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heemin
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my_awesome_billsum_model

Text2Text Generation
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update model card README.md

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@@ -21,7 +21,7 @@ model-index:
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  metrics:
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  - name: Rouge1
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  type: rouge
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- value: 0.1809
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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
@@ -31,12 +31,11 @@ should probably proofread and complete it, then remove this comment. -->
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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: 2.4174
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- - Rouge1: 0.1809
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- - Rouge2: 0.0831
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- - Rougel: 0.1534
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- - Rougelsum: 0.1532
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- - Gen Len: 19.0
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  ## Model description
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@@ -55,22 +54,26 @@ More information needed
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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: 4
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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 | 2.6145 | 0.1319 | 0.0414 | 0.1095 | 0.1094 | 19.0 |
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- | No log | 2.0 | 248 | 2.4825 | 0.1518 | 0.0585 | 0.1261 | 0.126 | 19.0 |
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- | No log | 3.0 | 372 | 2.4306 | 0.1731 | 0.0771 | 0.1455 | 0.1455 | 19.0 |
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- | No log | 4.0 | 496 | 2.4174 | 0.1809 | 0.0831 | 0.1534 | 0.1532 | 19.0 |
 
 
 
 
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  ### Framework versions
 
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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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  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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  ### 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