---
license: apache-2.0
base_model: microsoft/swinv2-base-patch4-window12-192-22k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Train-Test-Augmentation-V3D-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. -->

# Train-Test-Augmentation-V3D-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: 0.7725
- Accuracy: 0.8142

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 1.8252        | 0.9825 | 28   | 0.9390          | 0.7273   |
| 0.5282        | 2.0    | 57   | 0.6414          | 0.7804   |
| 0.2556        | 2.9825 | 85   | 0.6210          | 0.7815   |
| 0.1633        | 4.0    | 114  | 0.7030          | 0.8142   |
| 0.0869        | 4.9825 | 142  | 0.7398          | 0.7877   |
| 0.0524        | 6.0    | 171  | 0.8167          | 0.7962   |
| 0.0277        | 6.9825 | 199  | 0.6993          | 0.8176   |
| 0.0245        | 8.0    | 228  | 0.7444          | 0.8210   |
| 0.0232        | 8.9825 | 256  | 0.8129          | 0.8142   |
| 0.017         | 9.8246 | 280  | 0.7725          | 0.8142   |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.1.2
- Datasets 2.19.1
- Tokenizers 0.19.1