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long-t5-tglobal-large-pubmed-3k-booksum-16384-WIP17

This model is a fine-tuned version of pszemraj/long-t5-tglobal-large-pubmed-3k-booksum-16384-WIP16 on the kmfoda/booksum dataset.

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 0.0001
  • train_batch_size: 1
  • eval_batch_size: 1
  • seed: 42
  • distributed_type: multi-GPU
  • gradient_accumulation_steps: 64
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_ratio: 0.01
  • num_epochs: 3

Framework versions

  • Transformers 4.23.0.dev0
  • Pytorch 1.10.0+cu113
  • Datasets 2.5.1
  • Tokenizers 0.12.1
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Dataset used to train pszemraj/long-t5-tglobal-large-pubmed-3k-booksum-16384-WIP17

Evaluation results