---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swinv2-large-patch4-window12to16-192to256-22kto1k-ft-finetuned-BreastCancer-BreakHis-AH-60-20-20
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: Splitted-Resized
      split: train
      args: Splitted-Resized
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9943422913719944
---

<!-- 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-60-20-20

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 imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0229
- Accuracy: 0.9943

## 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: 7

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.2053        | 1.0   | 199  | 0.1227          | 0.9496   |
| 0.1302        | 2.0   | 398  | 0.0665          | 0.9736   |
| 0.0784        | 3.0   | 597  | 0.0600          | 0.9778   |
| 0.1181        | 4.0   | 796  | 0.0449          | 0.9849   |
| 0.208         | 5.0   | 995  | 0.0393          | 0.9887   |
| 0.0057        | 6.0   | 1194 | 0.0229          | 0.9943   |
| 0.0017        | 7.0   | 1393 | 0.0263          | 0.9939   |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3