---
license: apache-2.0
base_model: microsoft/swin-tiny-patch4-window7-224
tags:
- generated_from_trainer
datasets:
- imagefolder
- aytvill/plastic-recycling-codes
metrics:
- accuracy
model-index:
- name: swin-tiny-patch4-window7-224-finetuned-eurosat
  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: 0.391304347826087
widget:
- src: >-
    https://huggingface.co/DamarJati/plastic-recycling-codes/resolve/main/example/image1.jpg
  example_title: image1.jpg
- src: >-
    https://huggingface.co/DamarJati/plastic-recycling-codes/resolve/main/example/image2.jpg
  example_title: image2.jpg
- src: >-
    https://huggingface.co/DamarJati/plastic-recycling-codes/resolve/main/example/image3.jpg
  example_title: image3.jpg
language:
- en
pipeline_tag: image-classification
---

<!-- 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. -->


## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

More information needed

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-5
- 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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 5    | 1.847501        | 0.260870 |
| 1.9354        | 2.0   | 10   | 1.729485        | 0.333333 |
| 1.9354        | 3.0   | 15   | 1.681863        | 0.391304 |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3