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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- billsum
metrics:
- rouge
base_model: t5-small
model-index:
- name: txt_summary_model
results:
- task:
type: text2text-generation
name: Sequence-to-sequence Language Modeling
dataset:
name: billsum
type: billsum
config: default
split: ca_test
args: default
metrics:
- type: rouge
value: 0.1389
name: Rouge1
---
<!-- 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. -->
# txt_summary_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: 2.5514
- Rouge1: 0.1389
- Rouge2: 0.0536
- Rougel: 0.1181
- Rougelsum: 0.1176
- 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: 4
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log | 1.0 | 62 | 2.8496 | 0.1231 | 0.0345 | 0.1031 | 0.103 | 19.0 |
| No log | 2.0 | 124 | 2.6339 | 0.1302 | 0.0452 | 0.1107 | 0.1105 | 19.0 |
| No log | 3.0 | 186 | 2.5686 | 0.1373 | 0.0518 | 0.1163 | 0.1158 | 19.0 |
| No log | 4.0 | 248 | 2.5514 | 0.1389 | 0.0536 | 0.1181 | 0.1176 | 19.0 |
### Framework versions
- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
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