---
license: apache-2.0
base_model: t5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: text_shortening_model_v61
  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_v61

This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7370
- Rouge1: 0.6559
- Rouge2: 0.469
- Rougel: 0.6075
- Rougelsum: 0.6079
- Bert precision: 0.9075
- Bert recall: 0.9017
- Bert f1-score: 0.9041
- Average word count: 7.9152
- Max word count: 15
- Min word count: 3
- Average token count: 12.1741
- % shortened texts with length > 12: 6.6964

## 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: 1e-05
- 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Bert precision | Bert recall | Bert f1-score | Average word count | Max word count | Min word count | Average token count | % shortened texts with length > 12 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:--------------:|:-----------:|:-------------:|:------------------:|:--------------:|:--------------:|:-------------------:|:----------------------------------:|
| 2.2731        | 1.0   | 49   | 1.3305          | 0.3966 | 0.2328 | 0.3397 | 0.3396    | 0.7258         | 0.7385      | 0.7316        | 9.3438             | 19             | 0              | 16.3929             | 28.5714                            |
| 1.3225        | 2.0   | 98   | 0.9829          | 0.6051 | 0.422  | 0.5558 | 0.5557    | 0.8863         | 0.879       | 0.8822        | 8.0491             | 17             | 0              | 12.6607             | 8.0357                             |
| 1.0933        | 3.0   | 147  | 0.8678          | 0.6346 | 0.4487 | 0.5869 | 0.5875    | 0.9012         | 0.8928      | 0.8965        | 7.8527             | 15             | 0              | 12.1607             | 5.8036                             |
| 0.9836        | 4.0   | 196  | 0.8145          | 0.6404 | 0.449  | 0.5911 | 0.5918    | 0.9034         | 0.8971      | 0.8997        | 8.0179             | 15             | 3              | 12.1964             | 8.4821                             |
| 0.9182        | 5.0   | 245  | 0.7860          | 0.647  | 0.4598 | 0.597  | 0.5974    | 0.9055         | 0.8989      | 0.9017        | 7.8884             | 15             | 3              | 12.1116             | 7.1429                             |
| 0.8756        | 6.0   | 294  | 0.7659          | 0.6479 | 0.4606 | 0.5999 | 0.5996    | 0.9054         | 0.8982      | 0.9013        | 7.8839             | 15             | 3              | 12.1205             | 7.1429                             |
| 0.84          | 7.0   | 343  | 0.7517          | 0.6544 | 0.4688 | 0.6062 | 0.6061    | 0.9067         | 0.9008      | 0.9033        | 7.9196             | 15             | 3              | 12.1741             | 7.1429                             |
| 0.8256        | 8.0   | 392  | 0.7424          | 0.6515 | 0.4644 | 0.6033 | 0.6033    | 0.9068         | 0.9001      | 0.903         | 7.8705             | 15             | 3              | 12.1473             | 6.25                               |
| 0.8198        | 9.0   | 441  | 0.7386          | 0.656  | 0.469  | 0.6076 | 0.608     | 0.9076         | 0.9017      | 0.9041        | 7.9107             | 15             | 3              | 12.1696             | 6.6964                             |
| 0.8058        | 10.0  | 490  | 0.7370          | 0.6559 | 0.469  | 0.6075 | 0.6079    | 0.9075         | 0.9017      | 0.9041        | 7.9152             | 15             | 3              | 12.1741             | 6.6964                             |


### Framework versions

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