---
library_name: transformers
license: apache-2.0
base_model: microsoft/swinv2-tiny-patch4-window8-256
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swinv2-tiny-patch4-window8-256-RD-FIX
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: validation
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.782608695652174
---

<!-- 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. -->

# swinv2-tiny-patch4-window8-256-RD-FIX

This model is a fine-tuned version of [microsoft/swinv2-tiny-patch4-window8-256](https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5014
- Accuracy: 0.7826

## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 40

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| No log        | 0.8571  | 3    | 1.1955          | 0.4565   |
| No log        | 1.8571  | 6    | 1.1280          | 0.5      |
| No log        | 2.8571  | 9    | 1.0565          | 0.4783   |
| 4.8751        | 3.8571  | 12   | 0.9184          | 0.5870   |
| 4.8751        | 4.8571  | 15   | 0.8208          | 0.5870   |
| 4.8751        | 5.8571  | 18   | 0.7310          | 0.6087   |
| 3.6315        | 6.8571  | 21   | 0.6951          | 0.7174   |
| 3.6315        | 7.8571  | 24   | 0.6772          | 0.7174   |
| 3.6315        | 8.8571  | 27   | 0.6626          | 0.7174   |
| 2.8559        | 9.8571  | 30   | 0.5987          | 0.7826   |
| 2.8559        | 10.8571 | 33   | 0.5431          | 0.8261   |
| 2.8559        | 11.8571 | 36   | 0.6193          | 0.6739   |
| 2.8559        | 12.8571 | 39   | 0.6475          | 0.7174   |
| 2.3617        | 13.8571 | 42   | 0.5725          | 0.7174   |
| 2.3617        | 14.8571 | 45   | 0.5794          | 0.7826   |
| 2.3617        | 15.8571 | 48   | 0.5292          | 0.7826   |
| 2.1506        | 16.8571 | 51   | 0.5988          | 0.7391   |
| 2.1506        | 17.8571 | 54   | 0.6548          | 0.7174   |
| 2.1506        | 18.8571 | 57   | 0.5131          | 0.8261   |
| 1.9498        | 19.8571 | 60   | 0.4700          | 0.8478   |
| 1.9498        | 20.8571 | 63   | 0.5254          | 0.8043   |
| 1.9498        | 21.8571 | 66   | 0.5451          | 0.7826   |
| 1.9498        | 22.8571 | 69   | 0.5304          | 0.7609   |
| 1.422         | 23.8571 | 72   | 0.5105          | 0.8043   |
| 1.422         | 24.8571 | 75   | 0.4685          | 0.7826   |
| 1.422         | 25.8571 | 78   | 0.4875          | 0.8261   |
| 1.3044        | 26.8571 | 81   | 0.5492          | 0.7826   |
| 1.3044        | 27.8571 | 84   | 0.5202          | 0.7826   |
| 1.3044        | 28.8571 | 87   | 0.4737          | 0.8261   |
| 1.2464        | 29.8571 | 90   | 0.4398          | 0.8478   |
| 1.2464        | 30.8571 | 93   | 0.4753          | 0.8043   |
| 1.2464        | 31.8571 | 96   | 0.4913          | 0.8043   |
| 1.2464        | 32.8571 | 99   | 0.5262          | 0.7826   |
| 1.1614        | 33.8571 | 102  | 0.5280          | 0.7826   |
| 1.1614        | 34.8571 | 105  | 0.5252          | 0.7609   |
| 1.1614        | 35.8571 | 108  | 0.5127          | 0.7826   |
| 1.045         | 36.8571 | 111  | 0.5061          | 0.7826   |
| 1.045         | 37.8571 | 114  | 0.5012          | 0.7826   |
| 1.045         | 38.8571 | 117  | 0.5025          | 0.7826   |
| 0.9391        | 39.8571 | 120  | 0.5014          | 0.7826   |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0