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---
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
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