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tags: |
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- mt5 |
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- summarization |
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- Abstractive Summarization |
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- ar |
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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: mT5_multilingual_XLSum-finetuned-fa-finetuned-ar |
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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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# mT5_multilingual_XLSum-finetuned-fa-finetuned-ar |
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This model is a fine-tuned version of [ahmeddbahaa/mT5_multilingual_XLSum-finetuned-fa](https://huggingface.co/ahmeddbahaa/mT5_multilingual_XLSum-finetuned-fa) on the xlsum dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.6352 |
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- Rouge-1: 28.69 |
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- Rouge-2: 11.6 |
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- Rouge-l: 24.29 |
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- Gen Len: 41.37 |
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- Bertscore: 73.37 |
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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: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 16 |
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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 4.19.2 |
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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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