---
license: other
base_model: google/mobilenet_v2_1.0_224
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: doodle_mobilenet
  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. -->

# doodle_mobilenet

This model is a fine-tuned version of [google/mobilenet_v2_1.0_224](https://huggingface.co/google/mobilenet_v2_1.0_224) on the  
[Quick, Draw! small dataset](https://huggingface.co/datasets/Xenova/quickdraw-small)

## 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
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Accuracy |
|:-------------:|:------:|:-----:|:---------------:|:--------:|
| 1.4546        | 0.5688 | 5000  | 1.4383          | 0.6474   |
| 1.3759        | 1.1377 | 10000 | 1.3850          | 0.6610   |
| 1.3508        | 1.7065 | 15000 | 1.3163          | 0.6737   |
| 1.294         | 2.2753 | 20000 | 1.2832          | 0.6829   |
| 1.2811        | 2.8441 | 25000 | 1.2581          | 0.6881   |
| 1.2331        | 3.4130 | 30000 | 1.2387          | 0.6926   |
| 1.2276        | 3.9818 | 35000 | 1.2227          | 0.6978   |
| 1.1964        | 4.5506 | 40000 | 1.2196          | 0.6990   |
| 1.1498        | 5.1195 | 45000 | 1.1994          | 0.7036   |
| 1.1548        | 5.6883 | 50000 | 1.1900          | 0.7052   |
| 1.1232        | 6.2571 | 55000 | 1.1831          | 0.7075   |
| 1.1264        | 6.8259 | 60000 | 1.1695          | 0.7100   |
| 1.0896        | 7.3948 | 65000 | 1.1584          | 0.7128   |
| 1.0917        | 7.9636 | 70000 | 1.1535          | 0.7155   |
| 1.0654        | 8.5324 | 75000 | 1.1545          | 0.7144   |
| 1.0395        | 9.1013 | 80000 | 1.1471          | 0.7169   |
| 1.0383        | 9.6701 | 85000 | 1.1722          | 0.7136   |


### Framework versions

- Transformers 4.40.0
- Pytorch 2.2.1
- Datasets 2.19.0
- Tokenizers 0.19.1