---
license: apache-2.0
base_model: facebook/deit-tiny-distilled-patch16-224
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: quickdraw-DeiT-tiny-c
  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-DeiT-tiny-c

This model is a fine-tuned version of [facebook/deit-tiny-distilled-patch16-224](https://huggingface.co/facebook/deit-tiny-distilled-patch16-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8784
- Accuracy: 0.7849

## 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 |
|:-------------:|:------:|:-----:|:---------------:|:--------:|
| 1.2697        | 0.5688 | 5000  | 1.2368          | 0.6883   |
| 1.1262        | 1.1377 | 10000 | 1.1299          | 0.7127   |
| 1.0215        | 1.7065 | 15000 | 1.0110          | 0.7403   |
| 0.939         | 2.2753 | 20000 | 0.9628          | 0.7521   |
| 0.9129        | 2.8441 | 25000 | 0.9281          | 0.7606   |
| 0.8507        | 3.4130 | 30000 | 0.8973          | 0.7687   |
| 0.8354        | 3.9818 | 35000 | 0.8696          | 0.7752   |
| 0.7773        | 4.5506 | 40000 | 0.8575          | 0.7791   |
| 0.7011        | 5.1195 | 45000 | 0.8497          | 0.7829   |
| 0.6989        | 5.6883 | 50000 | 0.8350          | 0.7860   |
| 0.624         | 6.2571 | 55000 | 0.8524          | 0.7857   |
| 0.6245        | 6.8259 | 60000 | 0.8499          | 0.7874   |
| 0.565         | 7.3948 | 65000 | 0.8795          | 0.7849   |
| 0.5663        | 7.9636 | 70000 | 0.8784          | 0.7849   |


### Framework versions

- Transformers 4.41.0
- Pytorch 2.2.1
- Datasets 2.19.1
- Tokenizers 0.19.1