---
license: apache-2.0
base_model: facebook/dino-vits8
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: dino-vits8-musinsa
  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. -->

# dino-vits8-musinsa

This model is a fine-tuned version of [facebook/dino-vits8](https://huggingface.co/facebook/dino-vits8) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1692
- Precision: 0.9579
- Recall: 0.9576
- F1: 0.9575
- Accuracy: 0.9576

## 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: 5e-05
- 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 | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 202  | 0.1408          | 0.9513    | 0.9494 | 0.9498 | 0.9494   |
| No log        | 2.0   | 404  | 0.1328          | 0.9563    | 0.9558 | 0.9560 | 0.9558   |
| 0.1129        | 3.0   | 606  | 0.1692          | 0.9579    | 0.9576 | 0.9575 | 0.9576   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Tokenizers 0.19.1