readme: ---
  license: apache-2.0
  tags:
  - summarization
  - urdu
  - ur
  - mt5
  - Abstractive Summarization
  - generated_from_trainer
  datasets:
  - xlsum
  model-index:
  - name: mt5-base-finetuned-urdu
    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-base-finetuned-urdu
  
  This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on Urdu subset the xlsum dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.8954
  - Rouge-1: 28.84
  - Rouge-2: 13.87
  - Rouge-l: 25.63
  - Gen Len: 19.0
  - Bertscore: 71.31
  
  ## 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: 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
  - num_epochs: 5
  - label_smoothing_factor: 0.1
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Rouge-1 | Rouge-2 | Rouge-l | Gen Len | Bertscore |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:-------:|:---------:|
  | 3.6205        | 1.0   | 2114  | 3.0871          | 26.45   | 11.4    | 23.26   | 19.0    | 70.76     |
  | 3.2169        | 2.0   | 4228  | 2.9830          | 27.19   | 11.91   | 23.95   | 19.0    | 70.92     |
  | 3.0787        | 3.0   | 6342  | 2.9284          | 27.9    | 12.57   | 24.62   | 18.99   | 71.13     |
  | 2.9874        | 4.0   | 8456  | 2.9049          | 28.28   | 12.91   | 24.99   | 18.99   | 71.28     |
  | 2.9232        | 5.0   | 10570 | 2.8954          | 28.65   | 13.17   | 25.32   | 18.99   | 71.39     |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.11.0+cu113
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  