---
base_model: google/pegasus-large
tags:
- generated_from_trainer
metrics:
- rouge
- bleu
model-index:
- name: LifeMainSectionsPegasusLargeModel
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# LifeMainSectionsPegasusLargeModel

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: 5.8222
- Rouge1: 42.8874
- Rouge2: 11.2364
- Rougel: 27.5064
- Rougelsum: 39.4117
- Bertscore Precision: 77.6554
- Bertscore Recall: 81.0536
- Bertscore F1: 79.3129
- Bleu: 0.0730
- Gen Len: 227.0514

## 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  |
|:-------------:|:------:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------------------:|:----------------:|:------------:|:------:|:--------:|
| 6.9298        | 0.0888 | 100  | 6.6509          | 32.8681 | 7.0176  | 21.3819 | 29.8291   | 74.6005             | 79.1172          | 76.7856      | 0.0454 | 227.0514 |
| 6.6156        | 0.1776 | 200  | 6.3485          | 36.1792 | 8.8919  | 24.1486 | 33.0206   | 75.7824             | 79.9379          | 77.7981      | 0.0585 | 227.0514 |
| 6.4148        | 0.2664 | 300  | 6.2282          | 39.2098 | 10.0222 | 25.6326 | 35.6      | 76.2724             | 80.3779          | 78.2642      | 0.0655 | 227.0514 |
| 6.3735        | 0.3552 | 400  | 6.1269          | 39.6145 | 10.3955 | 25.9037 | 36.142    | 76.2138             | 80.4372          | 78.2611      | 0.0675 | 227.0514 |
| 6.2031        | 0.4440 | 500  | 6.0437          | 40.2044 | 10.3808 | 26.2646 | 36.6302   | 76.3888             | 80.5312          | 78.3982      | 0.0674 | 227.0514 |
| 6.1976        | 0.5328 | 600  | 5.9679          | 41.4546 | 10.6953 | 26.6781 | 37.9643   | 76.9224             | 80.7265          | 78.7724      | 0.0695 | 227.0514 |
| 6.1576        | 0.6216 | 700  | 5.9134          | 41.8873 | 10.8176 | 26.9451 | 38.6303   | 77.3503             | 80.8194          | 79.0412      | 0.0704 | 227.0514 |
| 6.123         | 0.7104 | 800  | 5.8734          | 41.4092 | 10.7374 | 26.9369 | 37.8851   | 77.0833             | 80.8538          | 78.9178      | 0.0699 | 227.0514 |
| 6.0612        | 0.7992 | 900  | 5.8530          | 43.3281 | 11.3695 | 27.52   | 39.7303   | 77.5853             | 81.0567          | 79.2776      | 0.0736 | 227.0514 |
| 6.0503        | 0.8880 | 1000 | 5.8316          | 42.7407 | 11.1329 | 27.4419 | 39.2638   | 77.6592             | 81.0404          | 79.3085      | 0.0724 | 227.0514 |
| 6.1028        | 0.9767 | 1100 | 5.8222          | 42.8874 | 11.2364 | 27.5064 | 39.4117   | 77.6554             | 81.0536          | 79.3129      | 0.0730 | 227.0514 |


### Framework versions

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