---
base_model: google/pegasus-xsum
tags:
- generated_from_trainer
model-index:
- name: pegasus-legalease
  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. -->

# pegasus-legalease

This model is a fine-tuned version of [google/pegasus-xsum](https://huggingface.co/google/pegasus-xsum) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3075

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 0.09  | 250  | 4.8425          |
| 5.1341        | 0.18  | 500  | 4.4270          |
| 5.1341        | 0.27  | 750  | 2.3842          |
| 3.085         | 0.35  | 1000 | 1.4872          |
| 3.085         | 0.44  | 1250 | 1.4106          |
| 1.5869        | 0.53  | 1500 | 1.3878          |
| 1.5869        | 0.62  | 1750 | 1.3722          |
| 1.4772        | 0.71  | 2000 | 1.3606          |
| 1.4772        | 0.8   | 2250 | 1.3496          |
| 1.4554        | 0.89  | 2500 | 1.3444          |
| 1.4554        | 0.98  | 2750 | 1.3373          |
| 1.446         | 1.06  | 3000 | 1.3315          |
| 1.446         | 1.15  | 3250 | 1.3261          |
| 1.3998        | 1.24  | 3500 | 1.3219          |
| 1.3998        | 1.33  | 3750 | 1.3195          |
| 1.3779        | 1.42  | 4000 | 1.3160          |
| 1.3779        | 1.51  | 4250 | 1.3143          |
| 1.4063        | 1.6   | 4500 | 1.3120          |
| 1.4063        | 1.68  | 4750 | 1.3105          |
| 1.3697        | 1.77  | 5000 | 1.3092          |
| 1.3697        | 1.86  | 5250 | 1.3080          |
| 1.3879        | 1.95  | 5500 | 1.3075          |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2