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--- |
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license: apache-2.0 |
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base_model: t5-small |
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tags: |
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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: my_awesome_billsum_model |
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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: ca_test |
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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: 0.2014 |
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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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# my_awesome_billsum_model |
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This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the billsum dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.2453 |
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- Rouge1: 0.2014 |
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- Rouge2: 0.1012 |
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- Rougel: 0.1696 |
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- Rougelsum: 0.1698 |
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- Gen Len: 19.0 |
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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: 10 |
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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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| No log | 1.0 | 124 | 2.5661 | 0.1328 | 0.0422 | 0.1082 | 0.1083 | 19.0 | |
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| No log | 2.0 | 248 | 2.4215 | 0.1686 | 0.0704 | 0.139 | 0.1391 | 19.0 | |
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| No log | 3.0 | 372 | 2.3551 | 0.1994 | 0.0994 | 0.1669 | 0.1667 | 19.0 | |
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| No log | 4.0 | 496 | 2.3135 | 0.2021 | 0.1018 | 0.1701 | 0.17 | 19.0 | |
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| 2.7983 | 5.0 | 620 | 2.2911 | 0.2019 | 0.103 | 0.1703 | 0.1705 | 19.0 | |
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| 2.7983 | 6.0 | 744 | 2.2719 | 0.2015 | 0.1023 | 0.1707 | 0.1708 | 19.0 | |
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| 2.7983 | 7.0 | 868 | 2.2597 | 0.2008 | 0.1013 | 0.1691 | 0.1693 | 19.0 | |
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| 2.7983 | 8.0 | 992 | 2.2515 | 0.2016 | 0.1016 | 0.1695 | 0.1697 | 19.0 | |
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| 2.4664 | 9.0 | 1116 | 2.2467 | 0.2017 | 0.1016 | 0.1696 | 0.1698 | 19.0 | |
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| 2.4664 | 10.0 | 1240 | 2.2453 | 0.2014 | 0.1012 | 0.1696 | 0.1698 | 19.0 | |
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### Framework versions |
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- Transformers 4.33.3 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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