---
license: mit
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bart-cnn-science-v3-e6
  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. -->

# bart-cnn-science-v3-e6

This model is a fine-tuned version of [theojolliffe/bart-cnn-science](https://huggingface.co/theojolliffe/bart-cnn-science) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8057
- Rouge1: 53.7462
- Rouge2: 34.9622
- Rougel: 37.5676
- Rougelsum: 51.0619
- Gen Len: 142.0

## 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: 6
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len  |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:--------:|
| No log        | 1.0   | 398  | 0.9961          | 52.632  | 32.8104 | 35.0789 | 50.3747   | 142.0    |
| 1.174         | 2.0   | 796  | 0.8565          | 52.8308 | 32.7064 | 34.6605 | 50.3348   | 142.0    |
| 0.7073        | 3.0   | 1194 | 0.8322          | 52.2418 | 32.8677 | 36.1806 | 49.6297   | 141.5556 |
| 0.4867        | 4.0   | 1592 | 0.8137          | 53.5537 | 34.5404 | 36.7194 | 50.8394   | 142.0    |
| 0.4867        | 5.0   | 1990 | 0.7996          | 53.4959 | 35.1017 | 37.5143 | 50.9972   | 141.8704 |
| 0.3529        | 6.0   | 2388 | 0.8057          | 53.7462 | 34.9622 | 37.5676 | 51.0619   | 142.0    |


### Framework versions

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