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README.md
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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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runs/Jan03_12-58-51_a8222cca6e0a/events.out.tfevents.1735909134.a8222cca6e0a.7508.0
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version https://git-lfs.github.com/spec/v1
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size
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version https://git-lfs.github.com/spec/v1
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size 8321
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