---
license: apache-2.0
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: 0.9772727272727273
---

<!-- 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: 0.0991
- Accuracy: 0.9773

## 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: 10
- eval_batch_size: 10
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 40
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.96  | 6    | 1.0191          | 0.6364   |
| 1.0551        | 1.92  | 12   | 0.8644          | 0.7273   |
| 1.0551        | 2.88  | 18   | 0.5563          | 0.8636   |
| 0.7192        | 4.0   | 25   | 0.2687          | 0.9545   |
| 0.4056        | 4.96  | 31   | 0.1921          | 0.9545   |
| 0.4056        | 5.92  | 37   | 0.1246          | 0.9545   |
| 0.267         | 6.88  | 43   | 0.1010          | 0.9773   |
| 0.2547        | 8.0   | 50   | 0.1442          | 0.9773   |
| 0.2547        | 8.96  | 56   | 0.1188          | 0.9773   |
| 0.189         | 9.6   | 60   | 0.0991          | 0.9773   |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3