---
license: apache-2.0
base_model: WinKawaks/vit-tiny-patch16-224
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: KDRSSC_ViT2TinyViT
  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. -->

# KDRSSC_ViT2TinyViT

This model is a fine-tuned version of [WinKawaks/vit-tiny-patch16-224](https://huggingface.co/WinKawaks/vit-tiny-patch16-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4414
- Accuracy: 0.9381
- Precision: 0.9385
- Recall: 0.9385
- F1: 0.9382

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.9089        | 1.0   | 148  | 0.5624          | 0.906    | 0.9072    | 0.9014 | 0.8987 |
| 0.4816        | 2.0   | 296  | 0.4759          | 0.94     | 0.9411    | 0.9389 | 0.9382 |
| 0.3958        | 3.0   | 444  | 0.4354          | 0.952    | 0.9503    | 0.9510 | 0.9496 |
| 0.3574        | 4.0   | 592  | 0.4273          | 0.949    | 0.9475    | 0.9470 | 0.9460 |
| 0.3406        | 5.0   | 740  | 0.4132          | 0.955    | 0.9548    | 0.9522 | 0.9523 |
| 0.3341        | 6.0   | 888  | 0.4164          | 0.951    | 0.9481    | 0.9503 | 0.9477 |
| 0.3314        | 7.0   | 1036 | 0.4087          | 0.957    | 0.9545    | 0.9538 | 0.9530 |
| 0.3302        | 8.0   | 1184 | 0.4075          | 0.955    | 0.9528    | 0.9517 | 0.9512 |
| 0.3295        | 9.0   | 1332 | 0.4067          | 0.956    | 0.9533    | 0.9533 | 0.9522 |
| 0.3292        | 10.0  | 1480 | 0.4071          | 0.956    | 0.9534    | 0.9533 | 0.9522 |


### Framework versions

- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1