---
license: apache-2.0
base_model: microsoft/swinv2-large-patch4-window12to16-192to256-22kto1k-ft
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: swinv2-large-patch4-window12to16-192to256-22kto1k-ft-finetuned-BreastCancer-BreakHis-AH-Shuffled
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# swinv2-large-patch4-window12to16-192to256-22kto1k-ft-finetuned-BreastCancer-BreakHis-AH-Shuffled

This model is a fine-tuned version of [microsoft/swinv2-large-patch4-window12to16-192to256-22kto1k-ft](https://huggingface.co/microsoft/swinv2-large-patch4-window12to16-192to256-22kto1k-ft) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0289
- Accuracy: 0.9953

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.5
- num_epochs: 12

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.1894        | 1.0   | 199  | 0.1739          | 0.9307   |
| 0.3951        | 2.0   | 398  | 0.1066          | 0.9614   |
| 0.1021        | 3.0   | 597  | 0.0741          | 0.9708   |
| 0.0784        | 4.0   | 796  | 0.0815          | 0.9760   |
| 0.0835        | 5.0   | 995  | 0.0723          | 0.9774   |
| 0.1394        | 6.0   | 1194 | 0.0532          | 0.9840   |
| 0.1755        | 7.0   | 1393 | 0.1068          | 0.9722   |
| 0.1134        | 8.0   | 1592 | 0.0390          | 0.9892   |
| 0.0237        | 9.0   | 1791 | 0.0789          | 0.9863   |
| 0.027         | 10.0  | 1990 | 0.0492          | 0.9887   |
| 0.0081        | 11.0  | 2189 | 0.0429          | 0.9934   |
| 0.011         | 12.0  | 2388 | 0.0289          | 0.9953   |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.0
- Tokenizers 0.13.3