Athipan01/codebert-model

1---2library_name: peft3base_model: microsoft/codebert-base4tags:5- generated_from_trainer6datasets:7- code_search_net8model-index:9- name: codebert-model10  results: []11---12 13<!-- This model card has been generated automatically according to the information the Trainer had access to. You14should probably proofread and complete it, then remove this comment. -->15 16# codebert-model17 18This model is a fine-tuned version of [microsoft/codebert-base](https://huggingface.co/microsoft/codebert-base) on the code_search_net dataset.19It achieves the following results on the evaluation set:20- eval_loss: 0.834621- eval_model_preparation_time: 0.005722- eval_accuracy: {'accuracy': 0.21967491508976225}23- eval_f1: {'f1': 0.0}24- eval_runtime: 9384.638225- eval_samples_per_second: 0.87826- eval_steps_per_second: 0.1127- step: 028 29## Model description30 31More information needed32 33## Intended uses & limitations34 35More information needed36 37## Training and evaluation data38 39More information needed40 41## Training procedure42 43### Training hyperparameters44 45The following hyperparameters were used during training:46- learning_rate: 5e-0547- train_batch_size: 848- eval_batch_size: 849- seed: 4250- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments51- lr_scheduler_type: linear52- num_epochs: 353 54### Framework versions55 56- PEFT 0.15.257- Transformers 4.51.358- Pytorch 2.6.0+cu12459- Datasets 3.6.060- Tokenizers 0.21.1