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---
license: apache-2.0
base_model: t5-base
tags:
- generated_from_trainer
datasets:
- billsum
metrics:
- rouge
model-index:
- name: yingchuanong_582_team_summarization
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: 0.2039
---
<!-- 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. -->
# yingchuanong_582_team_summarization
This model is a fine-tuned version of [t5-base](https://huggingface.co./t5-base) on the billsum dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8978
- Rouge1: 0.2039
- Rouge2: 0.1189
- Rougel: 0.1798
- Rougelsum: 0.1798
- 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: 4
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log | 1.0 | 124 | 2.0176 | 0.2024 | 0.1102 | 0.175 | 0.1747 | 19.0 |
| No log | 2.0 | 248 | 1.9361 | 0.2033 | 0.1146 | 0.1773 | 0.1771 | 19.0 |
| No log | 3.0 | 372 | 1.9046 | 0.2038 | 0.1184 | 0.1792 | 0.1791 | 19.0 |
| No log | 4.0 | 496 | 1.8978 | 0.2039 | 0.1189 | 0.1798 | 0.1798 | 19.0 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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