transformers pytorch safetensors bart text2text-generation summarization generated_from_trainer en dataset:EasyTerms/Manuel_dataset license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
tags:
- summarization
- generated_from_trainer
metrics:
- rouge
model-index:
- name: etsummerizer_v2
  results: []
datasets:
- EasyTerms/Manuel_dataset
language:
- en
library_name: transformers
pipeline_tag: summarization
---

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# etsummerizer_v2

This model is a fine-tuned version of [sshleifer/distilbart-cnn-12-6](https://huggingface.co/sshleifer/distilbart-cnn-12-6) on [EasyTerms/Manuel_dataset](https://huggingface.co/datasets/EasyTerms/Manuel_dataset).
It achieves the following results on the evaluation set:
- Loss: 0.3484
- Rouge1: 0.5448
- Rouge2: 0.3092
- Rougel: 0.4363
- Rougelsum: 0.4370

## Model description

This model was finetuned on legal text extracted from different terms and conditions documents. Its objective is to efficiently summerize such text and present the generation
in a simplified version lacking in legal jargon.

## Intended uses & limitations

As it is the second version of this model it effectively summerize legal text however, further training will be required to improve the simplification task.

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 3.5           | 1.0   | 30   | 0.5565          | 0.5111 | 0.2863 | 0.4092 | 0.4093    |
| 0.3056        | 2.0   | 60   | 0.3612          | 0.5267 | 0.3021 | 0.4277 | 0.4286    |
| 0.1716        | 3.0   | 90   | 0.3484          | 0.5448 | 0.3092 | 0.4363 | 0.4370    |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.0+cpu
- Datasets 2.1.0
- Tokenizers 0.13.3