| --- |
| base_model: bigcode/starcoderbase-1b |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| - precision |
| - recall |
| model-index: |
| - name: bigcode-starcoderbase-1b-finetuned-defect-cwe-group-detection |
| 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. --> |
|
|
| # bigcode-starcoderbase-1b-finetuned-defect-cwe-group-detection |
|
|
| This model is a fine-tuned version of [bigcode/starcoderbase-1b](https://huggingface.co/bigcode/starcoderbase-1b) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.7332 |
| - Accuracy: 0.7603 |
| - Precision: 0.7915 |
| - Recall: 0.5933 |
|
|
| ## 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: 2e-05 |
| - train_batch_size: 8 |
| - eval_batch_size: 8 |
| - seed: 4711 |
| - gradient_accumulation_steps: 4 |
| - total_train_batch_size: 32 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 5 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:| |
| | No log | 1.0 | 462 | 0.5916 | 0.7378 | 0.5849 | 0.4951 | |
| | 0.7929 | 2.0 | 925 | 0.4926 | 0.7760 | 0.7951 | 0.5958 | |
| | 0.4345 | 3.0 | 1387 | 0.6382 | 0.7316 | 0.7372 | 0.6156 | |
| | 0.3051 | 4.0 | 1850 | 0.6161 | 0.7580 | 0.7736 | 0.6097 | |
| | 0.2378 | 4.99 | 2310 | 0.7332 | 0.7603 | 0.7915 | 0.5933 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.38.1 |
| - Pytorch 2.2.0+cu121 |
| - Datasets 2.17.1 |
| - Tokenizers 0.15.2 |
| |
