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

# Social_Principal_PegasusLargeModel

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: 5.7293
- Rouge1: 42.5669
- Rouge2: 11.7234
- Rougel: 27.7786
- Rougelsum: 39.618
- Bertscore Precision: 77.477
- Bertscore Recall: 80.953
- Bertscore F1: 79.1718
- Bleu: 0.0783
- Gen Len: 193.5630

## 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 | Bertscore Precision | Bertscore Recall | Bertscore F1 | Bleu   | Gen Len  |
|:-------------:|:------:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------------------:|:----------------:|:------------:|:------:|:--------:|
| 6.8026        | 0.1314 | 100  | 6.4616          | 31.6892 | 6.7933  | 21.4758 | 29.2175   | 74.4637             | 79.3128          | 76.8049      | 0.0458 | 193.5630 |
| 6.3765        | 0.2628 | 200  | 6.1464          | 36.2413 | 9.2779  | 25.1904 | 33.7712   | 75.7773             | 80.0271          | 77.837       | 0.0618 | 193.5630 |
| 6.2227        | 0.3943 | 300  | 6.0317          | 39.5034 | 10.6245 | 26.455  | 36.7119   | 76.6932             | 80.4692          | 78.5301      | 0.0712 | 193.5630 |
| 6.125         | 0.5257 | 400  | 5.9252          | 39.3613 | 10.6879 | 26.5658 | 36.6574   | 76.7781             | 80.5732          | 78.6239      | 0.0723 | 193.5630 |
| 5.9687        | 0.6571 | 500  | 5.8381          | 40.3723 | 10.95   | 26.9783 | 37.6384   | 76.8811             | 80.6213          | 78.7007      | 0.0733 | 193.5630 |
| 5.9196        | 0.7885 | 600  | 5.7625          | 41.4841 | 11.4949 | 27.417  | 38.6113   | 77.0166             | 80.822           | 78.8674      | 0.0773 | 193.5630 |
| 5.898         | 0.9199 | 700  | 5.7293          | 42.5669 | 11.7234 | 27.7786 | 39.618    | 77.477              | 80.953           | 79.1718      | 0.0783 | 193.5630 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.2.1
- Tokenizers 0.19.1