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---
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
datasets:
- billsum
metrics:
- rouge
model-index:
- name: my_awesome_billsum_model
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: 0.2014
---
<!-- 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 billsum dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2453
- Rouge1: 0.2014
- Rouge2: 0.1012
- Rougel: 0.1696
- Rougelsum: 0.1698
- 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: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log | 1.0 | 124 | 2.5661 | 0.1328 | 0.0422 | 0.1082 | 0.1083 | 19.0 |
| No log | 2.0 | 248 | 2.4215 | 0.1686 | 0.0704 | 0.139 | 0.1391 | 19.0 |
| No log | 3.0 | 372 | 2.3551 | 0.1994 | 0.0994 | 0.1669 | 0.1667 | 19.0 |
| No log | 4.0 | 496 | 2.3135 | 0.2021 | 0.1018 | 0.1701 | 0.17 | 19.0 |
| 2.7983 | 5.0 | 620 | 2.2911 | 0.2019 | 0.103 | 0.1703 | 0.1705 | 19.0 |
| 2.7983 | 6.0 | 744 | 2.2719 | 0.2015 | 0.1023 | 0.1707 | 0.1708 | 19.0 |
| 2.7983 | 7.0 | 868 | 2.2597 | 0.2008 | 0.1013 | 0.1691 | 0.1693 | 19.0 |
| 2.7983 | 8.0 | 992 | 2.2515 | 0.2016 | 0.1016 | 0.1695 | 0.1697 | 19.0 |
| 2.4664 | 9.0 | 1116 | 2.2467 | 0.2017 | 0.1016 | 0.1696 | 0.1698 | 19.0 |
| 2.4664 | 10.0 | 1240 | 2.2453 | 0.2014 | 0.1012 | 0.1696 | 0.1698 | 19.0 |
### Framework versions
- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
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