---
license: mit
base_model: facebook/bart-large-cnn
tags:
- generated_from_trainer
datasets:
- scientific_papers
model-index:
- name: models
  results: []
---

<!-- 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. -->

# models

This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on the scientific_papers dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6842
- Rouge2 Precision: 0.1282
- Rouge2 Recall: 0.1133
- Rouge2 Fmeasure: 0.1186

## 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: 5e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
|:-------------:|:-----:|:----:|:---------------:|:----------------:|:-------------:|:---------------:|
| 2.9888        | 0.32  | 10   | 2.8091          | 0.1445           | 0.1158        | 0.1251          |
| 2.7186        | 0.64  | 20   | 2.6898          | 0.1332           | 0.1183        | 0.1232          |
| 2.6847        | 0.96  | 30   | 2.6861          | 0.1291           | 0.1144        | 0.1197          |


### Framework versions

- Transformers 4.37.2
- Pytorch 1.13.1
- Datasets 2.16.1
- Tokenizers 0.15.2