---
library_name: transformers
license: apache-2.0
base_model: microsoft/swin-tiny-patch4-window7-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: bridalMakeupClassifier
  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: 0.9969230769230769
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# bridalMakeupClassifier

This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co./microsoft/swin-tiny-patch4-window7-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0326
- Accuracy: 0.9969

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.1604        | 1.0   | 23   | 0.0509          | 0.9846   |
| 0.0837        | 2.0   | 46   | 0.0353          | 0.9877   |
| 0.0588        | 3.0   | 69   | 0.0326          | 0.9969   |
| 0.05          | 4.0   | 92   | 0.0302          | 0.9969   |
| 0.0284        | 5.0   | 115  | 0.0313          | 0.9938   |
| 0.0372        | 6.0   | 138  | 0.0273          | 0.9938   |
| 0.0461        | 7.0   | 161  | 0.0268          | 0.9969   |
| 0.0338        | 8.0   | 184  | 0.0259          | 0.9969   |
| 0.0253        | 9.0   | 207  | 0.0256          | 0.9938   |
| 0.0326        | 10.0  | 230  | 0.0266          | 0.9969   |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.1+cu121
- Datasets 2.21.0
- Tokenizers 0.20.0