readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: summarise
    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
  
  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: 1.0497
  - Rouge2 Precision: 0.3109
  - Rouge2 Recall: 0.406
  - Rouge2 Fmeasure: 0.3375
  
  ## Model description
  
  More information needed
  
  ## Intended uses & limitations
  
  max_input_length = 3072
  
  max_output_length = 1000
  
  led.config.max_length = 1000
  
  led.config.min_length = 100
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:----------------:|:-------------:|:---------------:|
  | 1.7163        | 0.22  | 10   | 1.2307          | 0.1428           | 0.5118        | 0.2089          |
  | 1.632         | 0.44  | 20   | 1.1337          | 0.36             | 0.3393        | 0.3181          |
  | 1.0916        | 0.67  | 30   | 1.0738          | 0.2693           | 0.3487        | 0.2731          |
  | 1.573         | 0.89  | 40   | 1.0497          | 0.3109           | 0.406         | 0.3375          |
  
  
  ### Framework versions
  
  - Transformers 4.21.3
  - Pytorch 1.12.1+cu113
  - Datasets 1.2.1
  - Tokenizers 0.12.1
  