---
license: mit
base_model: facebook/bart-large-xsum
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: text_shortening_model_v45
  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. -->

# text_shortening_model_v45

This model is a fine-tuned version of [facebook/bart-large-xsum](https://huggingface.co./facebook/bart-large-xsum) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 26.8982
- Rouge1: 0.0
- Rouge2: 0.0
- Rougel: 0.0
- Rougelsum: 0.0
- Bert precision: 0.6649
- Bert recall: 0.672
- Average word count: 1.0
- Max word count: 1
- Min word count: 1
- Average token count: 62.0
- % shortened texts with length > 12: 0.0

## 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: 0.0003
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Bert precision | Bert recall | Average word count | Max word count | Min word count | Average token count | % shortened texts with length > 12 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:--------------:|:-----------:|:------------------:|:--------------:|:--------------:|:-------------------:|:----------------------------------:|
| 3.3791        | 1.0   | 83   | 6.7318          | 0.0982 | 0.0    | 0.0972 | 0.0969    | 0.6855         | 0.6599      | 1.2937             | 2              | 1              | 16.7619             | 0.0                                |
| 2.8727        | 2.0   | 166  | 10.3841         | 0.0    | 0.0    | 0.0    | 0.0       | 0.674          | 0.6911      | 3.0                | 3              | 3              | 62.0                | 0.0                                |
| 2.7805        | 3.0   | 249  | 10.0261         | 0.0345 | 0.0    | 0.0346 | 0.0345    | 0.6746         | 0.6819      | 2.0                | 2              | 2              | 62.0                | 0.0                                |
| 2.7183        | 4.0   | 332  | 9.5191          | 0.0    | 0.0    | 0.0    | 0.0       | 0.673          | 0.6736      | 1.0                | 1              | 1              | 62.0                | 0.0                                |
| 2.7086        | 5.0   | 415  | 10.4466         | 0.0    | 0.0    | 0.0    | 0.0       | 0.6568         | 0.6648      | 1.0                | 1              | 1              | 62.0                | 0.0                                |
| 2.6474        | 6.0   | 498  | 13.9665         | 0.0    | 0.0    | 0.0    | 0.0       | 0.6641         | 0.6709      | 1.0                | 1              | 1              | 62.0                | 0.0                                |
| 2.63          | 7.0   | 581  | 13.3621         | 0.0    | 0.0    | 0.0    | 0.0       | 0.6457         | 0.6701      | 1.0                | 1              | 1              | 62.0                | 0.0                                |
| 2.5998        | 8.0   | 664  | 13.0602         | 0.0    | 0.0    | 0.0    | 0.0       | 0.6618         | 0.6672      | 1.0                | 1              | 1              | 62.0                | 0.0                                |
| 2.5689        | 9.0   | 747  | 15.0760         | 0.0    | 0.0    | 0.0    | 0.0       | 0.6591         | 0.6651      | 1.0                | 1              | 1              | 62.0                | 0.0                                |
| 2.5508        | 10.0  | 830  | 15.6936         | 0.0    | 0.0    | 0.0    | 0.0       | 0.6649         | 0.6716      | 1.0                | 1              | 1              | 62.0                | 0.0                                |
| 2.5298        | 11.0  | 913  | 16.8446         | 0.0    | 0.0    | 0.0    | 0.0       | 0.6604         | 0.6648      | 1.0                | 1              | 1              | 62.0                | 0.0                                |
| 2.5091        | 12.0  | 996  | 21.0673         | 0.0    | 0.0    | 0.0    | 0.0       | 0.6721         | 0.6702      | 1.0                | 1              | 1              | 62.0                | 0.0                                |
| 2.5019        | 13.0  | 1079 | 25.5628         | 0.0    | 0.0    | 0.0    | 0.0       | 0.6605         | 0.67        | 1.0                | 1              | 1              | 62.0                | 0.0                                |
| 2.4826        | 14.0  | 1162 | 25.1203         | 0.0    | 0.0    | 0.0    | 0.0       | 0.6725         | 0.6666      | 1.0                | 1              | 1              | 62.0                | 0.0                                |
| 2.4693        | 15.0  | 1245 | 26.8982         | 0.0    | 0.0    | 0.0    | 0.0       | 0.6649         | 0.672       | 1.0                | 1              | 1              | 62.0                | 0.0                                |


### Framework versions

- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3