|
|
--- |
|
|
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 |
|
|
|
