readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - enoriega/odinsynth_dataset
  model-index:
  - name: rule_learning_margin_1mm
    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_margin_1mm
  
  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: 0.3806
  - Margin Accuracy: 0.8239
  
  ## 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: 4
  - eval_batch_size: 4
  - seed: 42
  - gradient_accumulation_steps: 2000
  - 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 | Margin Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:---------------:|
  | 0.6482        | 0.16  | 20   | 0.6494          | 0.7263          |
  | 0.5151        | 0.32  | 40   | 0.5088          | 0.7792          |
  | 0.4822        | 0.48  | 60   | 0.4429          | 0.8045          |
  | 0.4472        | 0.64  | 80   | 0.4265          | 0.8107          |
  | 0.4352        | 0.8   | 100  | 0.4155          | 0.8132          |
  | 0.4335        | 0.96  | 120  | 0.4128          | 0.8116          |
  | 0.4113        | 1.12  | 140  | 0.4119          | 0.8142          |
  | 0.4186        | 1.28  | 160  | 0.4075          | 0.8120          |
  | 0.42          | 1.44  | 180  | 0.4072          | 0.8123          |
  | 0.4175        | 1.6   | 200  | 0.4080          | 0.8130          |
  | 0.4097        | 1.76  | 220  | 0.4031          | 0.8128          |
  | 0.397         | 1.92  | 240  | 0.4004          | 0.8130          |
  | 0.4115        | 2.08  | 260  | 0.3979          | 0.8136          |
  | 0.4108        | 2.24  | 280  | 0.3940          | 0.8167          |
  | 0.4125        | 2.4   | 300  | 0.3879          | 0.8218          |
  | 0.4117        | 2.56  | 320  | 0.3848          | 0.8217          |
  | 0.3967        | 2.72  | 340  | 0.3818          | 0.8231          |
  | 0.3947        | 2.88  | 360  | 0.3813          | 0.8240          |
  
  
  ### Framework versions
  
  - Transformers 4.19.2
  - Pytorch 1.11.0
  - Datasets 2.2.1
  - Tokenizers 0.12.1
  