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---
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: pegasus-multi_news_wires_hdwriter42k
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-multi_news_wires_hdwriter42k
This model is a fine-tuned version of [google/pegasus-multi_news](https://huggingface.co/google/pegasus-multi_news) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6427
- Rouge1: 37.3045
- Rouge2: 17.2478
- Rougel: 30.7768
- Rougelsum: 31.3514
- Gen Len: 34.6955
## 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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 1.7914 | 1.0 | 16875 | 1.6849 | 36.6608 | 17.005 | 30.4166 | 30.9289 | 35.4077 |
| 1.6658 | 2.0 | 33750 | 1.6452 | 37.2837 | 17.3162 | 30.8358 | 31.3382 | 34.7757 |
| 1.5478 | 3.0 | 50625 | 1.6427 | 37.3045 | 17.2478 | 30.7768 | 31.3514 | 34.6955 |
### Framework versions
- Transformers 4.23.1
- Pytorch 1.12.1+cu113
- Datasets 2.6.1
- Tokenizers 0.13.1
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