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README.md
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---
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license: apache-2.0
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tags:
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- summarization
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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: multi-news-diff-weight
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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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config: default
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split: train[:20%]
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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: 9.9082
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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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# multi-news-diff-weight
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This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the multi_news dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.5350
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- Rouge1: 9.9082
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- Rouge2: 3.6995
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- Rougel: 7.6135
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- Rougelsum: 9.0176
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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: 5e-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: 5
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
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|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|
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| 2.8555 | 1.0 | 4047 | 2.5846 | 9.7797 | 3.6212 | 7.5597 | 8.9387 |
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| 2.5262 | 2.0 | 8094 | 2.5231 | 9.7969 | 3.5968 | 7.5592 | 8.9532 |
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| 2.3195 | 3.0 | 12141 | 2.5149 | 9.83 | 3.6338 | 7.5109 | 8.9725 |
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| 2.1655 | 4.0 | 16188 | 2.5188 | 9.8704 | 3.6936 | 7.6094 | 9.0336 |
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| 2.055 | 5.0 | 20235 | 2.5350 | 9.9082 | 3.6995 | 7.6135 | 9.0176 |
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### Framework versions
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- Transformers 4.29.1
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- Pytorch 2.0.0
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- Datasets 2.12.0
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- Tokenizers 0.13.3
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