README.md

metadata

tags:
  - summarization
language:
  - it
metrics:
  - rouge
model-index:
  - name: summarization_fanpage128
    results: []
datasets:
  - ARTeLab/fanpage

summarization_fanpage128

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

It achieves the following results:

• Loss: 1.5492
• Rouge1: 33.8286
• Rouge2: 15.4551
• Rougel: 24.9001
• Rougelsum: 28.3133
• Gen Len: 69.7954

Usage

from transformers import T5Tokenizer, T5ForConditionalGeneration
tokenizer = T5Tokenizer.from_pretrained("ARTeLab/it5-summarization-fanpage-128")
model = T5ForConditionalGeneration.from_pretrained("ARTeLab/it5-summarization-fanpage-128")

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 5e-05
• train_batch_size: 3
• eval_batch_size: 3
• 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