|
|
--- |
|
|
license: apache-2.0 |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
datasets: |
|
|
- pubmed-summarization |
|
|
metrics: |
|
|
- rouge |
|
|
model-index: |
|
|
- name: my_awesome_billsum_model |
|
|
results: |
|
|
- task: |
|
|
name: Sequence-to-sequence Language Modeling |
|
|
type: text2text-generation |
|
|
dataset: |
|
|
name: pubmed-summarization |
|
|
type: pubmed-summarization |
|
|
config: section |
|
|
split: test |
|
|
args: section |
|
|
metrics: |
|
|
- name: Rouge1 |
|
|
type: rouge |
|
|
value: 0.1393 |
|
|
--- |
|
|
|
|
|
<!-- 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. --> |
|
|
|
|
|
# my_awesome_billsum_model |
|
|
|
|
|
This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the pubmed-summarization dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 2.3423 |
|
|
- Rouge1: 0.1393 |
|
|
- Rouge2: 0.0556 |
|
|
- Rougel: 0.1172 |
|
|
- Rougelsum: 0.1172 |
|
|
- Gen Len: 19.0 |
|
|
|
|
|
## 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: 2e-05 |
|
|
- train_batch_size: 16 |
|
|
- eval_batch_size: 16 |
|
|
- seed: 42 |
|
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
|
- lr_scheduler_type: linear |
|
|
- num_epochs: 2 |
|
|
- mixed_precision_training: Native AMP |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
|
|
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
|
|
| No log | 1.0 | 375 | 2.3755 | 0.1375 | 0.0538 | 0.1159 | 0.1159 | 19.0 | |
|
|
| 2.6739 | 2.0 | 750 | 2.3423 | 0.1393 | 0.0556 | 0.1172 | 0.1172 | 19.0 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.27.4 |
|
|
- Pytorch 1.13.1+cu116 |
|
|
- Datasets 2.11.0 |
|
|
- Tokenizers 0.13.2 |
|
|
|
