pszemraj / t5-base-askscience-lfqa

huggingface.co
Total runs: 23
24-hour runs: 1
7-day runs: 3
30-day runs: 11
Model's Last Updated: December 29 2025
text-generation

Introduction of t5-base-askscience-lfqa

Model Details of t5-base-askscience-lfqa

checkpoints

  • 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
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

Runs of pszemraj t5-base-askscience-lfqa on huggingface.co

23
Total runs
1
24-hour runs
2
3-day runs
3
7-day runs
11
30-day runs

More Information About t5-base-askscience-lfqa huggingface.co Model

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t5-base-askscience-lfqa install

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