---
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: 0.7586206896551724
---

<!-- 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: 0.6803
- Accuracy: 0.7586

## 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: 50
- eval_batch_size: 50
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 200
- 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        | 0.67  | 1    | 1.2027          | 0.3103   |
| No log        | 2.0   | 3    | 1.1212          | 0.3448   |
| No log        | 2.67  | 4    | 1.0648          | 0.4138   |
| No log        | 4.0   | 6    | 0.9779          | 0.5172   |
| No log        | 4.67  | 7    | 0.9494          | 0.5517   |
| No log        | 6.0   | 9    | 0.9168          | 0.5862   |
| 0.9535        | 6.67  | 10   | 0.8808          | 0.6552   |
| 0.9535        | 8.0   | 12   | 0.8136          | 0.7241   |
| 0.9535        | 8.67  | 13   | 0.8015          | 0.7241   |
| 0.9535        | 10.0  | 15   | 0.7727          | 0.7586   |
| 0.9535        | 10.67 | 16   | 0.7510          | 0.7586   |
| 0.9535        | 12.0  | 18   | 0.6997          | 0.7586   |
| 0.9535        | 12.67 | 19   | 0.6856          | 0.7586   |
| 0.5181        | 13.33 | 20   | 0.6803          | 0.7586   |


### Framework versions

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