README.md

---
license: apache-2.0
base_model: Yogesh1p/swin-tiny-patch4-window7-224-finetuned-cp3
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swin-tiny-patch4-window7-224-finetuned-cp3
 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: 0.5625
---

<!-- 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. -->

# swin-tiny-patch4-window7-224-finetuned-cp3

This model is a fine-tuned version of [Yogesh1p/swin-tiny-patch4-window7-224-finetuned-cp3](https://huggingface.co/Yogesh1p/swin-tiny-patch4-window7-224-finetuned-cp3) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7607
- Accuracy: 0.5625

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 0.86 | 3 | 1.0238 | 0.2292 |
| No log | 2.0 | 7 | 1.0684 | 0.2708 |
| 0.3856 | 2.86 | 10 | 0.7773 | 0.5208 |
| 0.3856 | 4.0 | 14 | 0.7619 | 0.5417 |
| 0.3856 | 4.29 | 15 | 0.7607 | 0.5625 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0