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---
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tags:
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- summarization
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- fa
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- xlmroberta
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- Abstractive Summarization
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- generated_from_trainer
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datasets:
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- pn_summary
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model-index:
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- name: xlmroberta-finetuned-fa
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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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# xlmroberta-finetuned-fa
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This model is a fine-tuned version of [](https://huggingface.co/) on the pn_summary dataset.
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It achieves the following results on the evaluation set:
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- Loss: 8.2286
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- Rouge-1: 4.99
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- Rouge-2: 0.0
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- Rouge-l: 4.99
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- Gen Len: 20.0
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- Bertscore: 51.89
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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: 0.0005
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- train_batch_size: 4
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- eval_batch_size: 4
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- seed: 42
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- gradient_accumulation_steps: 8
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- total_train_batch_size: 32
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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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- lr_scheduler_warmup_steps: 250
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- num_epochs: 5
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- label_smoothing_factor: 0.1
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### Training results
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### Framework versions
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- Transformers 4.19.4
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- Pytorch 1.11.0+cu113
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- Datasets 2.3.0
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- Tokenizers 0.12.1
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