---
license: apache-2.0
base_model: microsoft/swin-tiny-patch4-window7-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: segformer-class-classWeights-augmentation
  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: 0.8620689655172413
---

<!-- 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. -->

# segformer-class-classWeights-augmentation

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: 0.4872
- Accuracy: 0.8621

## 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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 1    | 1.1700          | 0.2759   |
| No log        | 2.0   | 3    | 1.0351          | 0.3793   |
| No log        | 3.0   | 5    | 0.9731          | 0.5172   |
| No log        | 4.0   | 6    | 0.9362          | 0.5172   |
| No log        | 5.0   | 7    | 0.8890          | 0.5517   |
| No log        | 6.0   | 9    | 0.7596          | 0.7586   |
| 0.5024        | 7.0   | 11   | 0.6531          | 0.8621   |
| 0.5024        | 8.0   | 12   | 0.6170          | 0.8621   |
| 0.5024        | 9.0   | 13   | 0.5878          | 0.8966   |
| 0.5024        | 10.0  | 15   | 0.5418          | 0.8621   |
| 0.5024        | 11.0  | 17   | 0.5122          | 0.8621   |
| 0.5024        | 12.0  | 18   | 0.5021          | 0.8621   |
| 0.5024        | 13.0  | 19   | 0.4928          | 0.8621   |
| 0.3117        | 13.33 | 20   | 0.4872          | 0.8621   |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3