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README.md
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---
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tags:
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- generated_from_trainer
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metrics:
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- rouge
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model-index:
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- name: pegasus-newsroom-summarizer_30216
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# pegasus-newsroom-summarizer_30216
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This model is a fine-tuned version of [google/pegasus-newsroom](https://huggingface.co/google/pegasus-newsroom) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.9637
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- Rouge1: 52.0929
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- Rouge2: 34.6709
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- Rougel: 41.1615
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- Rougelsum: 48.4141
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- Gen Len: 102.017
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 2
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- eval_batch_size: 2
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 3
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
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|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:--------:|
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| 1.0592 | 1.0 | 12086 | 0.9743 | 51.6187 | 34.1687 | 40.5959 | 47.9305 | 104.3352 |
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| 0.9742 | 2.0 | 24172 | 0.9647 | 52.1837 | 34.7301 | 41.2599 | 48.4955 | 101.2771 |
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| 0.9371 | 3.0 | 36258 | 0.9637 | 52.0929 | 34.6709 | 41.1615 | 48.4141 | 102.017 |
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### Framework versions
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- Transformers 4.23.1
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- Pytorch 1.12.1+cu113
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- Datasets 2.6.1
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- Tokenizers 0.13.1
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