readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: mbert2mbert-arabic-text-summarization-finetuned-xsum_arabic_abstractive_final_finaln
    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. -->
  
  # mbert2mbert-arabic-text-summarization-finetuned-xsum_arabic_abstractive_final_finaln
  
  This model is a fine-tuned version of [malmarjeh/mbert2mbert-arabic-text-summarization](https://huggingface.co/malmarjeh/mbert2mbert-arabic-text-summarization) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.2826
  - Rouge1: 0.0119
  - Rouge2: 0.0
  - Rougel: 0.0119
  - Rougelsum: 0.0119
  - Gen Len: 41.8856
  
  ## 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: 2e-05
  - train_batch_size: 4
  - eval_batch_size: 4
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 2
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
  | 2.5104        | 1.0   | 7915  | 2.3684          | 0.0    | 0.0    | 0.0    | 0.0       | 41.8314 |
  | 2.2222        | 2.0   | 15830 | 2.2826          | 0.0119 | 0.0    | 0.0119 | 0.0119    | 41.8856 |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.11.0
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  