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---
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
should probably proofread and complete it, then remove this comment. -->
# 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
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