---
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-Ocular-Toxoplasmosis
  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: 0.08064516129032258
---

<!-- 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-Ocular-Toxoplasmosis

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: 8.8834
- Accuracy: 0.0806

## 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: 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: 40

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.73  | 2    | 8.8834          | 0.0806   |
| No log        | 1.82  | 5    | 8.8522          | 0.0806   |
| No log        | 2.91  | 8    | 8.7000          | 0.0806   |
| 8.7803        | 4.0   | 11   | 8.2692          | 0.0806   |
| 8.7803        | 4.73  | 13   | 7.8836          | 0.0806   |
| 8.7803        | 5.82  | 16   | 7.3279          | 0.0806   |
| 8.7803        | 6.91  | 19   | 6.7700          | 0.0806   |
| 7.5847        | 8.0   | 22   | 6.1880          | 0.0806   |
| 7.5847        | 8.73  | 24   | 5.7783          | 0.0806   |
| 7.5847        | 9.82  | 27   | 5.2113          | 0.0806   |
| 5.7442        | 10.91 | 30   | 4.7163          | 0.0806   |
| 5.7442        | 12.0  | 33   | 4.2648          | 0.0806   |
| 5.7442        | 12.73 | 35   | 3.9892          | 0.0806   |
| 5.7442        | 13.82 | 38   | 3.6134          | 0.0806   |
| 4.1747        | 14.91 | 41   | 3.2828          | 0.0806   |
| 4.1747        | 16.0  | 44   | 2.9957          | 0.0806   |
| 4.1747        | 16.73 | 46   | 2.8259          | 0.0806   |
| 4.1747        | 17.82 | 49   | 2.5988          | 0.0806   |
| 3.0458        | 18.91 | 52   | 2.4004          | 0.0806   |
| 3.0458        | 20.0  | 55   | 2.2272          | 0.0806   |
| 3.0458        | 20.73 | 57   | 2.1254          | 0.0806   |
| 2.3301        | 21.82 | 60   | 1.9937          | 0.0806   |
| 2.3301        | 22.91 | 63   | 1.8860          | 0.0806   |
| 2.3301        | 24.0  | 66   | 1.8005          | 0.0806   |
| 2.3301        | 24.73 | 68   | 1.7551          | 0.0806   |
| 1.9107        | 25.82 | 71   | 1.7021          | 0.0806   |
| 1.9107        | 26.91 | 74   | 1.6654          | 0.0806   |
| 1.9107        | 28.0  | 77   | 1.6434          | 0.0806   |
| 1.9107        | 28.73 | 79   | 1.6362          | 0.0806   |
| 1.7061        | 29.09 | 80   | 1.6348          | 0.0806   |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0