readme: ---
  license: mit
  tags:
  - generated_from_trainer
  datasets:
  - gem
  model_index:
  - name: BART-large-commongen
    results:
    - task:
        name: Sequence-to-sequence Language Modeling
        type: text2text-generation
      dataset:
        name: gem
        type: gem
        args: common_gen
  ---
  
  <!-- 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. -->
  
  # BART-large-commongen
  
  This model is a fine-tuned version of [facebook/bart-large](https://huggingface.co/facebook/bart-large) on the gem dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.1409
  - Spice: 0.4009
  
  ## 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: 0.0001
  - train_batch_size: 32
  - eval_batch_size: 32
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 1000
  - training_steps: 6317
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Spice  |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 10.1086       | 0.05  | 100  | 4.9804          | 0.3736 |
  | 4.4168        | 0.09  | 200  | 2.4402          | 0.4079 |
  | 1.8158        | 0.14  | 300  | 1.1096          | 0.4258 |
  | 1.1723        | 0.19  | 400  | 1.0845          | 0.4086 |
  | 1.0894        | 0.24  | 500  | 1.0727          | 0.423  |
  | 1.0949        | 0.28  | 600  | 1.0889          | 0.4224 |
  | 1.0773        | 0.33  | 700  | 1.0977          | 0.4201 |
  | 1.0708        | 0.38  | 800  | 1.1157          | 0.4213 |
  | 1.0663        | 0.43  | 900  | 1.1798          | 0.421  |
  | 1.0985        | 0.47  | 1000 | 1.1611          | 0.4025 |
  | 1.0561        | 0.52  | 1100 | 1.1048          | 0.421  |
  | 1.0594        | 0.57  | 1200 | 1.2044          | 0.3626 |
  | 1.0689        | 0.62  | 1300 | 1.1409          | 0.4009 |
  
  
  ### Framework versions
  
  - Transformers 4.9.2
  - Pytorch 1.9.0+cu102
  - Datasets 1.11.1.dev0
  - Tokenizers 0.10.3
  