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README.md
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---
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license: mit
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tags:
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- generated_from_trainer
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datasets:
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- multi_news
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metrics:
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- rouge
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model-index:
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- name: bart-large-cnn-finetuned-multi-news1
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results:
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- task:
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name: Sequence-to-sequence Language Modeling
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type: text2text-generation
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dataset:
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name: multi_news
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type: multi_news
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args: default
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metrics:
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- name: Rouge1
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type: rouge
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value: 42.1215
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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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# bart-large-cnn-finetuned-multi-news1
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This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on the multi_news dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.0858
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- Rouge1: 42.1215
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- Rouge2: 14.9986
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- Rougel: 23.4737
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- Rougelsum: 36.4212
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- Gen Len: 133.703
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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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- gradient_accumulation_steps: 4
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- total_train_batch_size: 16
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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: 1
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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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| 2.1984 | 1.0 | 750 | 2.0858 | 42.1215 | 14.9986 | 23.4737 | 36.4212 | 133.703 |
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### Framework versions
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- Transformers 4.18.0
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- Pytorch 1.10.0+cu111
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- Datasets 2.0.0
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- Tokenizers 0.11.6
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