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update model card README.md
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README.md
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---
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tags:
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- summarization
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- ar
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- encoder-decoder
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- roberta
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- xlmroberta2xlmroberta
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- Abstractive Summarization
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- generated_from_trainer
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datasets:
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- wiki_lingua
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model-index:
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- name: xlmroberta2xlmroberta-finetuned-ar-wikilingua
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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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# xlmroberta2xlmroberta-finetuned-ar-wikilingua
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This model is a fine-tuned version of [](https://huggingface.co/) on the wiki_lingua dataset.
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It achieves the following results on the evaluation set:
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- Loss: 4.7757
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- Rouge-1: 11.2
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- Rouge-2: 1.96
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- Rouge-l: 10.28
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- Gen Len: 19.8
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- Bertscore: 66.27
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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: 5e-05
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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: 16
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- total_train_batch_size: 64
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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: 10
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- label_smoothing_factor: 0.1
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Rouge-1 | Rouge-2 | Rouge-l | Gen Len | Bertscore |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:-------:|:---------:|
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| 8.03 | 1.0 | 312 | 7.3208 | 0.19 | 0.0 | 0.19 | 20.0 | 54.84 |
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| 7.2309 | 2.0 | 624 | 7.1107 | 1.17 | 0.03 | 1.16 | 20.0 | 60.0 |
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| 7.0752 | 3.0 | 936 | 7.0061 | 2.58 | 0.15 | 2.55 | 20.0 | 63.52 |
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| 6.7538 | 4.0 | 1248 | 6.4189 | 5.75 | 0.46 | 5.55 | 19.95 | 62.83 |
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| 6.1513 | 5.0 | 1560 | 5.8402 | 8.46 | 1.04 | 8.08 | 19.2 | 64.25 |
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| 5.6639 | 6.0 | 1872 | 5.3938 | 8.62 | 1.17 | 8.16 | 19.28 | 64.81 |
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| 5.2857 | 7.0 | 2184 | 5.0719 | 9.34 | 1.41 | 8.61 | 19.71 | 65.29 |
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| 5.027 | 8.0 | 2496 | 4.9047 | 10.42 | 1.52 | 9.57 | 19.57 | 65.75 |
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| 4.8747 | 9.0 | 2808 | 4.8032 | 10.79 | 1.71 | 9.91 | 19.42 | 66.2 |
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| 4.7855 | 10.0 | 3120 | 4.7757 | 11.01 | 1.73 | 10.04 | 19.55 | 66.24 |
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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 2.2.2
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- Tokenizers 0.12.1
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