---
license: apache-2.0
base_model: WinKawaks/vit-tiny-patch16-224
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: quickdraw-ViT-base-finetune
  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. -->

# quickdraw-ViT-base-finetune

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: 0.8260
- Accuracy: 0.7892

## 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: 0.0008
- train_batch_size: 512
- eval_batch_size: 512
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10000
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Accuracy |
|:-------------:|:------:|:-----:|:---------------:|:--------:|
| 1.3104        | 0.5688 | 5000  | 1.2637          | 0.6826   |
| 1.1479        | 1.1377 | 10000 | 1.1421          | 0.7096   |
| 1.0236        | 1.7065 | 15000 | 1.0128          | 0.7404   |
| 0.9206        | 2.2753 | 20000 | 0.9457          | 0.7577   |
| 0.8878        | 2.8441 | 25000 | 0.9111          | 0.7652   |
| 0.8107        | 3.4130 | 30000 | 0.8754          | 0.7749   |
| 0.7874        | 3.9818 | 35000 | 0.8436          | 0.7827   |
| 0.7064        | 4.5506 | 40000 | 0.8360          | 0.7869   |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.2.1
- Datasets 2.19.1
- Tokenizers 0.19.1