|
--- |
|
license: apache-2.0 |
|
tags: |
|
- summarization |
|
- generated_from_trainer |
|
datasets: |
|
- billsum |
|
metrics: |
|
- rouge |
|
model-index: |
|
- name: CS685-text-summarizer-2 |
|
results: |
|
- task: |
|
name: Sequence-to-sequence Language Modeling |
|
type: text2text-generation |
|
dataset: |
|
name: billsum |
|
type: billsum |
|
config: default |
|
split: train[:20%] |
|
args: default |
|
metrics: |
|
- name: Rouge1 |
|
type: rouge |
|
value: 17.1607 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# CS685-text-summarizer-2 |
|
|
|
This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the billsum dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.7651 |
|
- Rouge1: 17.1607 |
|
- Rouge2: 13.943 |
|
- Rougel: 16.6793 |
|
- Rougelsum: 16.8422 |
|
|
|
## 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: 6 |
|
- eval_batch_size: 6 |
|
- 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 | |
|
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:| |
|
| 2.4547 | 1.0 | 569 | 1.9895 | 16.6343 | 13.0432 | 16.1262 | 16.2449 | |
|
| 2.0246 | 2.0 | 1138 | 1.8688 | 16.939 | 13.4711 | 16.4359 | 16.5797 | |
|
| 1.818 | 3.0 | 1707 | 1.8075 | 17.1388 | 13.827 | 16.6136 | 16.7574 | |
|
| 1.6831 | 4.0 | 2276 | 1.7744 | 17.2292 | 13.9353 | 16.6961 | 16.8786 | |
|
| 1.5956 | 5.0 | 2845 | 1.7651 | 17.1607 | 13.943 | 16.6793 | 16.8422 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.28.0 |
|
- Pytorch 2.0.0+cu118 |
|
- Datasets 2.12.0 |
|
- Tokenizers 0.13.3 |
|
|
