| | --- |
| | license: apache-2.0 |
| | base_model: facebook/bart-base |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - rouge |
| | model-index: |
| | - name: bart-base-finetuned-CNN-DailyNews |
| | 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. --> |
| |
|
| | # bart-base-finetuned-CNN-DailyNews |
| |
|
| | This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 1.8725 |
| | - Rouge1: 0.1807 |
| | - Rouge2: 0.1041 |
| | - Rougel: 0.1614 |
| | - Rougelsum: 0.1694 |
| |
|
| | ## 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: 5.6e-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: 8 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
| | |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:| |
| | | 2.6142 | 1.0 | 63 | 1.9661 | 0.1623 | 0.0912 | 0.1463 | 0.1523 | |
| | | 2.0578 | 2.0 | 126 | 1.8842 | 0.1865 | 0.1034 | 0.1643 | 0.1735 | |
| | | 1.7935 | 3.0 | 189 | 1.8447 | 0.1736 | 0.0951 | 0.1547 | 0.1623 | |
| | | 1.6412 | 4.0 | 252 | 1.8515 | 0.1863 | 0.1043 | 0.1636 | 0.1727 | |
| | | 1.4701 | 5.0 | 315 | 1.8509 | 0.1876 | 0.1072 | 0.1676 | 0.1758 | |
| | | 1.3969 | 6.0 | 378 | 1.8537 | 0.1828 | 0.1037 | 0.1627 | 0.1731 | |
| | | 1.2943 | 7.0 | 441 | 1.8540 | 0.183 | 0.1022 | 0.1629 | 0.1713 | |
| | | 1.2581 | 8.0 | 504 | 1.8725 | 0.1807 | 0.1041 | 0.1614 | 0.1694 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.41.2 |
| | - Pytorch 2.3.0+cu121 |
| | - Datasets 2.19.2 |
| | - Tokenizers 0.19.1 |
| |
|
