update model card README.md

README.md

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+---
+tags:
+- mt5
+- summarization
+- Abstractive Summarization
+- ar
+- generated_from_trainer
+datasets:
+- xlsum
+model-index:
+- name: mT5_multilingual_XLSum-finetuned-fa-finetuned-ar
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# mT5_multilingual_XLSum-finetuned-fa-finetuned-ar
+
+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.
+It achieves the following results on the evaluation set:
+- Loss: 3.6352
+- Rouge-1: 28.69
+- Rouge-2: 11.6
+- Rouge-l: 24.29
+- Gen Len: 41.37
+- Bertscore: 73.37
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 0.0005
+- train_batch_size: 2
+- eval_batch_size: 2
+- seed: 42
+- gradient_accumulation_steps: 8
+- total_train_batch_size: 16
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 250
+- num_epochs: 5
+- label_smoothing_factor: 0.1
+
+### Training results
+
+
+
+### Framework versions
+
+- Transformers 4.19.2
+- Pytorch 1.11.0+cu113
+- Datasets 2.2.2
+- Tokenizers 0.12.1