license: apache-2.0 | |
tags: | |
- summarization | |
- generated_from_trainer | |
datasets: | |
- billsum | |
metrics: | |
- rouge | |
model-index: | |
- name: billsum-full-data | |
results: | |
- task: | |
name: Sequence-to-sequence Language Modeling | |
type: text2text-generation | |
dataset: | |
name: billsum | |
type: billsum | |
config: default | |
split: train[:95%] | |
args: default | |
metrics: | |
- name: Rouge1 | |
type: rouge | |
value: 18.0383 | |
<!-- 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. --> | |
# billsum-full-data | |
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: 1.6583 | |
- Rouge1: 18.0383 | |
- Rouge2: 14.8462 | |
- Rougel: 17.6086 | |
- Rougelsum: 17.6843 | |
## 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: 5e-05 | |
- train_batch_size: 2 | |
- eval_batch_size: 2 | |
- seed: 42 | |
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
- lr_scheduler_type: linear | |
- num_epochs: 3 | |
### Training results | |
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | | |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:| | |
| 2.1401 | 1.0 | 8101 | 1.8087 | 17.8461 | 14.6015 | 17.3956 | 17.4842 | | |
| 1.7596 | 2.0 | 16202 | 1.6980 | 18.0568 | 14.7833 | 17.6068 | 17.6999 | | |
| 1.5789 | 3.0 | 24303 | 1.6583 | 18.0383 | 14.8462 | 17.6086 | 17.6843 | | |
### Framework versions | |
- Transformers 4.29.1 | |
- Pytorch 2.0.0 | |
- Datasets 2.12.0 | |
- Tokenizers 0.13.3 | |