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 |