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---
license: apache-2.0
base_model: microsoft/swinv2-base-patch4-window12-192-22k
tags:
- image-classification
- vision
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: SWIN_finetuned_frozen_v4
  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_finetuned_frozen_v4

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: 2.0700
- Accuracy: 0.7085

## 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: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15.0

### Training results

| Training Loss | Epoch | Step  | Accuracy | Validation Loss |
|:-------------:|:-----:|:-----:|:--------:|:---------------:|
| 1.3057        | 1.0   | 5249  | 0.5822   | 2.0464          |
| 1.1387        | 2.0   | 10498 | 0.6084   | 1.9457          |
| 0.988         | 3.0   | 15747 | 0.6124   | 1.9650          |
| 0.8653        | 4.0   | 20996 | 0.6344   | 1.9381          |
| 0.7662        | 5.0   | 26245 | 0.6335   | 1.9391          |
| 0.6882        | 6.0   | 31494 | 0.6444   | 1.9591          |
| 0.601         | 7.0   | 36743 | 0.6510   | 1.9506          |
| 0.5363        | 8.0   | 41992 | 0.6617   | 1.9556          |
| 0.4871        | 9.0   | 47241 | 0.6741   | 1.9037          |
| 0.4338        | 10.0  | 52490 | 0.6806   | 1.9794          |
| 0.3738        | 11.0  | 57739 | 0.6849   | 2.0053          |
| 0.3338        | 12.0  | 62988 | 0.6955   | 2.0140          |
| 0.2989        | 13.0  | 68237 | 0.6974   | 2.0830          |
| 0.267         | 14.0  | 73486 | 0.7041   | 2.0824          |
| 0.236         | 15.0  | 78735 | 0.7085   | 2.0700          |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.1.2
- Datasets 2.16.1
- Tokenizers 0.13.3