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README.md
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model-index:
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- name: FolkGPT
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# FolkGPT
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This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on
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## Model description
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## Intended uses & limitations
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## Training and evaluation data
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## Training procedure
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### Training hyperparameters
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- Transformers 4.26.1
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- Pytorch 1.13.1+cu116
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- Datasets 2.10.0
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- Tokenizers 0.13.2
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model-index:
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- name: FolkGPT
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results: []
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datasets:
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- vicclab/fairy_tales
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language:
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- en
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pipeline_tag: text-generation
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---
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# FolkGPT
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This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on vicclab/fairy_tales dataset.
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## Model description
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This model is the result of fine-tuning gpt2 on a dataset of fairy tales from various cultures.
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## Intended uses & limitations
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The idea behind this is to generate text in the fashion of fairy tales written in the 18th and 19th centuries.
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Why? Fairy tales seemed an appropriate application for text generation, as stories are usually short(ish),
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self-contained, and easy to read.
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## Training and evaluation data
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Trained on the vicclab/fairy_tales dataset. The dataset consists of a number of texts which
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were downloaded from Project Gutenberg, and then edited to remove all text except for the
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stories themselves. These were then all concatenated into a text file and pushed to HF at
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https://huggingface.co/datasets/vicclab/fairy_tales. The latest update to the dataset, which
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was used in the training of this model, was created and uploaded on February 26th, 2023.
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Texts used [and token count after removing boilerplate text]:
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https://www.gutenberg.org/files/2591/2591-0.txt [102927 tokens]
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https://www.gutenberg.org/files/503/503-0.txt [138353 tokens]
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https://www.gutenberg.org/cache/epub/69739/pg69739.txt [51035 tokens]
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https://www.gutenberg.org/files/2435/2435-0.txt [98791 tokens]
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https://www.gutenberg.org/cache/epub/7871/pg7871.txt [49410 tokens]
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https://www.gutenberg.org/files/8933/8933-0.txt [178622 tokens]
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gutenberg.org/cache/epub/30834/pg30834.txt [58359 tokens]
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https://www.gutenberg.org/cache/epub/68589/pg68589.txt [39815 tokens]
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https://www.gutenberg.org/cache/epub/34453/pg34453.txt [69365 tokens]
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gutenberg.org/cache/epub/8653/pg8653.txt [35351]
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[Total tokens in actual dataset: 1002654 tokens]
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## Training procedure
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The dataset was loaded, sampling by paragraph. From here, the dataset was split into a training dataset
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and a validation dataset in an 80-20 split. These were then tokenized. The model was set up, and the trainer
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was instantiated with the training_arguments listed below. Then, the training took place.
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### Training hyperparameters
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- Transformers 4.26.1
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- Pytorch 1.13.1+cu116
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- Datasets 2.10.0
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- Tokenizers 0.13.2
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