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summarization_ilpost

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

It achieves the following results:

  • Loss: 1.6020
  • Rouge1: 33.7802
  • Rouge2: 16.2953
  • Rougel: 27.4797
  • Rougelsum: 30.2273
  • Gen Len: 45.3175

Usage

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

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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Dataset used to train ARTeLab/it5-summarization-ilpost

Space using ARTeLab/it5-summarization-ilpost