| --- |
| license: apache-2.0 |
| tags: |
| - summarization |
| - generated_from_trainer |
| datasets: |
| - xsum |
| metrics: |
| - rouge |
| model-index: |
| - name: bart-base-facebook |
| results: |
| - task: |
| name: Sequence-to-sequence Language Modeling |
| type: text2text-generation |
| dataset: |
| name: xsum |
| type: xsum |
| config: default |
| split: train |
| args: default |
| metrics: |
| - name: Rouge1 |
| type: rouge |
| value: 0.7146 |
| --- |
| |
| <!-- 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-facebook |
|
|
| This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the xsum dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 2.1877 |
| - Rouge1: 0.7146 |
| - Rouge2: 0.3305 |
| - Rougel: 0.2988 |
| - Rougelsum: 0.6822 |
|
|
| ## 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: 10 |
| - eval_batch_size: 10 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 5 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
| |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:| |
| | 2.505 | 1.0 | 1359 | 2.1048 | 0.6788 | 0.3022 | 0.2843 | 0.6497 | |
| | 2.0216 | 2.0 | 2718 | 2.1010 | 0.7022 | 0.3182 | 0.2974 | 0.672 | |
| | 1.7088 | 3.0 | 4077 | 2.1228 | 0.7048 | 0.3214 | 0.2968 | 0.6722 | |
| | 1.4778 | 4.0 | 5436 | 2.1655 | 0.7117 | 0.325 | 0.2984 | 0.6786 | |
| | 1.3161 | 5.0 | 6795 | 2.1877 | 0.7146 | 0.3305 | 0.2988 | 0.6822 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.22.2 |
| - Pytorch 1.12.1+cu113 |
| - Datasets 2.5.2 |
| - Tokenizers 0.12.1 |
|
|
