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: 0.6902
Accuracy: 0.7715
Precision: 0.8036
Recall: 0.5867

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	0.4904	0.7800	0.6028	0.5178
0.5739	2.0	925	0.4917	0.7985	0.8159	0.5552
0.3111	3.0	1387	0.6582	0.7918	0.7907	0.5901
0.2395	4.0	1850	0.6238	0.7800	0.8018	0.6132
0.2047	4.99	2310	0.6902	0.7715	0.8036	0.5867

Framework versions

Transformers 4.38.1
Pytorch 2.2.0+cu121
Datasets 2.17.1
Tokenizers 0.15.2

mcanoglu/deepseek-ai-deepseek-coder-1.3b-base-finetuned-defect-cwe-group-detection

deepseek-ai-deepseek-coder-1.3b-base-finetuned-defect-cwe-group-detection

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

mcanoglu/
deepseek-ai-deepseek-coder-1.3b-base-finetuned-defect-cwe-group-detection