| --- |
| library_name: peft |
| base_model: microsoft/codebert-base |
| tags: |
| - generated_from_trainer |
| datasets: |
| - code_search_net |
| model-index: |
| - name: codebert-model |
| 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. --> |
|
|
| # codebert-model |
|
|
| This model is a fine-tuned version of [microsoft/codebert-base](https://huggingface.co/microsoft/codebert-base) on the code_search_net dataset. |
| It achieves the following results on the evaluation set: |
| - eval_loss: 0.8346 |
| - eval_model_preparation_time: 0.0057 |
| - eval_accuracy: {'accuracy': 0.21967491508976225} |
| - eval_f1: {'f1': 0.0} |
| - eval_runtime: 9384.6382 |
| - eval_samples_per_second: 0.878 |
| - eval_steps_per_second: 0.11 |
| - step: 0 |
| |
| ## 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 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - num_epochs: 3 |
| |
| ### Framework versions |
| |
| - PEFT 0.15.2 |
| - Transformers 4.51.3 |
| - Pytorch 2.6.0+cu124 |
| - Datasets 3.6.0 |
| - Tokenizers 0.21.1 |
