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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-headline_writer_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-newsroom-headline_writer_57k
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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: 1.3599
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- Rouge1: 42.2586
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- Rouge2: 23.2731
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- Rougel: 35.8685
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- Rougelsum: 36.0581
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- Gen Len: 34.3651
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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: 8
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- eval_batch_size: 8
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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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| 1.5213 | 1.0 | 5670 | 1.4040 | 41.8648 | 22.8205 | 35.3983 | 35.535 | 34.8817 |
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| 1.4171 | 2.0 | 11340 | 1.3672 | 42.26 | 23.2611 | 35.8016 | 35.9753 | 34.3492 |
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| 1.3722 | 3.0 | 17010 | 1.3599 | 42.2586 | 23.2731 | 35.8685 | 36.0581 | 34.3651 |
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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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