readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  model-index:
  - name: CodeBertaCLM
    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. -->
  
  # CodeBertaCLM
  
  This model is a fine-tuned version of [microsoft/codebert-base](https://huggingface.co/microsoft/codebert-base) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.5831
  - Accuracy: 0.0144
  - F1: 0.0144
  - Bleu4: 0.0421
  
  ## 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
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 200
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | Bleu4  |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:------:|
  | 3.6734        | 1.0   | 1673  | 3.6884          | 0.0159   | 0.0159 | 0.0131 |
  | 2.8139        | 2.0   | 3346  | 3.2517          | 0.0164   | 0.0164 | 0.0192 |
  | 2.4176        | 3.0   | 5019  | 3.0747          | 0.0178   | 0.0178 | 0.0332 |
  | 2.2785        | 4.0   | 6692  | 2.9695          | 0.0174   | 0.0174 | 0.0347 |
  | 2.1557        | 5.0   | 8365  | 2.8886          | 0.0171   | 0.0171 | 0.0377 |
  | 2.0357        | 6.0   | 10038 | 2.8313          | 0.0158   | 0.0158 | 0.0394 |
  | 1.9615        | 7.0   | 11711 | 2.7865          | 0.0158   | 0.0158 | 0.0393 |
  | 1.8982        | 8.0   | 13384 | 2.7498          | 0.0147   | 0.0147 | 0.0399 |
  | 1.8233        | 9.0   | 15057 | 2.7195          | 0.0149   | 0.0149 | 0.0430 |
  | 1.7866        | 10.0  | 16730 | 2.6925          | 0.0157   | 0.0157 | 0.0485 |
  | 1.7237        | 11.0  | 18403 | 2.6745          | 0.0146   | 0.0146 | 0.0419 |
  | 1.6757        | 12.0  | 20076 | 2.6616          | 0.0146   | 0.0146 | 0.0403 |
  | 1.6452        | 13.0  | 21749 | 2.6377          | 0.0147   | 0.0147 | 0.0403 |
  | 1.6036        | 14.0  | 23422 | 2.6216          | 0.0145   | 0.0145 | 0.0397 |
  | 1.5818        | 15.0  | 25095 | 2.6169          | 0.0150   | 0.0150 | 0.0413 |
  | 1.5389        | 16.0  | 26768 | 2.6047          | 0.0146   | 0.0146 | 0.0420 |
  | 1.5131        | 17.0  | 28441 | 2.5940          | 0.0153   | 0.0153 | 0.0433 |
  | 1.4822        | 18.0  | 30114 | 2.5899          | 0.0145   | 0.0145 | 0.0404 |
  | 1.4461        | 19.0  | 31787 | 2.5812          | 0.0150   | 0.0150 | 0.0423 |
  | 1.4149        | 20.0  | 33460 | 2.5841          | 0.0148   | 0.0148 | 0.0418 |
  | 1.3933        | 21.0  | 35133 | 2.5783          | 0.0139   | 0.0139 | 0.0386 |
  | 1.3752        | 22.0  | 36806 | 2.5730          | 0.0151   | 0.0151 | 0.0444 |
  | 1.3412        | 23.0  | 38479 | 2.5709          | 0.0149   | 0.0149 | 0.0419 |
  | 1.3307        | 24.0  | 40152 | 2.5699          | 0.0143   | 0.0143 | 0.0424 |
  | 1.2909        | 25.0  | 41825 | 2.5648          | 0.0144   | 0.0144 | 0.0416 |
  | 1.2679        | 26.0  | 43498 | 2.5615          | 0.0145   | 0.0145 | 0.0420 |
  | 1.2603        | 27.0  | 45171 | 2.5626          | 0.0148   | 0.0148 | 0.0433 |
  | 1.2203        | 28.0  | 46844 | 2.5670          | 0.0148   | 0.0148 | 0.0410 |
  | 1.2134        | 29.0  | 48517 | 2.5536          | 0.0147   | 0.0147 | 0.0422 |
  | 1.1907        | 30.0  | 50190 | 2.5701          | 0.0139   | 0.0139 | 0.0404 |
  | 1.1702        | 31.0  | 51863 | 2.5722          | 0.0143   | 0.0143 | 0.0424 |
  | 1.1555        | 32.0  | 53536 | 2.5679          | 0.0144   | 0.0144 | 0.0434 |
  | 1.1371        | 33.0  | 55209 | 2.5694          | 0.0146   | 0.0146 | 0.0431 |
  | 1.1189        | 34.0  | 56882 | 2.5692          | 0.0141   | 0.0141 | 0.0422 |
  | 1.0989        | 35.0  | 58555 | 2.5831          | 0.0144   | 0.0144 | 0.0421 |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  