---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swin-tiny-patch4-window7-224-finetuned-trash_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: 0.882689556509299
---

<!-- 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-finetuned-trash_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: 0.3380
- Accuracy: 0.8827

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4991        | 1.0   | 22   | 0.5482          | 0.7911   |
| 0.4008        | 2.0   | 44   | 0.5193          | 0.7954   |
| 0.3659        | 3.0   | 66   | 0.4464          | 0.8398   |
| 0.372         | 4.0   | 88   | 0.4384          | 0.8398   |
| 0.3388        | 5.0   | 110  | 0.4281          | 0.8455   |
| 0.2654        | 6.0   | 132  | 0.3618          | 0.8712   |
| 0.2326        | 7.0   | 154  | 0.3550          | 0.8755   |
| 0.2354        | 8.0   | 176  | 0.3401          | 0.8798   |
| 0.1774        | 9.0   | 198  | 0.3372          | 0.8827   |
| 0.1849        | 10.0  | 220  | 0.3380          | 0.8827   |


### Framework versions

- Transformers 4.23.1
- Pytorch 1.13.0+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2