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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-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-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: 0.5844 |
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- Accuracy Score: 0.6537 |
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- F1 Score: 0.5784 |
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- Precision Score: 0.5171 |
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- Recall Score: 0.6562 |
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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: 3 |
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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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| 0.6795 | 1.0 | 342 | 0.6435 | 0.6120 | 0.3099 | 0.1896 | 0.8470 | |
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| 0.6168 | 2.0 | 684 | 0.5960 | 0.6395 | 0.4316 | 0.2980 | 0.7824 | |
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| 0.5605 | 3.0 | 1026 | 0.5844 | 0.6537 | 0.5784 | 0.5171 | 0.6562 | |
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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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