---
license: apache-2.0
base_model: facebook/convnextv2-base-22k-384
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: convnext-base-wd1e-8-4e-5-erasing
  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: 0.95
---

<!-- 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-wd1e-8-4e-5-erasing

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: 0.2174
- Accuracy: 0.95

## 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: 4e-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: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.6036        | 1.0   | 1099  | 0.3737          | 0.8930   |
| 0.4997        | 2.0   | 2198  | 0.2730          | 0.9249   |
| 0.3663        | 3.0   | 3297  | 0.2666          | 0.9260   |
| 0.3176        | 4.0   | 4396  | 0.2380          | 0.9392   |
| 0.305         | 5.0   | 5495  | 0.2458          | 0.9372   |
| 0.2489        | 6.0   | 6594  | 0.2389          | 0.9459   |
| 0.2356        | 7.0   | 7693  | 0.2424          | 0.9451   |
| 0.1678        | 8.0   | 8792  | 0.2369          | 0.9439   |
| 0.1565        | 9.0   | 9891  | 0.2323          | 0.9499   |
| 0.1643        | 10.0  | 10990 | 0.2306          | 0.9503   |


### Framework versions

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