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

# HealthPrincipalMainPegasus

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: 5.0343
- Rouge1: 51.1056
- Rouge2: 17.2499
- Rougel: 33.8193
- Rougelsum: 47.8453
- Bertscore Precision: 80.2471
- Bertscore Recall: 82.3517
- Bertscore F1: 81.2824
- Bleu: 0.1256
- Gen Len: 233.9958

## 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  |
|:-------------:|:------:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------------------:|:----------------:|:------------:|:------:|:--------:|
| 6.5043        | 0.0835 | 100  | 6.1043          | 39.8446 | 11.121  | 25.4982 | 36.4742   | 76.5079             | 80.1477          | 78.2789      | 0.0801 | 233.9958 |
| 5.9911        | 0.1671 | 200  | 5.7625          | 44.9139 | 13.8953 | 29.2395 | 41.9312   | 78.5034             | 81.0686          | 79.7606      | 0.0984 | 233.9958 |
| 5.8802        | 0.2506 | 300  | 5.5925          | 45.7626 | 14.8524 | 30.2239 | 42.6984   | 78.7715             | 81.3496          | 80.0356      | 0.1063 | 233.9958 |
| 5.708         | 0.3342 | 400  | 5.4492          | 47.5481 | 15.4828 | 31.1939 | 44.4724   | 79.2119             | 81.535           | 80.3531      | 0.1099 | 233.9958 |
| 5.4908        | 0.4177 | 500  | 5.3144          | 49.3891 | 16.3343 | 32.4471 | 46.2974   | 79.6037             | 81.8018          | 80.6843      | 0.1159 | 233.9958 |
| 5.5082        | 0.5013 | 600  | 5.2235          | 49.2315 | 16.3591 | 32.6255 | 46.1221   | 79.5967             | 81.9095          | 80.733       | 0.1184 | 233.9958 |
| 5.4192        | 0.5848 | 700  | 5.1577          | 50.8099 | 16.929  | 33.2596 | 47.5073   | 79.9416             | 82.1638          | 81.0339      | 0.1226 | 233.9958 |
| 5.4327        | 0.6684 | 800  | 5.1134          | 51.0419 | 17.0275 | 33.4839 | 47.8258   | 80.0834             | 82.1836          | 81.1165      | 0.1228 | 233.9958 |
| 5.3311        | 0.7519 | 900  | 5.0760          | 50.6545 | 17.1249 | 33.5043 | 47.4752   | 80.0946             | 82.2579          | 81.1584      | 0.1242 | 233.9958 |
| 5.3244        | 0.8355 | 1000 | 5.0510          | 51.2619 | 17.2114 | 33.7881 | 47.9991   | 80.254              | 82.3319          | 81.2763      | 0.1247 | 233.9958 |
| 5.2486        | 0.9190 | 1100 | 5.0343          | 51.1056 | 17.2499 | 33.8193 | 47.8453   | 80.2471             | 82.3517          | 81.2824      | 0.1256 | 233.9958 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1