---
license: apache-2.0
base_model: google-t5/t5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: billsum_236_t5-base
  results: []
---

<!-- 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. -->

# billsum_236_t5-base

This model is a fine-tuned version of [google-t5/t5-base](https://huggingface.co/google-t5/t5-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1143
- Rouge1: 0.1513
- Rouge2: 0.0546
- Rougel: 0.1244
- Rougelsum: 0.1245
- Gen Len: 18.979

## 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: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 1.2695        | 1.69  | 500  | 2.1398          | 0.157  | 0.0611 | 0.1279 | 0.1279    | 19.0    |
| 1.1033        | 3.38  | 1000 | 2.1182          | 0.1582 | 0.0629 | 0.1296 | 0.1297    | 18.9984 |
| 1.1178        | 5.07  | 1500 | 2.1133          | 0.1551 | 0.0594 | 0.1275 | 0.1277    | 18.979  |
| 1.0399        | 6.75  | 2000 | 2.1171          | 0.1538 | 0.058  | 0.1266 | 0.1266    | 18.9887 |
| 1.0364        | 8.44  | 2500 | 2.1143          | 0.1513 | 0.0546 | 0.1244 | 0.1245    | 18.979  |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.0.1+cu117
- Datasets 2.15.0
- Tokenizers 0.15.0