---
license: apache-2.0
base_model: microsoft/swinv2-base-patch4-window12-192-22k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: 0.50-200Train-100Test-swinv2-base
  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. -->

# 0.50-200Train-100Test-swinv2-base

This model is a fine-tuned version of [microsoft/swinv2-base-patch4-window12-192-22k](https://huggingface.co/microsoft/swinv2-base-patch4-window12-192-22k) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8692
- Accuracy: 0.8218

## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 1.4079        | 0.9931 | 36   | 0.8584          | 0.7266   |
| 0.4802        | 1.9862 | 72   | 0.6626          | 0.7886   |
| 0.218         | 2.9793 | 108  | 0.7199          | 0.7904   |
| 0.1184        | 4.0    | 145  | 0.7587          | 0.8096   |
| 0.0531        | 4.9931 | 181  | 0.7530          | 0.8157   |
| 0.0579        | 5.9862 | 217  | 0.7707          | 0.8070   |
| 0.031         | 6.9793 | 253  | 0.8554          | 0.8262   |
| 0.0094        | 8.0    | 290  | 0.8697          | 0.8122   |
| 0.0131        | 8.9931 | 326  | 0.8843          | 0.8227   |
| 0.0128        | 9.9310 | 360  | 0.8692          | 0.8218   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1