|
--- |
|
language: |
|
- en |
|
license: apache-2.0 |
|
tags: |
|
- summarization |
|
- generated_from_trainer |
|
datasets: |
|
- multi_news |
|
metrics: |
|
- rouge |
|
base_model: facebook/bart-base |
|
model-index: |
|
- name: bart-base-multi-news |
|
results: |
|
- task: |
|
type: text2text-generation |
|
name: Sequence-to-sequence Language Modeling |
|
dataset: |
|
name: multi_news |
|
type: multi_news |
|
config: default |
|
split: validation |
|
args: default |
|
metrics: |
|
- type: rouge |
|
value: 26.31 |
|
name: Rouge1 |
|
- type: rouge |
|
value: 9.6 |
|
name: Rouge2 |
|
- type: rouge |
|
value: 20.87 |
|
name: Rougel |
|
- type: rouge |
|
value: 21.54 |
|
name: Rougelsum |
|
--- |
|
|
|
<!-- 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-multi-news |
|
|
|
This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the multi_news dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 2.4147 |
|
- Rouge1: 26.31 |
|
- Rouge2: 9.6 |
|
- Rougel: 20.87 |
|
- Rougelsum: 21.54 |
|
|
|
## Intended uses & limitations |
|
|
|
The inteded use of this model is text summarization. |
|
The model requires additional training in order to perform better in the task of summarization. |
|
|
|
## Training and evaluation data |
|
|
|
The training data were 10000 samples from the multi-news training dataset |
|
and the evaluation data were 500 samples from the multi-news evaluation dataset |
|
|
|
## Training procedure |
|
|
|
For the training procedure the Seq2SeqTrainer class was used from the transformers library. |
|
|
|
### Training hyperparameters |
|
|
|
The Hyperparameters were passed to the Seq2SeqTrainingArguments class from the transformers library. |
|
|
|
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: 1 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:| |
|
| 2.4041 | 1.0 | 1250 | 2.4147 | 26.31 | 9.6 | 20.87 | 21.54 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.30.0 |
|
- Pytorch 2.0.1+cu118 |
|
- Datasets 2.12.0 |
|
- Tokenizers 0.13.3 |
