readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - enoriega/odinsynth_dataset
  model-index:
  - name: rule_learning_test
    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. -->
  
  # rule_learning_test
  
  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the enoriega/odinsynth_dataset dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1255
  
  ## 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: 8
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 1000
  - total_train_batch_size: 8000
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 3.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss |
  |:-------------:|:-----:|:----:|:---------------:|
  | 0.1764        | 0.32  | 20   | 0.2303          |
  | 0.145         | 0.64  | 40   | 0.1470          |
  | 0.129         | 0.96  | 60   | 0.1321          |
  | 0.1256        | 1.29  | 80   | 0.1265          |
  | 0.1304        | 1.61  | 100  | 0.1252          |
  | 0.1235        | 1.93  | 120  | 0.1260          |
  | 0.125         | 2.26  | 140  | 0.1261          |
  | 0.1263        | 2.58  | 160  | 0.1262          |
  | 0.1244        | 2.9   | 180  | 0.1256          |
  
  
  ### Framework versions
  
  - Transformers 4.19.2
  - Pytorch 1.11.0
  - Datasets 2.2.1
  - Tokenizers 0.12.1
  