---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: convnext-large-224-22k-1k-LongSleeveCleanedData
  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: 0.9988826815642458
---

<!-- 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-large-224-22k-1k-LongSleeveCleanedData

This model is a fine-tuned version of [facebook/convnext-large-224-22k-1k](https://huggingface.co/facebook/convnext-large-224-22k-1k) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0060
- Accuracy: 0.9989

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 7
- total_train_batch_size: 56
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.01
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0805        | 0.99  | 143  | 0.0092          | 0.9978   |
| 0.0396        | 2.0   | 287  | 0.0060          | 0.9989   |
| 0.0382        | 3.0   | 431  | 0.0049          | 0.9989   |
| 0.0394        | 4.0   | 575  | 0.0035          | 0.9978   |
| 0.0269        | 5.0   | 719  | 0.0033          | 0.9989   |
| 0.0249        | 6.0   | 863  | 0.0035          | 0.9989   |
| 0.0388        | 7.0   | 1007 | 0.0058          | 0.9989   |
| 0.0175        | 7.99  | 1150 | 0.0039          | 0.9989   |
| 0.041         | 9.0   | 1294 | 0.0022          | 0.9989   |
| 0.0432        | 9.94  | 1430 | 0.0025          | 0.9989   |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3