readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: summarise_v2
    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. -->
  
  # summarise_v2
  
  This model is a fine-tuned version of [allenai/led-base-16384](https://huggingface.co/allenai/led-base-16384) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.3235
  - Rouge2 Precision: 0.018
  - Rouge2 Recall: 0.0916
  - Rouge2 Fmeasure: 0.0292
  
  ## 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: 2
  - eval_batch_size: 2
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 1
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
  |:-------------:|:-----:|:----:|:---------------:|:----------------:|:-------------:|:---------------:|
  | 3.1721        | 0.08  | 10   | 2.7742          | 0.0107           | 0.0671        | 0.0178          |
  | 3.0802        | 0.16  | 20   | 2.7914          | 0.0111           | 0.0878        | 0.019           |
  | 3.0795        | 0.24  | 30   | 2.6954          | 0.0094           | 0.076         | 0.0157          |
  | 2.5806        | 0.32  | 40   | 2.6587          | 0.0028           | 0.0271        | 0.0046          |
  | 2.6553        | 0.4   | 50   | 2.5958          | 0.0084           | 0.0566        | 0.0143          |
  | 2.689         | 0.48  | 60   | 2.4857          | 0.0089           | 0.0733        | 0.015           |
  | 2.6642        | 0.56  | 70   | 2.4205          | 0.0069           | 0.0478        | 0.0116          |
  | 2.3768        | 0.64  | 80   | 2.3754          | 0.0127           | 0.0795        | 0.0215          |
  | 2.1949        | 0.72  | 90   | 2.3752          | 0.0155           | 0.1013        | 0.0258          |
  | 2.3257        | 0.8   | 100  | 2.3509          | 0.0155           | 0.1011        | 0.0261          |
  | 2.4053        | 0.88  | 110  | 2.3261          | 0.015            | 0.0901        | 0.0246          |
  | 2.9896        | 0.96  | 120  | 2.3235          | 0.018            | 0.0916        | 0.0292          |
  
  
  ### Framework versions
  
  - Transformers 4.21.3
  - Pytorch 1.12.1+cu113
  - Datasets 1.2.1
  - Tokenizers 0.12.1
  