readme: ---
  tags:
  - generated_from_trainer
  datasets:
  - kp20k
  metrics:
  - rouge
  model-index:
  - name: ED_keyphrase/
    results:
    - task:
        name: Sequence-to-sequence Language Modeling
        type: text2text-generation
      dataset:
        name: kp20k
        type: kp20k
        config: generation
        split: train[:15%]
        args: generation
      metrics:
      - name: Rouge1
        type: rouge
        value: 0.0784
  ---
  
  <!-- 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. -->
  
  # ED_keyphrase/
  
  This model is a fine-tuned version of [](https://huggingface.co/) on the kp20k dataset.
  It achieves the following results on the evaluation set:
  - Loss: 4.4436
  - Rouge1: 0.0784
  - Rouge2: 0.0159
  - Rougel: 0.0732
  - Rougelsum: 0.0732
  - Gen Len: 70.8515
  
  ## 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: 32
  - eval_batch_size: 32
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 64
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 5
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
  | 6.1614        | 1.0   | 664  | 5.2825          | 0.0866 | 0.0047 | 0.0767 | 0.0767    | 53.6569 |
  | 5.2585        | 2.0   | 1328 | 4.7707          | 0.0551 | 0.0087 | 0.0517 | 0.0518    | 83.1487 |
  | 4.8764        | 3.0   | 1992 | 4.5703          | 0.0634 | 0.0117 | 0.0594 | 0.0595    | 81.5616 |
  | 4.5709        | 4.0   | 2656 | 4.4749          | 0.0743 | 0.0145 | 0.0695 | 0.0695    | 72.9576 |
  | 4.4978        | 5.0   | 3320 | 4.4436          | 0.0784 | 0.0159 | 0.0732 | 0.0732    | 70.8515 |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  