pytorch tensorboard bart text2text-generation dataset:scientific_papers transformers generated_from_trainer license:mit model-index autotrain_compatible
---
license: mit
tags:
- generated_from_trainer
datasets:
- scientific_papers
metrics:
- rouge
model-index:
- name: bart-large-cnn-pubmed1o3-pubmed2o3-pubmed3o3
  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: 37.5622
---

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# bart-large-cnn-pubmed1o3-pubmed2o3-pubmed3o3

This model is a fine-tuned version of [theojolliffe/bart-large-cnn-pubmed1o3-pubmed2o3](https://huggingface.co/theojolliffe/bart-large-cnn-pubmed1o3-pubmed2o3) on the scientific_papers dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8540
- Rouge1: 37.5622
- Rouge2: 15.5848
- Rougel: 23.1384
- Rougelsum: 34.2695
- Gen Len: 138.0326

## 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  |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:--------:|
| 1.9205        | 1.0   | 19987 | 1.8540          | 37.5622 | 15.5848 | 23.1384 | 34.2695   | 138.0326 |


### Framework versions

- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1
