ai-code-detector-finetuned – AI Model by Sab286 | AlphaNeural AI

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Sab286/
ai-code-detector-finetuned

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text-classification

generated_from_trainer

microsoft/codebert-base

text-embeddings-inference

endpoints_compatible

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ai-code-detector-finetuned

This model is a fine-tuned version of microsoft/codebert-base on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.0001
Accuracy: 1.0
F1: 1.0
Tpr: 1.0
Tnr: 1.0

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: 4
eval_batch_size: 8
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 200
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Tpr	Tnr
0.0004	1.0	479	0.0136	0.9941	0.9942	0.9884	1.0
0.0001	2.0	958	0.0001	1.0	1.0	1.0	1.0
0.0001	3.0	1437	0.0000	1.0	1.0	1.0	1.0
0.0000	4.0	1916	0.0000	1.0	1.0	1.0	1.0
0.0000	5.0	2395	0.0000	1.0	1.0	1.0	1.0

Framework versions

Transformers 5.9.0
Pytorch 2.12.0+cu130
Datasets 4.8.5
Tokenizers 0.22.2