readme: ---
  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*
  