---
license: other
base_model: deepseek-ai/deepseek-coder-1.3b-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: deepseek-ai-deepseek-coder-1.3b-base-finetuned-defect-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. -->

# deepseek-ai-deepseek-coder-1.3b-base-finetuned-defect-detection

This model is a fine-tuned version of [deepseek-ai/deepseek-coder-1.3b-base](https://huggingface.co/deepseek-ai/deepseek-coder-1.3b-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8154
- Accuracy: 0.7877
- F1: 0.7861
- Precision: 0.7736
- Recall: 0.7991

## 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 | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.5701        | 1.0   | 996  | 0.4446          | 0.7417   | 0.7633 | 0.6910    | 0.8525 |
| 0.3448        | 2.0   | 1993 | 0.4246          | 0.7681   | 0.7490 | 0.7944    | 0.7086 |
| 0.2305        | 3.0   | 2989 | 0.4693          | 0.7912   | 0.7924 | 0.7701    | 0.8160 |
| 0.1564        | 4.0   | 3986 | 0.5977          | 0.7836   | 0.7790 | 0.7774    | 0.7806 |
| 0.1102        | 5.0   | 4980 | 0.8154          | 0.7877   | 0.7861 | 0.7736    | 0.7991 |


### Framework versions

- Transformers 4.38.0
- Pytorch 2.2.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2