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  ---
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- language:
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- - it_IT
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- - it_IT
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  tags:
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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: summarization_mbart_fanpage4epoch
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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
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- should probably proofread and complete it, then remove this comment. -->
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- # summarization_mbart_fanpage4epoch
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- This model is a fine-tuned version of [facebook/mbart-large-cc25](https://huggingface.co/facebook/mbart-large-cc25) on an unknown dataset.
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- It achieves the following results on the evaluation set:
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  - Loss: 2.1833
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  - Rouge1: 36.5027
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  - Rouge2: 17.4428
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  - Rougelsum: 30.2636
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  - Gen Len: 75.2413
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- ## Model description
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-
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- More information needed
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-
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- ## Intended uses & limitations
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-
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- More information needed
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- ## Training and evaluation data
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-
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- More information needed
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-
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- ## Training procedure
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  ### Training hyperparameters
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  - lr_scheduler_type: linear
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  - num_epochs: 4.0
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- ### Training results
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-
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-
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-
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  ### Framework versions
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  - Transformers 4.15.0.dev0
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  - Pytorch 1.10.0+cu102
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  - Datasets 1.15.1
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- - Tokenizers 0.10.3
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  ---
 
 
 
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  tags:
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+ - summarization
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+ language:
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+ - it
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  metrics:
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  - rouge
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  model-index:
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  - name: summarization_mbart_fanpage4epoch
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  results: []
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+ datasets:
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+ - ARTeLab/fanpage
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  ---
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+ # mbart-summarization-fanpage
 
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+ This model is a fine-tuned version of [facebook/mbart-large-cc25](https://huggingface.co/facebook/mbart-large-cc25) on Fanpage dataset for Abstractive Summarization.
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+ It achieves the following results:
 
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  - Loss: 2.1833
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  - Rouge1: 36.5027
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  - Rouge2: 17.4428
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  - Rougelsum: 30.2636
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  - Gen Len: 75.2413
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+ ## Usage
 
 
 
 
 
 
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+ ```python
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+ from transformers import MBartTokenizer, MBartForConditionalGeneration
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+ tokenizer = MBartTokenizer.from_pretrained("ARTeLab/mbart-summarization-fanpage")
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+ model = MBartForConditionalGeneration.from_pretrained("ARTeLab/mbart-summarization-fanpage")
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+ ```
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  ### Training hyperparameters
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  - lr_scheduler_type: linear
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  - num_epochs: 4.0
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  ### Framework versions
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  - Transformers 4.15.0.dev0
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  - Pytorch 1.10.0+cu102
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  - Datasets 1.15.1
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+ - Tokenizers 0.10.3