transformers tensorboard safetensors t5 text2text-generation summarization generated_from_trainer base_model:google-t5/t5-small base_model:finetune:google-t5/t5-small license:apache-2.0 autotrain_compatible text-generation-inference endpoints_compatible region:us
---
base_model: t5-small
library_name: transformers
license: apache-2.0
metrics:
- rouge
tags:
- summarization
- generated_from_trainer
model-index:
- name: centralized-t5-small-billsum
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# centralized-t5-small-billsum

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: 1.9874
- Rouge1: 0.4956
- Rouge2: 0.2837
- Rougel: 0.3864
- Rougelsum: 0.4313

## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 2.5537        | 1.0   | 1125 | 2.1315          | 0.4851 | 0.2755 | 0.3751 | 0.4149    |
| 2.2928        | 2.0   | 2250 | 2.0491          | 0.4919 | 0.2806 | 0.3827 | 0.4267    |
| 2.2293        | 3.0   | 3375 | 2.0110          | 0.4919 | 0.2829 | 0.3845 | 0.4271    |
| 2.199         | 4.0   | 4500 | 1.9935          | 0.4937 | 0.2834 | 0.3841 | 0.4289    |
| 2.1853        | 5.0   | 5625 | 1.9874          | 0.4956 | 0.2837 | 0.3864 | 0.4313    |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
