---
library_name: transformers
license: apache-2.0
base_model: microsoft/swin-tiny-patch4-window7-224
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: swin-tiny-patch4-window7-224-finetuned-tekno24-highdata-90-3rd
  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-tiny-patch4-window7-224-finetuned-tekno24-highdata-90-3rd

This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9108
- Accuracy: 0.6221
- F1: 0.6116
- Precision: 0.6170
- Recall: 0.6221

## 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: 3e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 1.3622        | 0.9786  | 40   | 1.3459          | 0.3687   | 0.2453 | 0.2574    | 0.3687 |
| 1.335         | 1.9817  | 81   | 1.3295          | 0.3779   | 0.3635 | 0.3592    | 0.3779 |
| 1.2404        | 2.9847  | 122  | 1.1256          | 0.5023   | 0.4893 | 0.5048    | 0.5023 |
| 1.2113        | 3.9878  | 163  | 1.1081          | 0.5346   | 0.4918 | 0.5409    | 0.5346 |
| 1.1617        | 4.9908  | 204  | 1.0667          | 0.5300   | 0.4938 | 0.5204    | 0.5300 |
| 1.1758        | 5.9939  | 245  | 1.1505          | 0.4747   | 0.4713 | 0.5074    | 0.4747 |
| 1.1618        | 6.9969  | 286  | 1.1316          | 0.4931   | 0.4779 | 0.4950    | 0.4931 |
| 1.1748        | 8.0     | 327  | 1.0681          | 0.5161   | 0.4827 | 0.5256    | 0.5161 |
| 1.1421        | 8.9786  | 367  | 0.9743          | 0.5714   | 0.5445 | 0.5488    | 0.5714 |
| 1.1565        | 9.9817  | 408  | 0.9705          | 0.5622   | 0.5142 | 0.5429    | 0.5622 |
| 1.1297        | 10.9847 | 449  | 0.9879          | 0.5530   | 0.5365 | 0.5343    | 0.5530 |
| 1.1249        | 11.9878 | 490  | 0.9852          | 0.5760   | 0.5401 | 0.6055    | 0.5760 |
| 1.1289        | 12.9908 | 531  | 0.9555          | 0.5714   | 0.5363 | 0.5409    | 0.5714 |
| 1.1102        | 13.9939 | 572  | 0.9438          | 0.5991   | 0.5795 | 0.6033    | 0.5991 |
| 1.1011        | 14.9969 | 613  | 0.9492          | 0.5991   | 0.5840 | 0.6016    | 0.5991 |
| 1.1293        | 16.0    | 654  | 0.9826          | 0.5714   | 0.5548 | 0.6000    | 0.5714 |
| 1.0706        | 16.9786 | 694  | 0.9465          | 0.5945   | 0.5739 | 0.6001    | 0.5945 |
| 1.0825        | 17.9817 | 735  | 0.9268          | 0.6083   | 0.5861 | 0.6083    | 0.6083 |
| 1.0989        | 18.9847 | 776  | 0.9349          | 0.6083   | 0.5900 | 0.6168    | 0.6083 |
| 1.0541        | 19.9878 | 817  | 0.9408          | 0.6175   | 0.6103 | 0.6332    | 0.6175 |
| 1.0883        | 20.9908 | 858  | 0.9108          | 0.6221   | 0.6116 | 0.6170    | 0.6221 |
| 1.0828        | 21.9939 | 899  | 0.9412          | 0.5991   | 0.5913 | 0.6205    | 0.5991 |
| 1.0492        | 22.9969 | 940  | 0.9263          | 0.6129   | 0.6003 | 0.6442    | 0.6129 |
| 1.0486        | 24.0    | 981  | 0.9254          | 0.6129   | 0.6069 | 0.6137    | 0.6129 |
| 1.0648        | 24.9786 | 1021 | 0.9165          | 0.5991   | 0.5880 | 0.6002    | 0.5991 |
| 1.079         | 25.9817 | 1062 | 0.9294          | 0.5899   | 0.5795 | 0.6006    | 0.5899 |
| 1.0459        | 26.9847 | 1103 | 0.9237          | 0.6083   | 0.5953 | 0.6168    | 0.6083 |
| 1.057         | 27.9878 | 1144 | 0.9233          | 0.6083   | 0.5953 | 0.6168    | 0.6083 |
| 1.0496        | 28.9908 | 1185 | 0.9237          | 0.5991   | 0.5874 | 0.6077    | 0.5991 |
| 1.0509        | 29.3578 | 1200 | 0.9238          | 0.5991   | 0.5874 | 0.6077    | 0.5991 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1