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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-headline_57k
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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-headline_57k
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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: 1.4503
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- Rouge1: 42.3147
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- Rouge2: 23.2213
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- Rougel: 35.7441
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- Rougelsum: 35.8964
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- Gen Len: 33.8245
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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: 4
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- eval_batch_size: 4
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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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| 1.6546 | 1.0 | 11339 | 1.5170 | 41.7822 | 22.7843 | 35.3913 | 35.5749 | 34.1139 |
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| 1.5132 | 2.0 | 22678 | 1.4602 | 42.0161 | 22.9778 | 35.5357 | 35.6921 | 33.9944 |
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| 1.4147 | 3.0 | 34017 | 1.4503 | 42.3147 | 23.2213 | 35.7441 | 35.8964 | 33.8245 |
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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 2.6.0
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- Tokenizers 0.13.1
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