---
license: apache-2.0
tags:
- image-classification
- generated_from_trainer
metrics:
- f1
model-index:
- name: vit_tickers_binaryclf
  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. -->

# vit_tickers_binaryclf

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the cord dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0116
- F1: 0.9991

## 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: 0.0002
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.0026        | 0.28  | 500  | 0.0187          | 0.9982 |
| 0.0186        | 0.56  | 1000 | 0.0116          | 0.9991 |
| 0.0006        | 0.84  | 1500 | 0.0044          | 0.9997 |


### Framework versions

- Transformers 4.21.2
- Pytorch 1.11.0+cu102
- Datasets 2.4.0
- Tokenizers 0.12.1