---
license: apache-2.0
base_model: microsoft/swin-base-patch4-window12-384
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: 10-swin-base-patch4-window12-384-finetuned-spiderTraining20-500
  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. -->

# 10-swin-base-patch4-window12-384-finetuned-spiderTraining20-500

This model is a fine-tuned version of [microsoft/swin-base-patch4-window12-384](https://huggingface.co/microsoft/swin-base-patch4-window12-384) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3023
- Accuracy: 0.9339
- Precision: 0.9335
- Recall: 0.9314
- F1: 0.9313

## 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: 0.0005
- train_batch_size: 25
- eval_batch_size: 25
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 4
- total_train_batch_size: 100
- 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 | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.786         | 1.0   | 80   | 0.6341          | 0.7918   | 0.8135    | 0.7860 | 0.7830 |
| 0.6519        | 2.0   | 160  | 0.6522          | 0.7958   | 0.8177    | 0.7913 | 0.7840 |
| 0.6352        | 3.0   | 240  | 0.5289          | 0.8328   | 0.8473    | 0.8255 | 0.8258 |
| 0.4922        | 4.0   | 320  | 0.5681          | 0.8448   | 0.8680    | 0.8386 | 0.8396 |
| 0.3959        | 5.0   | 400  | 0.3896          | 0.8799   | 0.8816    | 0.8772 | 0.8755 |
| 0.3277        | 6.0   | 480  | 0.3588          | 0.9119   | 0.9073    | 0.9104 | 0.9080 |
| 0.284         | 7.0   | 560  | 0.3355          | 0.9099   | 0.9126    | 0.9066 | 0.9058 |
| 0.2075        | 8.0   | 640  | 0.2876          | 0.9289   | 0.9271    | 0.9287 | 0.9269 |
| 0.1751        | 9.0   | 720  | 0.2871          | 0.9349   | 0.9337    | 0.9320 | 0.9321 |
| 0.1923        | 10.0  | 800  | 0.3023          | 0.9339   | 0.9335    | 0.9314 | 0.9313 |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3