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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: answerdotai/ModernBERT-base |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: ModernBERT-base-ft-code-defect-detection-10e-4k |
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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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# ModernBERT-base-ft-code-defect-detection-10e-4k |
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This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.0516 |
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- Accuracy Score: 0.6369 |
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- F1 Score: 0.6091 |
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- Precision Score: 0.6159 |
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- Recall Score: 0.6025 |
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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: 8e-05 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- optimizer: Use adamw_torch with betas=(0.9,0.98) and epsilon=1e-06 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy Score | F1 Score | Precision Score | Recall Score | |
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|:-------------:|:-----:|:----:|:---------------:|:--------------:|:--------:|:---------------:|:------------:| |
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| 0.6768 | 1.0 | 342 | 0.6130 | 0.6358 | 0.5728 | 0.5315 | 0.6210 | |
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| 0.5902 | 2.0 | 684 | 0.5828 | 0.6654 | 0.5421 | 0.4311 | 0.7301 | |
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| 0.5346 | 3.0 | 1026 | 0.5995 | 0.6585 | 0.4744 | 0.3355 | 0.8096 | |
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| 0.4583 | 4.0 | 1368 | 0.6115 | 0.6812 | 0.6085 | 0.5394 | 0.6979 | |
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| 0.3722 | 5.0 | 1710 | 0.6749 | 0.6482 | 0.6197 | 0.6239 | 0.6156 | |
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| 0.2896 | 6.0 | 2052 | 0.8197 | 0.6490 | 0.6087 | 0.5944 | 0.6237 | |
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| 0.2234 | 7.0 | 2394 | 0.9451 | 0.6490 | 0.6019 | 0.5777 | 0.6282 | |
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| 0.1655 | 8.0 | 2736 | 1.1632 | 0.6354 | 0.6115 | 0.6247 | 0.5989 | |
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| 0.1151 | 9.0 | 3078 | 1.4168 | 0.6387 | 0.6063 | 0.6056 | 0.6070 | |
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| 0.0684 | 10.0 | 3420 | 2.0516 | 0.6369 | 0.6091 | 0.6159 | 0.6025 | |
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### Framework versions |
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- Transformers 4.48.0.dev0 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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