|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- billsum |
|
metrics: |
|
- rouge |
|
model-index: |
|
- name: 2_smtg |
|
results: |
|
- task: |
|
name: Sequence-to-sequence Language Modeling |
|
type: text2text-generation |
|
dataset: |
|
name: billsum |
|
type: billsum |
|
config: default |
|
split: ca_test |
|
args: default |
|
metrics: |
|
- name: Rouge1 |
|
type: rouge |
|
value: 0.1982 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# 2_smtg |
|
|
|
This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co/google/flan-t5-small) on the billsum dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.9346 |
|
- Rouge1: 0.1982 |
|
- Rouge2: 0.1052 |
|
- Rougel: 0.1709 |
|
- Rougelsum: 0.1711 |
|
- 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: 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: 20 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
|
| No log | 1.0 | 124 | 2.2154 | 0.1881 | 0.0892 | 0.1571 | 0.157 | 18.996 | |
|
| No log | 2.0 | 248 | 2.1455 | 0.2003 | 0.1039 | 0.1695 | 0.1696 | 19.0 | |
|
| No log | 3.0 | 372 | 2.0963 | 0.2011 | 0.1043 | 0.1706 | 0.1706 | 19.0 | |
|
| No log | 4.0 | 496 | 2.0696 | 0.2014 | 0.105 | 0.1708 | 0.1708 | 19.0 | |
|
| 2.4198 | 5.0 | 620 | 2.0437 | 0.1991 | 0.1016 | 0.1693 | 0.1694 | 19.0 | |
|
| 2.4198 | 6.0 | 744 | 2.0256 | 0.1983 | 0.1016 | 0.1694 | 0.1695 | 19.0 | |
|
| 2.4198 | 7.0 | 868 | 2.0109 | 0.2003 | 0.1044 | 0.1702 | 0.1705 | 19.0 | |
|
| 2.4198 | 8.0 | 992 | 1.9969 | 0.1981 | 0.1025 | 0.1692 | 0.1694 | 19.0 | |
|
| 2.2056 | 9.0 | 1116 | 1.9849 | 0.1984 | 0.103 | 0.1696 | 0.1699 | 19.0 | |
|
| 2.2056 | 10.0 | 1240 | 1.9738 | 0.1985 | 0.1032 | 0.1702 | 0.1704 | 19.0 | |
|
| 2.2056 | 11.0 | 1364 | 1.9661 | 0.1976 | 0.1029 | 0.1694 | 0.1697 | 19.0 | |
|
| 2.2056 | 12.0 | 1488 | 1.9591 | 0.1986 | 0.1038 | 0.1704 | 0.1706 | 19.0 | |
|
| 2.1209 | 13.0 | 1612 | 1.9535 | 0.1994 | 0.1045 | 0.1708 | 0.1709 | 19.0 | |
|
| 2.1209 | 14.0 | 1736 | 1.9486 | 0.1986 | 0.1047 | 0.1706 | 0.1708 | 19.0 | |
|
| 2.1209 | 15.0 | 1860 | 1.9440 | 0.1988 | 0.1053 | 0.1709 | 0.1711 | 19.0 | |
|
| 2.1209 | 16.0 | 1984 | 1.9406 | 0.1983 | 0.1057 | 0.1708 | 0.1709 | 19.0 | |
|
| 2.0754 | 17.0 | 2108 | 1.9378 | 0.199 | 0.1062 | 0.1712 | 0.1712 | 19.0 | |
|
| 2.0754 | 18.0 | 2232 | 1.9361 | 0.1986 | 0.1057 | 0.1713 | 0.1714 | 19.0 | |
|
| 2.0754 | 19.0 | 2356 | 1.9348 | 0.1986 | 0.1056 | 0.1712 | 0.1713 | 19.0 | |
|
| 2.0754 | 20.0 | 2480 | 1.9346 | 0.1982 | 0.1052 | 0.1709 | 0.1711 | 19.0 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.26.1 |
|
- Pytorch 1.13.1.post200 |
|
- Datasets 2.10.0 |
|
- Tokenizers 0.13.2 |
|
|
