---
base_model: bigcode/starcoderbase-1b
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
model-index:
- name: bigcode-starcoderbase-1b-finetuned-defect-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-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: 0.9591
- Accuracy: 0.7666
- Roc Auc: 0.7662
- Precision: 0.7657
- Recall: 0.7523

## 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 | Roc Auc | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------:|:---------:|:------:|
| 0.7596        | 1.0   | 996  | 0.5406          | 0.6852   | 0.6897  | 0.6264    | 0.8813 |
| 0.4855        | 2.0   | 1993 | 0.4691          | 0.7377   | 0.7396  | 0.6954    | 0.8237 |
| 0.3547        | 3.0   | 2989 | 0.4832          | 0.7480   | 0.7479  | 0.7410    | 0.7441 |
| 0.2463        | 4.0   | 3986 | 0.5966          | 0.7628   | 0.7646  | 0.7196    | 0.8428 |
| 0.1633        | 5.0   | 4980 | 0.9591          | 0.7666   | 0.7662  | 0.7657    | 0.7523 |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2