---
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
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# 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