transformers safetensors t5 text2text-generation generated_from_trainer base_model:t5-small license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
---
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: my_awesome_billsum_model
  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. -->

# my_awesome_billsum_model

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3056
- Rouge1: 0.1977
- Rouge2: 0.0989
- Rougel: 0.171
- Rougelsum: 0.1712
- 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: 2
- eval_batch_size: 2
- 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   | 495  | 2.4452          | 0.1804 | 0.0829 | 0.1538 | 0.1538    | 19.0    |
| 2.9368        | 2.0   | 990  | 2.3497          | 0.1982 | 0.0983 | 0.171  | 0.171     | 19.0    |
| 2.5685        | 3.0   | 1485 | 2.3170          | 0.1988 | 0.0998 | 0.1711 | 0.1715    | 19.0    |
| 2.4993        | 4.0   | 1980 | 2.3056          | 0.1977 | 0.0989 | 0.171  | 0.1712    | 19.0    |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.0.1+cu117
- Datasets 2.15.0
- Tokenizers 0.15.0
