transformers tensorboard safetensors swin image-classification generated_from_trainer dataset:imagefolder base_model:microsoft/swin-tiny-patch4-window7-224 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
base_model: microsoft/swin-tiny-patch4-window7-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swin-tiny-patch4-window7-224-finetuned-fraud-detection
  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: 0.9591584158415841
---

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# swin-tiny-patch4-window7-224-finetuned-fraud-detection

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: 0.1294
- Accuracy: 0.9592

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.1859        | 1.0   | 57   | 0.2052          | 0.9394   |
| 0.14          | 2.0   | 114  | 0.1544          | 0.9505   |
| 0.1296        | 3.0   | 171  | 0.1620          | 0.9530   |
| 0.1208        | 4.0   | 228  | 0.1573          | 0.9493   |
| 0.0889        | 5.0   | 285  | 0.1294          | 0.9592   |
| 0.0846        | 6.0   | 342  | 0.1400          | 0.9517   |
| 0.0775        | 7.0   | 399  | 0.1222          | 0.9567   |
| 0.0774        | 8.0   | 456  | 0.1564          | 0.9418   |
| 0.0577        | 9.0   | 513  | 0.1274          | 0.9579   |
| 0.0722        | 10.0  | 570  | 0.1332          | 0.9579   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1
