---
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: 0.9148418491484185
---

<!-- 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: 0.2418
- Accuracy: 0.9148

## 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: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.4375        | 0.9836 | 30   | 0.4385          | 0.8564   |
| 0.3408        | 2.0    | 61   | 0.2872          | 0.8978   |
| 0.3106        | 2.9836 | 91   | 0.2598          | 0.9100   |
| 0.3167        | 4.0    | 122  | 0.2609          | 0.9124   |
| 0.2533        | 4.9836 | 152  | 0.2426          | 0.9075   |
| 0.256         | 6.0    | 183  | 0.2372          | 0.9075   |
| 0.2492        | 6.9836 | 213  | 0.2418          | 0.9148   |
| 0.2364        | 8.0    | 244  | 0.2352          | 0.9051   |
| 0.2301        | 8.9836 | 274  | 0.2348          | 0.9075   |
| 0.2255        | 9.8361 | 300  | 0.2350          | 0.8978   |


### Framework versions

- Transformers 4.42.3
- Pytorch 1.12.1+cu113
- Datasets 2.19.2
- Tokenizers 0.19.1