---
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-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: 0.8387096774193549
---

<!-- 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: 0.5167
- Accuracy: 0.8387

## 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        | 0.7273  | 2    | 1.4057          | 0.2419   |
| No log        | 1.8182  | 5    | 1.2100          | 0.4677   |
| No log        | 2.9091  | 8    | 1.1808          | 0.4516   |
| 1.3062        | 4.0     | 11   | 1.0975          | 0.5968   |
| 1.3062        | 4.7273  | 13   | 1.0542          | 0.6613   |
| 1.3062        | 5.8182  | 16   | 0.9857          | 0.6613   |
| 1.3062        | 6.9091  | 19   | 0.9176          | 0.6774   |
| 1.0003        | 8.0     | 22   | 0.8761          | 0.6774   |
| 1.0003        | 8.7273  | 24   | 0.8540          | 0.6774   |
| 1.0003        | 9.8182  | 27   | 0.7777          | 0.6613   |
| 0.8096        | 10.9091 | 30   | 0.7498          | 0.6613   |
| 0.8096        | 12.0    | 33   | 0.7569          | 0.6613   |
| 0.8096        | 12.7273 | 35   | 0.7422          | 0.6774   |
| 0.8096        | 13.8182 | 38   | 0.7278          | 0.7097   |
| 0.6556        | 14.9091 | 41   | 0.6877          | 0.7258   |
| 0.6556        | 16.0    | 44   | 0.6433          | 0.7258   |
| 0.6556        | 16.7273 | 46   | 0.6324          | 0.7419   |
| 0.6556        | 17.8182 | 49   | 0.6390          | 0.7419   |
| 0.5725        | 18.9091 | 52   | 0.6504          | 0.7742   |
| 0.5725        | 20.0    | 55   | 0.6145          | 0.7581   |
| 0.5725        | 20.7273 | 57   | 0.5824          | 0.7903   |
| 0.5057        | 21.8182 | 60   | 0.5476          | 0.8226   |
| 0.5057        | 22.9091 | 63   | 0.5413          | 0.8226   |
| 0.5057        | 24.0    | 66   | 0.5335          | 0.8226   |
| 0.5057        | 24.7273 | 68   | 0.5302          | 0.8226   |
| 0.4945        | 25.8182 | 71   | 0.5231          | 0.8226   |
| 0.4945        | 26.9091 | 74   | 0.5167          | 0.8387   |
| 0.4945        | 28.0    | 77   | 0.5132          | 0.8387   |
| 0.4945        | 28.7273 | 79   | 0.5131          | 0.8387   |
| 0.4883        | 29.0909 | 80   | 0.5131          | 0.8387   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1