---
license: apache-2.0
base_model: facebook/convnextv2-tiny-22k-384
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: convnext-tiny-new-5e-5
  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: 0.9404761904761905
---

<!-- 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-new-5e-5

This model is a fine-tuned version of [facebook/convnextv2-tiny-22k-384](https://huggingface.co/facebook/convnextv2-tiny-22k-384) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2310
- Accuracy: 0.9405

## 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: 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.7921        | 1.0   | 1099  | 0.4486          | 0.8680   |
| 0.6062        | 2.0   | 2198  | 0.3753          | 0.8926   |
| 0.4537        | 3.0   | 3297  | 0.3196          | 0.9113   |
| 0.4313        | 4.0   | 4396  | 0.2750          | 0.9241   |
| 0.3747        | 5.0   | 5495  | 0.2922          | 0.9201   |
| 0.3382        | 6.0   | 6594  | 0.2780          | 0.9276   |
| 0.3065        | 7.0   | 7693  | 0.2569          | 0.9292   |
| 0.2331        | 8.0   | 8792  | 0.2539          | 0.9344   |
| 0.2127        | 9.0   | 9891  | 0.2480          | 0.9352   |
| 0.2409        | 10.0  | 10990 | 0.2452          | 0.9344   |


### Framework versions

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