metadata

library_name: peft
base_model: microsoft/codebert-base
tags:
  - generated_from_trainer
datasets:
  - code_search_net
model-index:
  - name: codebert-model
    results: []

codebert-model

This model is a fine-tuned version of 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