---
library_name: transformers
base_model: google/pegasus-large
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: Fine-Tuned-billsum-Summarization
  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. -->

# Fine-Tuned-billsum-Summarization

This model is a fine-tuned version of [google/pegasus-large](https://huggingface.co/google/pegasus-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8618
- Rouge1: 0.2169
- Rouge2: 0.0916
- Rougel: 0.1809
- Rougelsum: 0.1799
- Generated Length: 104.8158

## 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
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Generated Length |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:----------------:|
| No log        | 1.0   | 19   | 2.3003          | 0.2218 | 0.0946 | 0.1807 | 0.1792    | 106.5789         |
| No log        | 2.0   | 38   | 1.9734          | 0.2164 | 0.0922 | 0.1799 | 0.1789    | 104.4474         |
| No log        | 3.0   | 57   | 1.8618          | 0.2169 | 0.0916 | 0.1809 | 0.1799    | 104.8158         |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1