metadata
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
CS685-text-summarizer-2
This model is a fine-tuned version of 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