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cs608
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multi-news-model

Summarization
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bart
text2text-generation
Generated from Trainer
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@@ -3,11 +3,26 @@ 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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  metrics:
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  - rouge
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  model-index:
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  - name: CS685-text-summarizer
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- results: []
 
 
 
 
 
 
 
 
 
 
 
 
 
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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
@@ -15,13 +30,13 @@ should probably proofread and complete it, then remove this comment. -->
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  # CS685-text-summarizer
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- This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.6758
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- - Rouge1: 50.1818
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- - Rouge2: 25.0255
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- - Rougel: 45.4346
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- - Rougelsum: 45.4932
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  ## Model description
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@@ -41,24 +56,27 @@ More information needed
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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: 10
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- - eval_batch_size: 10
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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: 2
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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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- | 2.0628 | 1.0 | 613 | 1.7464 | 48.9466 | 24.0276 | 44.5506 | 44.6348 |
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- | 1.5004 | 2.0 | 1226 | 1.6758 | 50.1818 | 25.0255 | 45.4346 | 45.4932 |
 
 
 
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  ### Framework versions
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- - Transformers 4.28.1
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  - Pytorch 2.0.0+cu118
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  - Datasets 2.12.0
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  - Tokenizers 0.13.3
 
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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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+ - multi_news
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  metrics:
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  - rouge
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  model-index:
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  - name: CS685-text-summarizer
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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: multi_news
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+ type: multi_news
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+ config: default
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+ split: train[:20%]
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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: 9.8777
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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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  # CS685-text-summarizer
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+ This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the multi_news dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 2.4960
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+ - Rouge1: 9.8777
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+ - Rouge2: 3.6509
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+ - Rougel: 7.597
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+ - Rougelsum: 9.0495
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  ## Model description
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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: 6
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+ - eval_batch_size: 6
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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: 5
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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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+ | 2.8402 | 1.0 | 1349 | 2.5256 | 9.7548 | 3.5429 | 7.5078 | 8.9174 |
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+ | 2.5581 | 2.0 | 2698 | 2.5011 | 9.7256 | 3.6262 | 7.5644 | 8.8904 |
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+ | 2.3908 | 3.0 | 4047 | 2.4948 | 9.7569 | 3.5976 | 7.5209 | 8.8919 |
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+ | 2.2744 | 4.0 | 5396 | 2.4875 | 9.9116 | 3.7758 | 7.6823 | 9.0881 |
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+ | 2.1908 | 5.0 | 6745 | 2.4960 | 9.8777 | 3.6509 | 7.597 | 9.0495 |
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  ### Framework versions
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+ - Transformers 4.29.1
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  - Pytorch 2.0.0+cu118
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  - Datasets 2.12.0
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  - Tokenizers 0.13.3