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---
tags:
- generated_from_trainer
metrics:
- rouge
base_model: google/pegasus-newsroom
model-index:
- name: pegasus-newsroom-rewriter
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-newsroom-rewriter
This model is a fine-tuned version of [google/pegasus-newsroom](https://huggingface.co/google/pegasus-newsroom) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3424
- Rouge1: 46.6856
- Rouge2: 31.6377
- Rougel: 33.2741
- Rougelsum: 44.5003
- Gen Len: 126.58
## 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: 2e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| No log | 1.0 | 450 | 1.4020 | 47.0593 | 32.2065 | 33.9168 | 44.901 | 126.32 |
| 1.9944 | 2.0 | 900 | 1.3567 | 46.2635 | 30.9959 | 32.933 | 44.1659 | 126.48 |
| 1.6511 | 3.0 | 1350 | 1.3449 | 46.1544 | 30.7257 | 32.693 | 43.9977 | 126.4 |
| 1.5951 | 4.0 | 1800 | 1.3424 | 46.6856 | 31.6377 | 33.2741 | 44.5003 | 126.58 |
### Framework versions
- Transformers 4.17.0
- Pytorch 1.10.0+cu111
- Datasets 2.0.0
- Tokenizers 0.11.6
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