---
license: apache-2.0
base_model: microsoft/swinv2-large-patch4-window12-192-22k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swinv2-large-patch4-window12-192-22k-augmented
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8723404255319149
---

<!-- 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-large-patch4-window12-192-22k-augmented

This model is a fine-tuned version of [microsoft/swinv2-large-patch4-window12-192-22k](https://huggingface.co./microsoft/swinv2-large-patch4-window12-192-22k) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3067
- Accuracy: 0.8723

## 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: 0.0001
- train_batch_size: 48
- eval_batch_size: 48
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 384
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.89  | 3    | 1.4847          | 0.5816   |
| No log        | 1.78  | 6    | 0.9256          | 0.6950   |
| 1.2457        | 2.96  | 10   | 0.6017          | 0.7589   |
| 1.2457        | 3.85  | 13   | 0.3806          | 0.8723   |
| 1.2457        | 4.74  | 16   | 0.3866          | 0.8440   |
| 0.3656        | 5.93  | 20   | 0.3358          | 0.8794   |
| 0.3656        | 6.81  | 23   | 0.2803          | 0.8865   |
| 0.3656        | 8.0   | 27   | 0.3079          | 0.8723   |
| 0.2205        | 8.89  | 30   | 0.3067          | 0.8723   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.1+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1