update model card README.md

README.md

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+---
+tags:
+- summarization
+- ur
+- seq2seq
+- mbart
+- Abstractive Summarization
+- generated_from_trainer
+datasets:
+- xlsum
+model-index:
+- name: MBart-finetuned-ur-xlsum
+  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. -->
+
+# MBart-finetuned-ur-xlsum
+
+This model is a fine-tuned version of [facebook/mbart-large-50](https://huggingface.co/facebook/mbart-large-50) on the xlsum dataset.
+It achieves the following results on the evaluation set:
+- Loss: 3.2663
+- Rouge-1: 40.6
+- Rouge-2: 18.9
+- Rouge-l: 34.39
+- Gen Len: 37.88
+- Bertscore: 77.06
+
+## 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: 5e-05
+- train_batch_size: 4
+- eval_batch_size: 4
+- seed: 42
+- gradient_accumulation_steps: 8
+- total_train_batch_size: 32
+- 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 4.20.0
+- Pytorch 1.11.0+cu113
+- Datasets 2.3.2
+- Tokenizers 0.12.1