---
license: apache-2.0
base_model: facebook/convnextv2-tiny-1k-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
- precision
model-index:
- name: convnextv2-tiny-1k-224-finetuned-bottomwear-v2
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8981481481481481
    - name: Precision
      type: precision
      value: 0.9001054377012231
---

<!-- 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-tiny-1k-224-finetuned-bottomwear-v2

This model is a fine-tuned version of [facebook/convnextv2-tiny-1k-224](https://huggingface.co/facebook/convnextv2-tiny-1k-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3267
- Accuracy: 0.8981
- Precision: 0.9001

## 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: 2e-05
- train_batch_size: 10
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 100

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|
| No log        | 1.0   | 87   | 1.3349          | 0.6852   | 0.7395    |
| No log        | 2.0   | 174  | 0.7869          | 0.8426   | 0.8543    |
| No log        | 3.0   | 261  | 0.6571          | 0.8472   | 0.8712    |
| No log        | 4.0   | 348  | 0.4293          | 0.9028   | 0.9122    |
| No log        | 5.0   | 435  | 0.4030          | 0.8935   | 0.8953    |
| 0.916         | 6.0   | 522  | 0.4251          | 0.8657   | 0.8787    |
| 0.916         | 7.0   | 609  | 0.3536          | 0.8889   | 0.8936    |
| 0.916         | 8.0   | 696  | 0.3611          | 0.8796   | 0.8833    |
| 0.916         | 9.0   | 783  | 0.3267          | 0.8981   | 0.9001    |
| 0.916         | 10.0  | 870  | 0.3526          | 0.8796   | 0.8972    |
| 0.916         | 11.0  | 957  | 0.3694          | 0.8981   | 0.9100    |
| 0.3192        | 12.0  | 1044 | 0.3694          | 0.8935   | 0.9007    |


### Framework versions

- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1