---
library_name: transformers
license: apache-2.0
base_model: microsoft/swin-base-patch4-window7-224-in22k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swin-base-patch4-window7-224-in22k-construction_type
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: validation
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8804347826086957
---

<!-- 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-base-patch4-window7-224-in22k-construction_type

This model is a fine-tuned version of [microsoft/swin-base-patch4-window7-224-in22k](https://huggingface.co/microsoft/swin-base-patch4-window7-224-in22k) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3095
- Accuracy: 0.8804

## 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: 128
- eval_batch_size: 128
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 512
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 7

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.9839        | 0.9836 | 15   | 0.4599          | 0.8183   |
| 0.4167        | 1.9672 | 30   | 0.3605          | 0.8628   |
| 0.3853        | 2.9508 | 45   | 0.3272          | 0.8799   |
| 0.3302        | 4.0    | 61   | 0.3227          | 0.8763   |
| 0.3302        | 4.9836 | 76   | 0.3269          | 0.8753   |
| 0.3049        | 5.9672 | 91   | 0.3138          | 0.8799   |
| 0.2951        | 6.8852 | 105  | 0.3095          | 0.8804   |


### Framework versions

- Transformers 4.44.2
- Pytorch 1.13.1+cu117
- Datasets 2.20.0
- Tokenizers 0.19.1