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  • This model is a fine-tuned version of google/t5-v1_1-base on the vblagoje/lfqa dataset, with training duration of 2 epochs, for a (somewhat) apples-to-apples comparison with t5-base on the standard eli5 dataset.
    • This checkpoint does seem to be more coherent than t5-base on the original dataset.
  • Compared to bart on lfqa, it seems to be able to respond to some questions independently of retrieval.

NOTE: the inference API is limited to generating approx. 64 chars for runtime reasons, for longer outputs try using it in python as a transformers pipeline object.

Intended uses & limitations

  • Q&A, information retrieval
  • it is probably better to use it with a retrieval pipeline than alone

Training and evaluation data

  • see linked dataset. the dataset was filtered to only included the askscience subreddit in an attempt to focus on academic/technical queries.

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 4e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • distributed_type: multi-GPU
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • num_epochs: 2

Training results

Framework versions

  • Transformers 4.16.2
  • Pytorch 1.10.0+cu113
  • Datasets 1.18.3
  • Tokenizers 0.11.0
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Model size
248M params
Tensor type
Hosted inference API
Text2Text Generation
This model can be loaded on the Inference API on-demand.

Dataset used to train pszemraj/t5-base-askscience-lfqa

Space using pszemraj/t5-base-askscience-lfqa 1