---
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
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# 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