---
license: apache-2.0
base_model: microsoft/swin-tiny-patch4-window7-224
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: swin-tiny-patch4-window7-224-finetuned-RCC
  results: []
---

<!-- 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. -->

# swin-tiny-patch4-window7-224-finetuned-RCC

This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3526
- Accuracy: 0.8226
- Precision: 0.9245
- Recall: 0.875
- F1: 0.5829
- Auc: 0.6042

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     | Auc    |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|
| No log        | 1.0   | 7    | 0.3296          | 0.9032   | 0.9032    | 1.0    | 0.4746 | 0.5    |
| 0.4795        | 2.0   | 14   | 0.3129          | 0.9032   | 0.9032    | 1.0    | 0.4746 | 0.5    |
| 0.2503        | 3.0   | 21   | 0.3182          | 0.9032   | 0.9032    | 1.0    | 0.4746 | 0.5    |
| 0.2503        | 4.0   | 28   | 0.2973          | 0.9032   | 0.9032    | 1.0    | 0.4746 | 0.5    |
| 0.2231        | 5.0   | 35   | 0.3275          | 0.9032   | 0.9032    | 1.0    | 0.4746 | 0.5    |
| 0.1791        | 6.0   | 42   | 0.3147          | 0.9032   | 0.9032    | 1.0    | 0.4746 | 0.5    |
| 0.1791        | 7.0   | 49   | 0.3401          | 0.8978   | 0.9071    | 0.9881 | 0.5206 | 0.5218 |
| 0.1361        | 8.0   | 56   | 0.3885          | 0.7849   | 0.9211    | 0.8333 | 0.5529 | 0.5833 |
| 0.1245        | 9.0   | 63   | 0.3192          | 0.8817   | 0.9195    | 0.9524 | 0.6012 | 0.5873 |
| 0.0902        | 10.0  | 70   | 0.3526          | 0.8226   | 0.9245    | 0.875  | 0.5829 | 0.6042 |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.0.0+cu117
- Datasets 2.19.1
- Tokenizers 0.19.1