---
license: apache-2.0
base_model: facebook/convnext-tiny-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/convnext-tiny-224](https://huggingface.co/facebook/convnext-tiny-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8413
- Accuracy: 0.7826

## 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: 5000
- num_epochs: 7
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Accuracy |
|:-------------:|:------:|:-----:|:---------------:|:--------:|
| 1.0895        | 0.5688 | 5000  | 1.0618          | 0.7278   |
| 0.8912        | 1.1377 | 10000 | 0.9315          | 0.7602   |
| 0.8658        | 1.7065 | 15000 | 0.8871          | 0.7701   |
| 0.7558        | 2.2753 | 20000 | 0.8653          | 0.7780   |
| 0.7578        | 2.8441 | 25000 | 0.8392          | 0.7826   |
| 0.6249        | 3.4130 | 30000 | 0.8584          | 0.7842   |
| 0.6243        | 3.9818 | 35000 | 0.8410          | 0.7882   |
| 0.4585        | 4.5506 | 40000 | 0.9402          | 0.7828   |
| 0.2934        | 5.1195 | 45000 | 1.0587          | 0.7758   |
| 0.2869        | 5.6883 | 50000 | 1.1280          | 0.7745   |
| 0.1837        | 6.2571 | 55000 | 1.2402          | 0.7684   |
| 0.1858        | 6.8259 | 60000 | 1.2570          | 0.7679   |


### Framework versions

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