---
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-Mid-NonMidMarket-Classification
  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: 0.8425624321389794
---

<!-- 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-Mid-NonMidMarket-Classification

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: 0.4046
- Accuracy: 0.8426

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.5809        | 0.9884 | 64   | 0.5024          | 0.7937   |
| 0.5326        | 1.9923 | 129  | 0.4402          | 0.8132   |
| 0.4626        | 2.9961 | 194  | 0.4244          | 0.8284   |
| 0.4778        | 4.0    | 259  | 0.4234          | 0.8274   |
| 0.4109        | 4.9884 | 323  | 0.4197          | 0.8306   |
| 0.3764        | 5.9923 | 388  | 0.4095          | 0.8295   |
| 0.3725        | 6.9961 | 453  | 0.4046          | 0.8426   |
| 0.3583        | 8.0    | 518  | 0.4109          | 0.8371   |
| 0.3451        | 8.9884 | 582  | 0.4171          | 0.8350   |
| 0.3351        | 9.8842 | 640  | 0.4153          | 0.8404   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1