---
license: bsd-3-clause
tags:
- generated_from_trainer
datasets:
- pszemraj/scientific_lay_summarisation-plos-norm
metrics:
- rouge
model-index:
- name: long-t5-tglobal-xl-16384-book-summary-scientific_lay_summarisation-plos-norm-16384-summ-v1
  results:
  - task:
      name: Summarization
      type: summarization
    dataset:
      name: pszemraj/scientific_lay_summarisation-plos-norm
      type: pszemraj/scientific_lay_summarisation-plos-norm
      split: validation
    metrics:
    - name: Rouge1
      type: rouge
      value: 44.3203
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# long-t5-tglobal-xl-16384-book-summary-scientific_lay_summarisation-plos-norm-16384-summ-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-plos-norm dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5041
- Rouge1: 44.3203
- Rouge2: 11.0576
- Rougel: 22.7584
- Rougelsum: 40.1462
- Gen Len: 256.66

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 3e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 165
- 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: 1.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 1.7715        | 0.28  | 350  | 1.5310          | 43.4729 | 10.4616 | 22.1928 | 39.505    | 260.87  |
| 1.9307        | 0.56  | 700  | 1.5102          | 44.1634 | 10.9336 | 22.3896 | 40.2939   | 253.58  |
| 1.2981        | 0.84  | 1050 | 1.5046          | 44.2728 | 10.8455 | 22.4122 | 40.3019   | 261.29  |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3