---
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-Shuff-3
  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-Shuff-3

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: 0.0161
- Accuracy: 0.9972

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.2598        | 1.0   | 199  | 0.1445          | 0.9416   |
| 0.194         | 2.0   | 398  | 0.1121          | 0.9524   |
| 0.0967        | 3.0   | 597  | 0.0504          | 0.9826   |
| 0.0809        | 4.0   | 796  | 0.1604          | 0.9449   |
| 0.1531        | 5.0   | 995  | 0.0673          | 0.9807   |
| 0.0941        | 6.0   | 1194 | 0.0866          | 0.9680   |
| 0.1157        | 7.0   | 1393 | 0.0525          | 0.9844   |
| 0.0684        | 8.0   | 1592 | 0.1004          | 0.9760   |
| 0.0141        | 9.0   | 1791 | 0.0521          | 0.9873   |
| 0.038         | 10.0  | 1990 | 0.0293          | 0.9934   |
| 0.0044        | 11.0  | 2189 | 0.0161          | 0.9972   |
| 0.0006        | 12.0  | 2388 | 0.0197          | 0.9967   |


### Framework versions

- Transformers 4.32.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3