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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- pszemraj/scientific_lay_summarisation-elife-norm
metrics:
- rouge
model-index:
- name: long-t5-tglobal-xl-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: 47.1446
pipeline_tag: summarization
inference: False
---
# long-t5-tglobal-xl-sci-simplify-elife
This model is a fine-tuned version of [google/long-t5-tglobal-xl](https://huggingface.co/google/long-t5-tglobal-xl) on the pszemraj/scientific_lay_summarisation-elife-norm dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6666
- Rouge1: 47.1446
- Rouge2: 14.2158
- Rougel: 23.3524
- Rougelsum: 44.6063
- Gen Len: 431.22
## Model description
More information needed
## 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: 8e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 6963
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 1.7959 | 1.0 | 543 | 1.6770 | 44.4187 | 12.6752 | 22.4669 | 41.944 | 456.33 |
| 1.7578 | 2.0 | 1086 | 1.6666 | 47.1446 | 14.2158 | 23.3524 | 44.6063 | 431.22 | |