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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-multi_news-summarizer_01
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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-multi_news-summarizer_01
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This model is a fine-tuned version of [google/pegasus-multi_news](https://huggingface.co/google/pegasus-multi_news) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.2794
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- Rouge1: 52.1693
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- Rouge2: 34.8989
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- Rougel: 41.2385
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- Rougelsum: 48.4365
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- Gen Len: 98.6433
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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: 1
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- eval_batch_size: 1
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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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| 1.3936 | 1.0 | 16113 | 1.2972 | 51.5747 | 34.2062 | 40.7279 | 47.7783 | 95.0004 |
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| 1.3664 | 2.0 | 32226 | 1.2817 | 52.1077 | 34.8189 | 41.1614 | 48.3894 | 100.3265 |
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| 1.3002 | 3.0 | 48339 | 1.2794 | 52.1693 | 34.8989 | 41.2385 | 48.4365 | 98.6433 |
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### Framework versions
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- Transformers 4.12.3
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- Pytorch 1.9.0+cu111
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- Datasets 1.15.1
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- Tokenizers 0.10.3
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