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update model card README.md

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+ ---
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+ tags:
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+ - summarization
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+ - ur
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+ - encoder-decoder
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+ - xlm-roberta
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+ - Abstractive Summarization
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+ - roberta
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+ - generated_from_trainer
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+ datasets:
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+ - xlsum
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+ model-index:
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+ - name: xlmroberta2xlmroberta-finetune-summarization-ur
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+ results: []
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+ ---
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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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+
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+ # xlmroberta2xlmroberta-finetune-summarization-ur
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+
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+ This model is a fine-tuned version of [](https://huggingface.co/) on the xlsum dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 5.4576
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+ - Rouge-1: 26.51
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+ - Rouge-2: 9.4
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+ - Rouge-l: 23.21
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+ - Gen Len: 19.99
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+ - Bertscore: 68.15
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+
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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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+
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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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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 5e-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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+ - gradient_accumulation_steps: 8
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+ - total_train_batch_size: 48
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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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+
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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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+
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+ - Transformers 4.19.4
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+ - Pytorch 1.11.0+cu113
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+ - Datasets 2.3.2
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+ - Tokenizers 0.12.1