Steven Liu
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update model card README.md
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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: t5-small-finetuned-billsum-ca_test
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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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args: default
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metrics:
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- name: Rouge1
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type: rouge
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value: 52.2582
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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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# t5-small-finetuned-billsum-ca_test
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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: 1.5234
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- Rouge1: 52.2582
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- Rouge2: 34.8162
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- Rougel: 50.5491
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- Rougelsum: 50.6121
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- Gen Len: 18.996
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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: 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: 4
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- mixed_precision_training: Native AMP
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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 | 495 | 1.8113 | 58.4024 | 41.7432 | 56.9521 | 57.0516 | 18.9597 |
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| 2.709 | 2.0 | 990 | 1.6230 | 47.7769 | 32.1777 | 46.0344 | 46.046 | 18.996 |
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| 1.9323 | 3.0 | 1485 | 1.5459 | 51.2371 | 33.8242 | 49.4532 | 49.5038 | 18.996 |
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| 1.7842 | 4.0 | 1980 | 1.5234 | 52.2582 | 34.8162 | 50.5491 | 50.6121 | 18.996 |
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### Framework versions
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- Transformers 4.12.2
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- Pytorch 1.9.0+cu111
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- Datasets 1.14.0
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- Tokenizers 0.10.3
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