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--- |
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base_model: microsoft/unixcoder-base |
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library_name: peft |
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license: apache-2.0 |
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metrics: |
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- accuracy |
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- f1 |
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- precision |
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- recall |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: CodeGenDetect-Unixcoder_Lora |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# CodeGenDetect-Unixcoder_Lora |
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This model is a fine-tuned version of [microsoft/unixcoder-base](https://huggingface.co/microsoft/unixcoder-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0266 |
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- Accuracy: 0.9927 |
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- F1: 0.9927 |
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- Precision: 0.9927 |
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- Recall: 0.9927 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 128 |
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- eval_batch_size: 128 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 5 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| 0.0349 | 1.02 | 4000 | 0.0342 | 0.9887 | 0.9887 | 0.9887 | 0.9887 | |
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| 0.0244 | 2.05 | 8000 | 0.0279 | 0.9916 | 0.9916 | 0.9916 | 0.9916 | |
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| 0.0234 | 3.07 | 12000 | 0.0260 | 0.9923 | 0.9923 | 0.9923 | 0.9923 | |
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| 0.0249 | 4.1 | 16000 | 0.0266 | 0.9927 | 0.9927 | 0.9927 | 0.9927 | |
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### Framework versions |
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- PEFT 0.9.0 |
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- Transformers 4.38.2 |
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- Pytorch 2.5.1+rocm6.2 |
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- Datasets 2.21.0 |
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- Tokenizers 0.15.2 |
