---
license: other
base_model: apple/mobilevit-xx-small
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: KDRSSC_TinyViT2MobileViT-xx-small
  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_TinyViT2MobileViT-xx-small

This model is a fine-tuned version of [apple/mobilevit-xx-small](https://huggingface.co./apple/mobilevit-xx-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8217
- Accuracy: 0.8398
- Precision: 0.8409
- Recall: 0.8398
- F1: 0.8365

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 2.1113        | 1.0   | 148  | 1.7471          | 0.588    | 0.6313    | 0.588  | 0.5698 |
| 1.6003        | 2.0   | 296  | 1.3462          | 0.704    | 0.7133    | 0.704  | 0.6844 |
| 1.2989        | 3.0   | 444  | 1.1278          | 0.759    | 0.7716    | 0.759  | 0.7509 |
| 1.1115        | 4.0   | 592  | 0.9891          | 0.802    | 0.8022    | 0.802  | 0.7952 |
| 0.9978        | 5.0   | 740  | 0.9123          | 0.827    | 0.8413    | 0.827  | 0.8255 |
| 0.9274        | 6.0   | 888  | 0.8512          | 0.843    | 0.8445    | 0.843  | 0.8387 |
| 0.8748        | 7.0   | 1036 | 0.8210          | 0.842    | 0.8412    | 0.842  | 0.8373 |
| 0.8411        | 8.0   | 1184 | 0.7952          | 0.842    | 0.8398    | 0.842  | 0.8365 |
| 0.818         | 9.0   | 1332 | 0.7814          | 0.852    | 0.8574    | 0.852  | 0.8489 |
| 0.8081        | 10.0  | 1480 | 0.7796          | 0.853    | 0.8591    | 0.853  | 0.8487 |


### Framework versions

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