metadata

language:
  - en
tags:
  - t5
datasets:
  - eli5
metrics:
  - rouge
widget:
  - text: why aren't there more planets in our solar system?
    example_title: solar system
  - text: >-
      question: what is a probability distribution? context: I am just learning
      about statistics.
    example_title: probability distribution
  - text: >-
      question: how does exercise help us lose weight? context: I started
      working out two weeks ago and already feel a lot better, and started to
      think about it and became deeply confused.
    example_title: pumpen
inference:
  parameters:
    max_length: 128
    no_repeat_ngram_size: 2
    encoder_no_repeat_ngram_size: 3
    repetition_penalty: 2.4
    length_penalty: 0.5
    num_beams: 4
    early_stopping: true

t5 - base- askscience

the entirety of askscience sub-section of eli5 dataset for one epoch.
compare to bart on eli5 here
note that for the inference API here, the model is restricted to outputting 128 tokens - using the model in python with the transformers library, you can get longer outputs.

training

for inputs, the model was presented with the post title and the post selftext encoded as: question: <post title> context: <post selftext>. You may see better results if queries are posed in this fashion.
The top two replies were aggregated and presented to the model as the output text.