---
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-1e-4-batch-32
  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-1e-4-batch-32

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: 0.2265
- 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: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7731        | 1.0   | 550  | 0.4237          | 0.8839   |
| 0.6206        | 2.0   | 1100 | 0.3756          | 0.8930   |
| 0.5014        | 3.0   | 1650 | 0.3272          | 0.9074   |
| 0.3892        | 4.0   | 2200 | 0.2729          | 0.9280   |
| 0.3819        | 5.0   | 2750 | 0.2953          | 0.9205   |
| 0.3315        | 6.0   | 3300 | 0.2784          | 0.9260   |
| 0.281         | 7.0   | 3850 | 0.2535          | 0.9328   |
| 0.217         | 8.0   | 4400 | 0.2498          | 0.9344   |
| 0.2152        | 9.0   | 4950 | 0.2405          | 0.9400   |
| 0.2185        | 10.0  | 5500 | 0.2370          | 0.9400   |


### Framework versions

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