transformers tensorboard 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_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_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: 2.5803
- Rouge1: 0.1414
- Rouge2: 0.0501
- Rougel: 0.1176
- 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
- training_steps: 200
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 3.9137        | 0.65  | 40   | 3.0404          | 0.1351 | 0.044  | 0.1138 | 0.114     | 19.0    |
| 3.0852        | 1.29  | 80   | 2.7349          | 0.1363 | 0.0453 | 0.1143 | 0.1144    | 19.0    |
| 2.9298        | 1.94  | 120  | 2.6341          | 0.1405 | 0.0471 | 0.1162 | 0.1164    | 19.0    |
| 2.8389        | 2.58  | 160  | 2.5929          | 0.1413 | 0.049  | 0.1176 | 0.118     | 19.0    |
| 2.8414        | 3.23  | 200  | 2.5803          | 0.1414 | 0.0501 | 0.1176 | 0.1176    | 19.0    |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1
