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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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- billsum
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metrics:
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- rouge
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model-index:
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- name: CS685-text-summarizer-2
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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: billsum
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type: billsum
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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: 17.1607
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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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# CS685-text-summarizer-2
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This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the billsum dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.7651
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- Rouge1: 17.1607
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- Rouge2: 13.943
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- Rougel: 16.6793
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- Rougelsum: 16.8422
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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: 5.6e-05
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- train_batch_size: 6
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- eval_batch_size: 6
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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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| 2.4547 | 1.0 | 569 | 1.9895 | 16.6343 | 13.0432 | 16.1262 | 16.2449 |
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| 2.0246 | 2.0 | 1138 | 1.8688 | 16.939 | 13.4711 | 16.4359 | 16.5797 |
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| 1.818 | 3.0 | 1707 | 1.8075 | 17.1388 | 13.827 | 16.6136 | 16.7574 |
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| 1.6831 | 4.0 | 2276 | 1.7744 | 17.2292 | 13.9353 | 16.6961 | 16.8786 |
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| 1.5956 | 5.0 | 2845 | 1.7651 | 17.1607 | 13.943 | 16.6793 | 16.8422 |
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### Framework versions
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- Transformers 4.28.0
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- Pytorch 2.0.0+cu118
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- Datasets 2.12.0
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- Tokenizers 0.13.3
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