---
license: apache-2.0
base_model: microsoft/swinv2-base-patch4-window16-256
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: SwinV2-Base-Document-Classifier
  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. -->

# SwinV2-Base-Document-Classifier

This model is a fine-tuned version of [microsoft/swinv2-base-patch4-window16-256](https://huggingface.co./microsoft/swinv2-base-patch4-window16-256) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0191
- Accuracy: 0.9946
- F1: 0.9946
- Precision: 0.9946
- Recall: 0.9946

## 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
- training_steps: 800

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.0794        | 0.2   | 160  | 0.0330          | 0.9899   | 0.9899 | 0.9899    | 0.9899 |
| 0.0619        | 0.3   | 240  | 0.0278          | 0.9908   | 0.9908 | 0.9908    | 0.9909 |
| 0.0499        | 0.4   | 320  | 0.0272          | 0.9914   | 0.9914 | 0.9914    | 0.9914 |
| 0.0482        | 0.5   | 400  | 0.0275          | 0.9917   | 0.9917 | 0.9917    | 0.9917 |
| 0.0416        | 1.1   | 480  | 0.0218          | 0.9931   | 0.9931 | 0.9931    | 0.9931 |
| 0.0353        | 1.2   | 560  | 0.0208          | 0.9942   | 0.9942 | 0.9942    | 0.9942 |
| 0.0306        | 1.3   | 640  | 0.0183          | 0.9949   | 0.9949 | 0.9949    | 0.9949 |
| 0.0296        | 1.4   | 720  | 0.0198          | 0.9944   | 0.9944 | 0.9944    | 0.9944 |
| 0.0305        | 1.5   | 800  | 0.0191          | 0.9946   | 0.9946 | 0.9946    | 0.9946 |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.2.2
- Datasets 2.18.0
- Tokenizers 0.15.2