-base-22k-224](https://huggingface.co/facebook/convnextv2-base-22k-224) on the image_folder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5846
- Accuracy: 0.7337

## 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: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- 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 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6258        | 1.0   | 14   | 0.5879          | 0.7136   |
| 0.5574        | 2.0   | 28   | 0.5707          | 0.7286   |
| 0.5062        | 3.0   | 42   | 0.5633          | 0.7186   |
| 0.4812        | 4.0   | 56   | 0.5761          | 0.7136   |
| 0.4418        | 5.0   | 70   | 0.5644          | 0.7312   |
| 0.4167        | 6.0   | 84   | 0.5756          | 0.7236   |
| 0.4091        | 7.0   | 98   | 0.5751          | 0.7337   |
| 0.379         | 8.0   | 112  | 0.5727          | 0.7312   |
| 0.3717        | 9.0   | 126  | 0.5877          | 0.7387   |
| 0.346         | 10.0  | 140  | 0.5846          | 0.7337   |


### Framework versions

- Transformers 4.33.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3