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

# Physical_MainSections_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: 5.4319
- Rouge1: 45.5252
- Rouge2: 14.1464
- Rougel: 31.4229
- Rougelsum: 41.3858
- Bertscore Precision: 79.0611
- Bertscore Recall: 82.0495
- Bertscore F1: 80.5201
- Bleu: 0.0938
- Gen Len: 192.3440

## 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  |
|:-------------:|:------:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------------------:|:----------------:|:------------:|:------:|:--------:|
| 6.7243        | 0.0622 | 100  | 6.4316          | 35.9433 | 8.9384  | 23.9375 | 31.9391   | 75.7874             | 79.9159          | 77.7871      | 0.0555 | 192.3440 |
| 6.3971        | 0.1244 | 200  | 6.0845          | 38.3256 | 10.9703 | 27.2908 | 34.7128   | 76.6783             | 80.6127          | 78.5859      | 0.0706 | 192.3440 |
| 6.2761        | 0.1866 | 300  | 5.9553          | 40.7647 | 12.2223 | 28.45   | 36.7148   | 77.1954             | 81.0751          | 79.0774      | 0.0807 | 192.3440 |
| 6.0434        | 0.2489 | 400  | 5.8472          | 42.1277 | 12.5854 | 29.1212 | 37.9861   | 77.5784             | 81.2781          | 79.3756      | 0.0839 | 192.3440 |
| 6.0126        | 0.3111 | 500  | 5.7596          | 42.3736 | 12.8329 | 29.4128 | 38.3711   | 77.6752             | 81.4031          | 79.4859      | 0.0852 | 192.3440 |
| 5.9705        | 0.3733 | 600  | 5.6999          | 42.782  | 13.0394 | 29.6295 | 38.5859   | 77.6255             | 81.462           | 79.4875      | 0.0864 | 192.3440 |
| 5.8576        | 0.4355 | 700  | 5.6527          | 43.1782 | 13.1374 | 29.8607 | 39.0053   | 77.9976             | 81.5732          | 79.7363      | 0.0872 | 192.3440 |
| 5.8948        | 0.4977 | 800  | 5.6187          | 43.6171 | 13.2343 | 30.0467 | 39.4409   | 78.0197             | 81.5872          | 79.7542      | 0.0869 | 192.3440 |
| 5.8581        | 0.5599 | 900  | 5.5710          | 44.6985 | 13.6521 | 30.6142 | 40.4634   | 78.5325             | 81.7996          | 80.1244      | 0.0900 | 192.3440 |
| 5.669         | 0.6222 | 1000 | 5.5349          | 45.0937 | 13.8618 | 30.8512 | 40.8417   | 78.6878             | 81.9065          | 80.2571      | 0.0919 | 192.3440 |
| 5.6482        | 0.6844 | 1100 | 5.5042          | 45.0894 | 13.9336 | 31.0576 | 41.0813   | 78.9344             | 81.9388          | 80.4013      | 0.0927 | 192.3440 |
| 5.8084        | 0.7466 | 1200 | 5.4730          | 44.4944 | 13.6928 | 30.9811 | 40.6992   | 78.8689             | 81.8742          | 80.3361      | 0.0910 | 192.3440 |
| 5.6847        | 0.8088 | 1300 | 5.4582          | 45.1825 | 14.0216 | 31.2665 | 41.128    | 79.0426             | 81.9989          | 80.4862      | 0.0928 | 192.3440 |
| 5.6545        | 0.8710 | 1400 | 5.4444          | 45.5502 | 14.1713 | 31.3938 | 41.3877   | 79.0623             | 82.0733          | 80.5322      | 0.0942 | 192.3440 |
| 5.5869        | 0.9332 | 1500 | 5.4363          | 45.545  | 14.1516 | 31.4241 | 41.4205   | 79.1346             | 82.0625          | 80.5647      | 0.0939 | 192.3440 |
| 5.7046        | 0.9955 | 1600 | 5.4319          | 45.5252 | 14.1464 | 31.4229 | 41.3858   | 79.0611             | 82.0495          | 80.5201      | 0.0938 | 192.3440 |


### Framework versions

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