---
base_model: swinv2
tags:
- image-classification
- breast cancer
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: swinV2-Mammmogram-V1
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# swinV2-Mammmogram-V1

This model is a fine-tuned version of [swinv2](https://huggingface.co/swinv2) on the Mammogram V1 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1434
- Accuracy: 0.9524
- Precision: 0.9751
- Recall: 0.9524
- F1: 0.9630

## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.4455        | 1.0   | 1112 | 0.1385          | 0.9782   | 0.9739    | 0.9782 | 0.9760 |
| 0.3974        | 2.0   | 2224 | 0.1974          | 0.9524   | 0.9749    | 0.9524 | 0.9630 |
| 0.3712        | 3.0   | 3336 | 0.1386          | 0.9735   | 0.9748    | 0.9735 | 0.9741 |
| 0.2748        | 4.0   | 4448 | 0.1597          | 0.9479   | 0.9752    | 0.9479 | 0.9607 |
| 0.2603        | 5.0   | 5560 | 0.1434          | 0.9524   | 0.9751    | 0.9524 | 0.9630 |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1