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
- Downloads last month
- 43
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Model tree for ARTeLab/it5-summarization-ilpost
Base model
gsarti/it5-base