transformers tensorboard safetensors t5 text2text-generation generated_from_trainer base_model:google-t5/t5-small license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
---
license: apache-2.0
base_model: google-t5/t5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: my_fine_tuning_billsum_model_hf
  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_fine_tuning_billsum_model_hf

This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co/google-t5/t5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4322
- Rouge1: 0.1736
- Rouge2: 0.0757
- Rougel: 0.1462
- Rougelsum: 0.1461
- 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: 8
- eval_batch_size: 8
- 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   | 124  | 2.6266          | 0.1278 | 0.0413 | 0.1075 | 0.1076    | 19.0    |
| No log        | 2.0   | 248  | 2.4912          | 0.1468 | 0.0534 | 0.122  | 0.1218    | 19.0    |
| No log        | 3.0   | 372  | 2.4453          | 0.1663 | 0.0702 | 0.1393 | 0.1393    | 19.0    |
| No log        | 4.0   | 496  | 2.4322          | 0.1736 | 0.0757 | 0.1462 | 0.1461    | 19.0    |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.15.2
