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---
license: mit
tags:
- generated_from_trainer
datasets:
- scientific_papers
metrics:
- rouge
model-index:
- name: bart-large-cnn-pubmed1o3-pubmed2o3
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: scientific_papers
type: scientific_papers
args: pubmed
metrics:
- name: Rouge1
type: rouge
value: 37.4586
---
<!-- 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. -->
# bart-large-cnn-pubmed1o3-pubmed2o3
This model is a fine-tuned version of [theojolliffe/bart-large-cnn-pubmed1o3](https://huggingface.co/theojolliffe/bart-large-cnn-pubmed1o3) on the scientific_papers dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8817
- Rouge1: 37.4586
- Rouge2: 15.5572
- Rougel: 23.0686
- Rougelsum: 34.1522
- Gen Len: 138.379
## 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: 2e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 1.9586 | 1.0 | 19988 | 1.8817 | 37.4586 | 15.5572 | 23.0686 | 34.1522 | 138.379 |
### Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1
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