pytorch tensorboard gpt2 text-generation transformers license:mit model-index
---
license: mit
tags:
model-index:
- name: BERFALTER
  results: []
widget:
- text: "Gregg Berhalter"
- text: "The USMNT won't win the World Cup"
- text: "The Soccer Media in this country"
- text: "Ball don't"
- text: "This lineup"

---

# BOTHALTEROUT

This model is a fine-tuned version of [GPT-2](https://huggingface.co/gpt2) using 21,832 tweets from 12 twitter users with very strong opinions about the United States Men's National Team.

## Limitations and bias

The model has all [the same limitations and bias as GPT-2](https://huggingface.co/gpt2#limitations-and-bias).

Additionally, BOTHALTEROUT can create some problematic results based upon the tweets used to generate the model.


### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0001372
- train_batch_size: 1
- 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

### Training results



### Framework versions

- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1

## About

*Built by [Eliot McKinley](https://twitter.com/etmckinley) based upon [HuggingTweets](https://colab.research.google.com/github/borisdayma/huggingtweets/blob/master/huggingtweets-demo.ipynb) by Boris Dayama*
