---
license: apache-2.0
base_model: facebook/convnextv2-tiny-1k-224
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: quickdraw-ConvNeXT-Tiny-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-ConvNeXT-Tiny-Finetune

This model is a fine-tuned version of [facebook/convnextv2-tiny-1k-224](https://huggingface.co/facebook/convnextv2-tiny-1k-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9012
- Accuracy: 0.7697

## 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: cosine
- lr_scheduler_warmup_steps: 10000
- num_epochs: 8
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Accuracy |
|:-------------:|:------:|:-----:|:---------------:|:--------:|
| 1.2089        | 0.5688 | 5000  | 1.1779          | 0.7020   |
| 1.0859        | 1.1377 | 10000 | 1.1145          | 0.7167   |
| 1.0115        | 1.7065 | 15000 | 1.0129          | 0.7402   |
| 0.8966        | 2.2753 | 20000 | 0.9684          | 0.7533   |
| 0.8868        | 2.8441 | 25000 | 0.9375          | 0.7600   |
| 0.7743        | 3.4130 | 30000 | 0.9292          | 0.7638   |
| 0.7735        | 3.9818 | 35000 | 0.9005          | 0.7707   |
| 0.6379        | 4.5506 | 40000 | 0.9470          | 0.7675   |
| 0.4587        | 5.1195 | 45000 | 1.0663          | 0.7632   |
| 0.469         | 5.6883 | 50000 | 1.0687          | 0.7642   |
| 0.3053        | 6.2571 | 55000 | 1.2674          | 0.7561   |
| 0.3087        | 6.8259 | 60000 | 1.3039          | 0.7563   |
| 0.215         | 7.3948 | 65000 | 1.4453          | 0.7499   |
| 0.2128        | 7.9636 | 70000 | 1.4542          | 0.7500   |


### Framework versions

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