readme: ---
  tags:
  - generated_from_trainer
  model-index:
  - name: gbert-large
    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. -->
  
  # gbert-large
  
  This model is a fine-tuned version of deepset/gbert-large 
  
  It was fine-tuned on poetry from Projekt Gutenberg in order to do masked language modeling tasks in poetry generation (synonym creation for rythm and to find rhyming pairs) 
  
  - Loss: 2.1519
  
  ## 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: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 10
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss |
  |:-------------:|:-----:|:-----:|:---------------:|
  | 2.7515        | 1.0   | 2481  | 2.5493          |
  | 2.5626        | 2.0   | 4962  | 2.4392          |
  | 2.4839        | 3.0   | 7443  | 2.3692          |
  | 2.4082        | 4.0   | 9924  | 2.3425          |
  | 2.3109        | 5.0   | 12405 | 2.2934          |
  | 2.2551        | 6.0   | 14886 | 2.2582          |
  | 2.2154        | 7.0   | 17367 | 2.2062          |
  | 2.2003        | 8.0   | 19848 | 2.1962          |
  | 2.1616        | 9.0   | 22329 | 2.1991          |
  | 2.1462        | 10.0  | 24810 | 2.1519          |
  
  
  ### Framework versions
  
  - Transformers 4.19.4
  - Pytorch 1.11.0+cu113
  - Datasets 2.2.2
  - Tokenizers 0.12.1
  