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--- |
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license: apache-2.0 |
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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: 19.4885 |
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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: 2.1303 |
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- Rouge1: 19.4885 |
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- Rouge2: 9.7756 |
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- Rougel: 16.7539 |
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- Rougelsum: 18.153 |
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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: 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: 8 |
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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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| 2.9287 | 1.0 | 124 | 2.3690 | 18.7685 | 8.721 | 15.7134 | 17.2109 | |
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| 2.5051 | 2.0 | 248 | 2.2540 | 19.5651 | 9.5886 | 16.5619 | 18.1252 | |
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| 2.4042 | 3.0 | 372 | 2.2140 | 19.4716 | 9.7429 | 16.6675 | 18.0006 | |
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| 2.3442 | 4.0 | 496 | 2.1800 | 19.5841 | 9.7078 | 16.7923 | 18.1682 | |
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| 2.3075 | 5.0 | 620 | 2.1562 | 19.4162 | 9.6647 | 16.5106 | 17.9637 | |
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| 2.2693 | 6.0 | 744 | 2.1394 | 19.5064 | 9.8462 | 16.6515 | 18.0461 | |
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| 2.2714 | 7.0 | 868 | 2.1321 | 19.475 | 9.7216 | 16.6698 | 18.1103 | |
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| 2.2413 | 8.0 | 992 | 2.1303 | 19.4885 | 9.7756 | 16.7539 | 18.153 | |
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### Framework versions |
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- Transformers 4.25.1 |
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- Pytorch 1.13.0+cu116 |
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- Datasets 2.7.1 |
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- Tokenizers 0.13.2 |
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