---
base_model: google/pegasus-large
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: LifePrincipalPegasusLarge
  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. -->

# LifePrincipalPegasusLarge

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: 5.6547
- Rouge1: 43.3679
- Rouge2: 10.9243
- Rougel: 27.4864
- Rougelsum: 40.3896
- Gen Len: 227.7642

## 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: 5e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len  |
|:-------------:|:------:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:--------:|
| 6.8795        | 0.0881 | 100  | 6.5014          | 32.7482 | 6.8933  | 21.4622 | 30.1026   | 227.7642 |
| 6.4726        | 0.1762 | 200  | 6.2112          | 37.0799 | 8.9306  | 24.652  | 34.5305   | 227.7642 |
| 6.2749        | 0.2643 | 300  | 6.0775          | 38.9836 | 9.7478  | 25.6809 | 36.2375   | 227.7642 |
| 6.2445        | 0.3524 | 400  | 5.9878          | 39.9961 | 10.0625 | 25.9686 | 37.4853   | 227.7642 |
| 6.1752        | 0.4405 | 500  | 5.8898          | 40.1077 | 10.1194 | 26.1056 | 37.4283   | 227.7642 |
| 6.0343        | 0.5286 | 600  | 5.8116          | 41.7626 | 10.4065 | 26.7348 | 38.9953   | 227.7642 |
| 6.0009        | 0.6167 | 700  | 5.7529          | 42.0869 | 10.5523 | 26.9037 | 39.3663   | 227.7642 |
| 5.9523        | 0.7048 | 800  | 5.7057          | 42.4863 | 10.6188 | 27.1573 | 39.6282   | 227.7642 |
| 5.9445        | 0.7929 | 900  | 5.6786          | 42.4071 | 10.6897 | 27.1549 | 39.5086   | 227.7642 |
| 5.8047        | 0.8810 | 1000 | 5.6646          | 43.4098 | 10.9746 | 27.4646 | 40.4014   | 227.7642 |
| 5.8718        | 0.9691 | 1100 | 5.6547          | 43.3679 | 10.9243 | 27.4864 | 40.3896   | 227.7642 |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.1.2
- Datasets 2.2.1
- Tokenizers 0.19.1