
# vit-base-patch16-224-Futurama_Image_multilabel_clf

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224).

It achieves the following results on the evaluation set:
- Loss: 0.0592
- F1: 0.9818
- Roc Auc: 0.9842
- Accuracy: 0.9672

## Model description

This is a multilabel classification model of screenshot images from the show Futurama.

For more information on how it was created, check out the following link: https://github.com/DunnBC22/Vision_Audio_and_Multimodal_Projects/blob/main/Computer%20Vision/Image%20Classification/Multilabel%20Classification/Futurama%20Screenshots/Futurama%20-%20ML%20Image%20CLF.ipynb

## Intended uses & limitations

This model is intended to demonstrate my ability to solve a complex problem using technology.

## Training and evaluation data

Dataset Source: https://www.kaggle.com/datasets/gonzalorecioc/futurama-frames-with-characteronscreen-data

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| 0.2456        | 1.0   | 916  | 0.0723          | 0.9711 | 0.9746  | 0.9481   |
| 0.0269        | 2.0   | 1832 | 0.0545          | 0.9799 | 0.9818  | 0.9640   |
| 0.0086        | 3.0   | 2748 | 0.0580          | 0.9794 | 0.9814  | 0.9623   |
| 0.0044        | 4.0   | 3664 | 0.0612          | 0.9814 | 0.9832  | 0.9651   |
| 0.0027        | 5.0   | 4580 | 0.0592          | 0.9818 | 0.9842  | 0.9672   |
| 0.0017        | 6.0   | 5496 | 0.0634          | 0.9800 | 0.9832  | 0.9645   |
| 0.0012        | 7.0   | 6412 | 0.0657          | 0.9817 | 0.9840  | 0.9667   |
| 0.0005        | 8.0   | 7328 | 0.0668          | 0.9812 | 0.9836  | 0.9667   |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.12.1
- Datasets 2.8.0
- Tokenizers 0.12.1
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