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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: billsum-full-data
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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[:95%]
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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: 18.0383
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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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# billsum-full-data
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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: 1.6583
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- Rouge1: 18.0383
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- Rouge2: 14.8462
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- Rougel: 17.6086
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- Rougelsum: 17.6843
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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: 3
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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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| 2.1401 | 1.0 | 8101 | 1.8087 | 17.8461 | 14.6015 | 17.3956 | 17.4842 |
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| 1.7596 | 2.0 | 16202 | 1.6980 | 18.0568 | 14.7833 | 17.6068 | 17.6999 |
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| 1.5789 | 3.0 | 24303 | 1.6583 | 18.0383 | 14.8462 | 17.6086 | 17.6843 |
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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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