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---
tags:
- generated_from_trainer
datasets:
- govreport-summarization
model-index:
- name: Pegasus-x-base-govreport-12288-1024-numepoch-10
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. -->
# Pegasus-x-base-govreport-12288-1024-numepoch-10
This model is a fine-tuned version of [google/pegasus-x-base](https://huggingface.co/google/pegasus-x-base) on the govreport-summarization dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6234
## Model description
More information needed
## Evaluation Score
**'ROUGE'**:
{
'rouge1': 0.5012,
'rouge2': 0.2205,
'rougeL': 0.2552,
'rougeLsum': 0.2554
}
**'BERT_SCORE'**
{'f1': 0.859,
'precision': 0.8619,
'recall': 0.8563
}
## 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: 0.0001
- train_batch_size: 1
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 64
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.1149 | 0.37 | 100 | 1.9237 |
| 1.9545 | 0.73 | 200 | 1.8380 |
| 1.8835 | 1.1 | 300 | 1.7574 |
| 1.862 | 1.46 | 400 | 1.7305 |
| 1.8536 | 1.83 | 500 | 1.7100 |
| 1.8062 | 2.19 | 600 | 1.6944 |
| 1.8161 | 2.56 | 700 | 1.6882 |
| 1.7611 | 2.92 | 800 | 1.6803 |
| 1.7878 | 3.29 | 900 | 1.6671 |
| 1.7299 | 3.65 | 1000 | 1.6599 |
| 1.7636 | 4.02 | 1100 | 1.6558 |
| 1.7262 | 4.38 | 1200 | 1.6547 |
| 1.715 | 4.75 | 1300 | 1.6437 |
| 1.7178 | 5.12 | 1400 | 1.6445 |
| 1.7163 | 5.48 | 1500 | 1.6386 |
| 1.7367 | 5.85 | 1600 | 1.6364 |
| 1.7114 | 6.21 | 1700 | 1.6365 |
| 1.6452 | 6.58 | 1800 | 1.6309 |
| 1.7251 | 6.94 | 1900 | 1.6301 |
| 1.6726 | 7.31 | 2000 | 1.6305 |
| 1.7104 | 7.67 | 2100 | 1.6285 |
| 1.6739 | 8.04 | 2200 | 1.6252 |
| 1.7082 | 8.4 | 2300 | 1.6246 |
| 1.6888 | 8.77 | 2400 | 1.6244 |
| 1.6609 | 9.13 | 2500 | 1.6256 |
| 1.6707 | 9.5 | 2600 | 1.6241 |
| 1.669 | 9.86 | 2700 | 1.6234 |
### Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3
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