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# bart-base-instructiongen + LongForm
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This model is a fine-tuned version of [pszemraj/bart-base-instructiongen](https://huggingface.co/pszemraj/bart-base-instructiongen) on the `akoksal/LongForm` dataset.
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## Training procedure
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### Training hyperparameters
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_ratio: 0.02
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- num_epochs: 3.0
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### Training results
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### Framework versions
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- Transformers 4.29.0.dev0
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- Pytorch 2.0.1+cu117
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- Datasets 2.12.0
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- Tokenizers 0.13.3
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# bart-base-instructiongen + LongForm
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Instead of generating questions from text, generate instructions for LLMs!
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- Check out a [basic demo on Spaces](https://huggingface.co/spaces/pszemraj/generate-instructions)
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- An example of how to use instructiongen models in a CLI script can be found [here](https://gist.github.com/pszemraj/8b0213e700763106074d3ac15d041c14)
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- You can find other models fine-tuned for instruction generation by [searching for the instructiongen tag](https://huggingface.co/models?other=instructiongen).
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## about
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This model is a fine-tuned version of [pszemraj/bart-base-instructiongen](https://huggingface.co/pszemraj/bart-base-instructiongen) on the `akoksal/LongForm` dataset.
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This was trained on a dataset of **only** instructions+outputs, with any `inputs` filtered out. This means that text of *1) cookies and cream 2) chocolate chip 3) mint chip 4) oreo* will **not** get you *"Rank the following ice cream flavors: oreo, mint chip, chocolate chip, cookies and cream"*.
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## Training procedure
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### Training hyperparameters
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_ratio: 0.02
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- num_epochs: 3.0
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