metadata
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: []
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 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5530
- Accuracy: 0.7686
- F1: 0.7679
- Precision: 0.7527
- Recall: 0.7837
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: 2
- eval_batch_size: 2
- seed: 4711
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.5818 | 1.0 | 996 | 0.4514 | 0.7510 | 0.7353 | 0.7647 | 0.7081 |
| 0.3357 | 2.0 | 1992 | 0.4397 | 0.7615 | 0.7695 | 0.7289 | 0.8150 |
| 0.2098 | 3.0 | 2988 | 0.5530 | 0.7686 | 0.7679 | 0.7527 | 0.7837 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0