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---
tags:
- generated_from_trainer
metrics:
- rouge
base_model: google/pegasus-newsroom
model-index:
- name: pegasus-newsroom-summarizer_30216
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-summarizer_30216
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: 0.9637
- Rouge1: 52.0929
- Rouge2: 34.6709
- Rougel: 41.1615
- Rougelsum: 48.4141
- Gen Len: 102.017
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:--------:|
| 1.0592 | 1.0 | 12086 | 0.9743 | 51.6187 | 34.1687 | 40.5959 | 47.9305 | 104.3352 |
| 0.9742 | 2.0 | 24172 | 0.9647 | 52.1837 | 34.7301 | 41.2599 | 48.4955 | 101.2771 |
| 0.9371 | 3.0 | 36258 | 0.9637 | 52.0929 | 34.6709 | 41.1615 | 48.4141 | 102.017 |
### Framework versions
- Transformers 4.23.1
- Pytorch 1.12.1+cu113
- Datasets 2.6.1
- Tokenizers 0.13.1
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