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

# HealthPrincipalPegasusLargeModel

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: 5.0009
- Rouge1: 51.2684
- Rouge2: 17.3059
- Rougel: 33.9682
- Rougelsum: 47.9417
- Bertscore Precision: 80.1764
- Bertscore Recall: 82.3653
- Bertscore F1: 81.2525
- Bleu: 0.1263
- Gen Len: 235.1606

## 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  |
|:-------------:|:------:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------------------:|:----------------:|:------------:|:------:|:--------:|
| 6.4911        | 0.0826 | 100  | 6.0799          | 39.9533 | 10.9966 | 25.4783 | 36.614    | 76.4664             | 80.1259          | 78.2467      | 0.0798 | 235.1606 |
| 5.9704        | 0.1653 | 200  | 5.7449          | 44.7107 | 13.7317 | 29.3188 | 41.7669   | 78.3865             | 81.0296          | 79.6811      | 0.0985 | 235.1606 |
| 5.7855        | 0.2479 | 300  | 5.5879          | 45.798  | 14.5707 | 30.3632 | 42.7848   | 78.6676             | 81.319           | 79.9669      | 0.1056 | 235.1606 |
| 5.679         | 0.3305 | 400  | 5.4498          | 46.4083 | 15.0208 | 30.9687 | 43.4256   | 78.8922             | 81.4895          | 80.1659      | 0.1086 | 235.1606 |
| 5.5132        | 0.4131 | 500  | 5.3107          | 48.8581 | 15.965  | 32.298  | 45.7224   | 79.3363             | 81.749           | 80.5209      | 0.1158 | 235.1606 |
| 5.4462        | 0.4958 | 600  | 5.2137          | 49.3647 | 16.3083 | 32.6541 | 46.1675   | 79.4978             | 81.9205          | 80.6871      | 0.1196 | 235.1606 |
| 5.4811        | 0.5784 | 700  | 5.1333          | 49.6995 | 16.5538 | 33.0588 | 46.5791   | 79.7496             | 82.0476          | 80.8784      | 0.1200 | 235.1606 |
| 5.3819        | 0.6610 | 800  | 5.0847          | 49.9273 | 16.6235 | 33.3042 | 46.6683   | 79.8845             | 82.1754          | 81.01        | 0.1216 | 235.1606 |
| 5.2029        | 0.7436 | 900  | 5.0461          | 50.8755 | 16.9213 | 33.649  | 47.5007   | 80.0059             | 82.2579          | 81.1127      | 0.1236 | 235.1606 |
| 5.2703        | 0.8263 | 1000 | 5.0225          | 51.0187 | 17.1644 | 33.8249 | 47.7395   | 80.1442             | 82.3293          | 81.2185      | 0.1254 | 235.1606 |
| 5.2121        | 0.9089 | 1100 | 5.0116          | 50.8382 | 17.0946 | 33.8088 | 47.5529   | 80.1459             | 82.3297          | 81.2196      | 0.1251 | 235.1606 |
| 5.3128        | 0.9915 | 1200 | 5.0009          | 51.2684 | 17.3059 | 33.9682 | 47.9417   | 80.1764             | 82.3653          | 81.2525      | 0.1263 | 235.1606 |


### Framework versions

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