---
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: pegasus-legalease
  results: []
datasets:
- hheiden/us-congress-117-bills
---

<!-- 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. -->

# pegasus-legalease

This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 4.2373
- Rouge1: 0.4847
- Rouge2: 0.3225
- Rougel: 0.4194
- Rougelsum: 0.4177
- Gen Len: 43.02

## 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: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 5.2738        | 1.0   | 125  | 4.6004          | 0.4363 | 0.2769 | 0.375  | 0.3743    | 37.24   |
| 4.8164        | 2.0   | 250  | 4.4350          | 0.464  | 0.3085 | 0.405  | 0.4038    | 40.3    |
| 4.8494        | 3.0   | 375  | 4.3372          | 0.473  | 0.3153 | 0.412  | 0.41      | 41.2    |
| 4.6062        | 4.0   | 500  | 4.2669          | 0.4791 | 0.3196 | 0.4159 | 0.4141    | 43.03   |
| 4.5682        | 5.0   | 625  | 4.2373          | 0.4847 | 0.3225 | 0.4194 | 0.4177    | 43.02   |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2