---
library_name: transformers
license: other
base_model: apple/mobilevit-xx-small
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: KDRSSC_ViT2MobileViT-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_ViT2MobileViT-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: 0.6274
- Accuracy: 0.8495
- Precision: 0.8504
- Recall: 0.8501
- F1: 0.8440

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.6963        | 1.0   | 148  | 1.3476          | 0.596    | 0.6092    | 0.5736 | 0.5557 |
| 1.2335        | 2.0   | 296  | 1.0216          | 0.725    | 0.7180    | 0.7135 | 0.6918 |
| 0.9693        | 3.0   | 444  | 0.8330          | 0.776    | 0.7560    | 0.7699 | 0.7481 |
| 0.8246        | 4.0   | 592  | 0.7345          | 0.812    | 0.8091    | 0.8042 | 0.7889 |
| 0.7393        | 5.0   | 740  | 0.6836          | 0.828    | 0.8084    | 0.8223 | 0.8070 |
| 0.6895        | 6.0   | 888  | 0.6504          | 0.831    | 0.8245    | 0.8253 | 0.8134 |
| 0.6528        | 7.0   | 1036 | 0.6252          | 0.859    | 0.8546    | 0.8571 | 0.8461 |
| 0.6303        | 8.0   | 1184 | 0.6089          | 0.856    | 0.8506    | 0.8554 | 0.8444 |
| 0.6138        | 9.0   | 1332 | 0.6002          | 0.863    | 0.8567    | 0.8632 | 0.8519 |
| 0.6067        | 10.0  | 1480 | 0.6003          | 0.863    | 0.8596    | 0.8624 | 0.8521 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0
- Datasets 3.0.0
- Tokenizers 0.19.1