update model card README.md

README.md

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+---
+tags:
+- summarization
+- ar
+- encoder-decoder
+- arabert
+- arabert2arabert
+- Abstractive Summarization
+- generated_from_trainer
+datasets:
+- wiki_lingua
+model-index:
+- name: arabert2arabert-finetuned-ar-wikilingua
+  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. -->
+
+# arabert2arabert-finetuned-ar-wikilingua
+
+This model is a fine-tuned version of [](https://huggingface.co/) on the wiki_lingua dataset.
+It achieves the following results on the evaluation set:
+- Loss: 4.6877
+- Rouge-1: 13.2
+- Rouge-2: 3.43
+- Rouge-l: 12.45
+- Gen Len: 20.0
+- Bertscore: 64.88
+
+## 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: 8
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 16
+- total_train_batch_size: 128
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 250
+- num_epochs: 8
+- label_smoothing_factor: 0.1
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Rouge-1 | Rouge-2 | Rouge-l | Gen Len | Bertscore |
+|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:-------:|:---------:|
+| 6.7667        | 1.0   | 156  | 5.3846          | 3.36    | 0.56    | 3.27    | 20.0    | 60.6      |
+| 5.257         | 2.0   | 312  | 5.0424          | 5.44    | 0.88    | 5.35    | 20.0    | 60.56     |
+| 4.743         | 3.0   | 468  | 4.8294          | 9.21    | 1.8     | 8.93    | 20.0    | 62.91     |
+| 4.3832        | 4.0   | 624  | 4.7240          | 9.88    | 2.19    | 9.6     | 20.0    | 62.65     |
+| 4.1166        | 5.0   | 780  | 4.6861          | 11.61   | 2.86    | 11.13   | 20.0    | 63.71     |
+| 3.91          | 6.0   | 936  | 4.6692          | 12.27   | 3.11    | 11.76   | 20.0    | 64.07     |
+| 3.7569        | 7.0   | 1092 | 4.6805          | 12.93   | 3.38    | 12.28   | 20.0    | 64.61     |
+| 3.6454        | 8.0   | 1248 | 4.6877          | 13.2    | 3.43    | 12.45   | 20.0    | 64.88     |
+
+
+### Framework versions
+
+- Transformers 4.19.4
+- Pytorch 1.11.0+cu113
+- Datasets 2.2.2
+- Tokenizers 0.12.1