readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: CommitPredictor
    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. -->
  
  # CommitPredictor
  
  This model is a fine-tuned version of [microsoft/codebert-base-mlm](https://huggingface.co/microsoft/codebert-base-mlm) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.8427
  - Accuracy: 0.6409
  
  ## 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: 4
  - total_train_batch_size: 128
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 50
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | No log        | 1.0   | 292  | 2.2754          | 0.5767   |
  | 2.5787        | 2.0   | 584  | 2.2006          | 0.5877   |
  | 2.5787        | 3.0   | 876  | 2.0851          | 0.5953   |
  | 2.2167        | 4.0   | 1168 | 2.0148          | 0.6142   |
  | 2.2167        | 5.0   | 1460 | 1.9583          | 0.6144   |
  | 2.064         | 6.0   | 1752 | 1.8846          | 0.6309   |
  | 1.9626        | 7.0   | 2044 | 1.9399          | 0.6247   |
  | 1.9626        | 8.0   | 2336 | 1.8423          | 0.6401   |
  | 1.8671        | 9.0   | 2628 | 1.8065          | 0.6407   |
  | 1.8671        | 10.0  | 2920 | 1.7582          | 0.6507   |
  | 1.7957        | 11.0  | 3212 | 1.7978          | 0.6479   |
  | 1.7226        | 12.0  | 3504 | 1.8058          | 0.6521   |
  | 1.7226        | 13.0  | 3796 | 1.8427          | 0.6409   |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  