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--- |
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license: apache-2.0 |
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base_model: jackaduma/SecBERT |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: cyner_secbert |
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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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# cyner_secbert |
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This model is a fine-tuned version of [jackaduma/SecBERT](https://huggingface.co/jackaduma/SecBERT) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1212 |
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- Precision: 0.7047 |
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- Recall: 0.5517 |
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- F1: 0.6189 |
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- Accuracy: 0.9723 |
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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: 8 |
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- eval_batch_size: 8 |
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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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- num_epochs: 10.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| 0.165 | 1.42 | 500 | 0.1212 | 0.7047 | 0.5517 | 0.6189 | 0.9723 | |
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| 0.04 | 2.84 | 1000 | 0.1647 | 0.6924 | 0.5147 | 0.5905 | 0.9705 | |
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| 0.0156 | 4.26 | 1500 | 0.1803 | 0.6769 | 0.5351 | 0.5977 | 0.9714 | |
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| 0.0087 | 5.68 | 2000 | 0.1866 | 0.6574 | 0.5415 | 0.5938 | 0.9713 | |
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| 0.0036 | 7.1 | 2500 | 0.2020 | 0.6740 | 0.5492 | 0.6052 | 0.9719 | |
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| 0.0024 | 8.52 | 3000 | 0.2036 | 0.6697 | 0.5568 | 0.6081 | 0.9720 | |
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| 0.0018 | 9.94 | 3500 | 0.2084 | 0.6682 | 0.5504 | 0.6036 | 0.9715 | |
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### Framework versions |
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- Transformers 4.36.0.dev0 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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