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
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Base model
microsoft/codebert-base