summarization_mlsum

This model is a fine-tuned version of gsarti/it5-base on MLSum-it for Abstractive Summarization.

It achieves the following results:

  • Loss: 2.0190
  • Rouge1: 19.3739
  • Rouge2: 5.9753
  • Rougel: 16.691
  • Rougelsum: 16.7862
  • Gen Len: 32.5268

Usage

from transformers import T5Tokenizer, T5ForConditionalGeneration
tokenizer = T5Tokenizer.from_pretrained("ARTeLab/it5-summarization-mlsum")
model = T5ForConditionalGeneration.from_pretrained("ARTeLab/it5-summarization-mlsum")

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 5e-05
  • train_batch_size: 6
  • eval_batch_size: 6
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 4.0

Framework versions

  • Transformers 4.12.0.dev0
  • Pytorch 1.9.1+cu102
  • Datasets 1.12.1
  • Tokenizers 0.10.3
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Select AutoNLP in the “Train” menu to fine-tune this model automatically.

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