| --- |
| 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 |
| --- |
| |
| <!-- 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. --> |
|
|
| # 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 |
