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--- |
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language: |
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- en |
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- multilingual |
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- de |
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- it |
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- es |
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- fr |
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tags: |
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- instruction-tuning |
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- text-generation-inference |
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- text2text-generation |
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widget: |
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- text: Write an essay about meditation. |
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example_title: Essay Generation |
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- text: Give me 5 steps to clean my room. |
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example_title: How-to Instructions |
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- text: How are the continents formed? |
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example_title: Question-Answering |
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- text: >- |
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Prompt: A man draws a gun in a dark alley and asks for your wallet. You |
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begrudgingly obey. He throws it on the ground, shoots it till it screeches, |
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and turns to you; 'you are safe now'. Write a story about given prompt. |
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example_title: Story Generation |
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- text: >- |
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Write directions of a cooking recipe with these ingredients: chicken breast, |
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carrots, green peas, celery, butter, onion, flour, salt, black pepper, |
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celery seed, chicken broth, milk, unbaked pie crusts |
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example_title: Recipe Generation |
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- text: Schreiben Sie einen Blogbeitrag über die Vorteile des Lesens von Büchern. |
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example_title: German Essay Generation |
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inference: |
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parameters: |
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top_p: 0.9 |
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do_sample: true |
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max_length: 100 |
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datasets: |
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- akoksal/LongForm |
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--- |
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## LongForm-OPT-6.7B |
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The LongForm dataset is created by leveraging English corpus examples with augmented instructions. We select a diverse set of human-written documents from existing corpora such as C4 and Wikipedia and generate instructions for the given documents via LLMs. Then, we extend these examples with structured corpora examples such as Stack Exchange and WikiHow and task examples such as question answering, email writing, grammar error correction, story/poem generation, and text summarization. |
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Github Repo: https://github.com/akoksal/LongForm |
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LongForm-**OPT-2.7B**: https://huggingface.co/akoksal/LongForm-OPT-2.7B |
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LongForm-**OPT-6.7B**: https://huggingface.co/akoksal/LongForm-OPT-6.7B |
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## Evaluation |
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We provide in-depth evaluation of LongForm models and baselines in the paper. We present the METEOR scores of models in out-of-domain datasets. In all tasks, Recipe Generation (RGen), long-form question answering (ELI5), short story generation (WritingPrompts/WP), LongForm models outperform prior instruction-tuned models. |
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| | **All** | **Recipe Generation** | **ELI5** | **Writing Prompts** | |
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|-----------------------|---------|-----------------------------------|----------|---------------------| |
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| **T0++** | 10.9 | 18.7 | 3.8 | 10.2 | |
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| **Tk-Instruct** | 6.3 | 12.9* | 3.6 | 2.4 | |
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| **Flan-T5** | 10.6 | 20.9* | 3.5 | 7.4 | |
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| **Alpaca-LLaMA-7B** | 14.6 | 19.5 | 12.5 | 11.8 | |
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| **OPT-30B** | 11.1 | 18.6 | 12.2 | 2.6 | |
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| **[LongForm-T5-XL](https://huggingface.co/akoksal/LongForm-T5-XL)** | 16.3 | 20.2 | 18.3 | 10.6 | |
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| **[LongForm-OPT-2.7B](https://huggingface.co/akoksal/LongForm-OPT-2.7B)** | 17.8 | 15.5 | 17.9 | **19.9** | |
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| **[LongForm-OPT-6.7B](https://huggingface.co/akoksal/LongForm-OPT-6.7B)** | 17.7 | 16.9 | 17.2 | 19.0 | |
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| **LongForm-LLaMA-7B**‡ | **19.7** | **21.7** | **18.6** | 18.9 | |
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‡: We cannot release LongForm-LLaMA-7B publicly due to restrictions of LLaMA models. |
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## Limitations |
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The LongForm dataset and models mainly focus on long text generation and have limitations regarding structured prediction tasks in NLP. Additionally, we observe that LongForm models may present hallucination problems similar to those found in LLMs. |
