---
license: mit
base_model: facebook/bart-large-xsum
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: text_shortening_model_v35
  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_v35

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: 2.1783
- Rouge1: 0.4993
- Rouge2: 0.2724
- Rougel: 0.4472
- Rougelsum: 0.4467
- Bert precision: 0.8744
- Bert recall: 0.8769
- Average word count: 8.6096
- Max word count: 20
- Min word count: 5
- Average token count: 14.97
- % shortened texts with length > 12: 3.6036

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:--------------:|:-----------:|:------------------:|:--------------:|:--------------:|:-------------------:|:----------------------------------:|
| 1.83          | 1.0   | 37   | 1.9642          | 0.457  | 0.2329 | 0.4049 | 0.4054    | 0.8677         | 0.8663      | 8.027              | 13             | 4              | 16.6607             | 2.7027                             |
| 0.8629        | 2.0   | 74   | 1.6943          | 0.5268 | 0.3019 | 0.4695 | 0.4697    | 0.8758         | 0.8901      | 10.0571            | 19             | 5              | 17.8258             | 19.2192                            |
| 0.7849        | 3.0   | 111  | 1.6564          | 0.5001 | 0.279  | 0.4553 | 0.4554    | 0.873          | 0.8805      | 8.9099             | 17             | 5              | 15.4865             | 5.1051                             |
| 0.6116        | 4.0   | 148  | 1.7559          | 0.4638 | 0.2376 | 0.4183 | 0.4188    | 0.863          | 0.8665      | 8.4414             | 15             | 4              | 13.8829             | 0.9009                             |
| 0.3976        | 5.0   | 185  | 1.6708          | 0.4999 | 0.2723 | 0.4481 | 0.4481    | 0.8744         | 0.8766      | 8.5556             | 16             | 5              | 14.6877             | 3.9039                             |
| 0.2977        | 6.0   | 222  | 1.7196          | 0.4937 | 0.2699 | 0.4376 | 0.4379    | 0.8684         | 0.877       | 9.1652             | 20             | 5              | 15.3964             | 5.7057                             |
| 0.2187        | 7.0   | 259  | 1.7942          | 0.5129 | 0.2905 | 0.4572 | 0.4575    | 0.8765         | 0.8803      | 8.7117             | 19             | 5              | 14.6306             | 3.9039                             |
| 0.1603        | 8.0   | 296  | 1.8003          | 0.4822 | 0.2538 | 0.4237 | 0.4229    | 0.8688         | 0.8722      | 8.6306             | 19             | 5              | 15.4474             | 5.7057                             |
| 0.1175        | 9.0   | 333  | 2.0138          | 0.5024 | 0.2798 | 0.4486 | 0.4475    | 0.8742         | 0.8791      | 8.7988             | 19             | 5              | 16.1471             | 6.6066                             |
| 0.0859        | 10.0  | 370  | 2.1783          | 0.4993 | 0.2724 | 0.4472 | 0.4467    | 0.8744         | 0.8769      | 8.6096             | 20             | 5              | 14.97               | 3.6036                             |


### Framework versions

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