| --- |
| license: apache-2.0 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - rouge |
| model-index: |
| - name: mbarthez-copy_mechanism-hal_articles |
| results: |
| - task: |
| name: Summarization |
| type: summarization |
| metrics: |
| - name: Rouge1 |
| type: rouge |
| value: 36.548 |
| --- |
| |
| <!-- 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. --> |
|
|
| # mbarthez-davide_articles-copy_enhanced |
|
|
| This model is a fine-tuned version of [moussaKam/mbarthez](https://huggingface.co/moussaKam/mbarthez) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.4905 |
| - Rouge1: 36.548 |
| - Rouge2: 19.6282 |
| - Rougel: 30.2513 |
| - Rougelsum: 30.2765 |
| - Gen Len: 25.7238 |
|
|
| ## 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: 3e-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: 3.0 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
| |:-------------:|:-----:|:------:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:| |
| | 1.6706 | 1.0 | 33552 | 1.5690 | 31.2477 | 16.5455 | 26.9855 | 26.9754 | 18.6217 | |
| | 1.3446 | 2.0 | 67104 | 1.5060 | 32.1108 | 17.1408 | 27.7833 | 27.7703 | 18.9115 | |
| | 1.3245 | 3.0 | 100656 | 1.4905 | 32.9084 | 17.7027 | 28.2912 | 28.2975 | 18.9801 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.10.2 |
| - Pytorch 1.7.1+cu110 |
| - Datasets 1.11.0 |
| - Tokenizers 0.10.3 |
|
|
