---
license: 
- bsd-3-clause
- apache-2.0
tags:
- generated_from_trainer
datasets:
- pszemraj/scientific_lay_summarisation-elife-norm
metrics:
- rouge
model-index:
- name: >-
    long-t5-tglobal-xl-16384-book-summary-scientific_lay_summarisation-elife-norm-16384-summ-v1
  results:
  - task:
      name: Summarization
      type: summarization
    dataset:
      name: pszemraj/scientific_lay_summarisation-elife-norm
      type: pszemraj/scientific_lay_summarisation-elife-norm
      split: validation
    metrics:
    - name: Rouge1
      type: rouge
      value: 47.4591
language:
- en
library_name: transformers
inference: False
---


# long-t5-tglobal-xl-16384-booksci-summary-v1

This model is a fine-tuned version of [pszemraj/long-t5-tglobal-xl-16384-book-summary](https://huggingface.co/pszemraj/long-t5-tglobal-xl-16384-book-summary) on the pszemraj/scientific_lay_summarisation-elife-norm dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7518
- Rouge1: 47.4591
- Rouge2: 12.7287
- Rougel: 21.5549
- Rougelsum: 44.8709
- Gen Len: 384.39

## Model description

An experiment of further fine-tuning a booksum model on a different dataset. Compare to either the starting checkpoint (_linked above_) or to the [variant only fine-tuned on the scientific lay summaries](https://huggingface.co/pszemraj/long-t5-tglobal-xl-sci-simplify-elife).


## Intended uses & limitations

More information needed

## Training and evaluation data

the pszemraj/scientific_lay_summarisation-elife-norm dataset, input 16384 tokens then truncate, output 1024 tokens then truncate.

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 3e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 878
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.02
- num_epochs: 2.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 1.9629        | 1.0   | 543  | 1.7637          | 46.6926 | 12.4769 | 21.4364 | 44.4329   | 381.23  |
| 1.8555        | 2.0   | 1086 | 1.7518          | 47.4591 | 12.7287 | 21.5549 | 44.8709   | 384.39  |