readme: ---
  license: apache-2.0
  tags:
  - summarization
  - fa
  - mt5
  - Abstractive Summarization
  - generated_from_trainer
  datasets:
  - pn_summary
  model-index:
  - name: mt5-base-finetuned-fa
    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-fa
  
  This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on the pn_summary dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.6477
  - Rouge-1: 33.7
  - Rouge-2: 21.28
  - Rouge-l: 31.69
  - Gen Len: 19.0
  - Bertscore: 74.52
  
  ## 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
  - lr_scheduler_warmup_steps: 250
  - 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 |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:-------:|:---------:|
  | 3.3828        | 1.0   | 1875 | 2.8114          | 32.17   | 19.47   | 30.12   | 18.99   | 74.25     |
  | 2.8204        | 2.0   | 3750 | 2.7080          | 32.67   | 19.92   | 30.56   | 19.0    | 74.31     |
  | 2.6907        | 3.0   | 5625 | 2.6724          | 33.22   | 20.44   | 31.11   | 19.0    | 74.47     |
  | 2.6029        | 4.0   | 7500 | 2.6513          | 33.46   | 20.75   | 31.38   | 19.0    | 74.54     |
  | 2.5414        | 5.0   | 9375 | 2.6477          | 33.68   | 20.91   | 31.62   | 19.0    | 74.58     |
  
  
  ### Framework versions
  
  - Transformers 4.19.4
  - Pytorch 1.11.0+cu113
  - Datasets 2.2.2
  - Tokenizers 0.12.1
  