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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: distilbert/distilbert-base-uncased
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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model-index:
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- name: LLMGUARD-x
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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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# LLMGUARD-x
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This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.8936
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- Accuracy: 0.7084
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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: 0.0003
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- train_batch_size: 16
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- eval_batch_size: 8
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- seed: 42
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 32
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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 |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|
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| 0.7163 | 1.0 | 1332 | 0.7270 | 0.7649 |
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| 0.6975 | 2.0 | 2664 | 0.7528 | 0.7467 |
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| 0.6864 | 3.0 | 3996 | 0.8722 | 0.7360 |
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| 0.7611 | 4.0 | 5328 | 1.0374 | 0.7241 |
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| 0.814 | 5.0 | 6660 | 1.0346 | 0.6928 |
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| 0.72 | 6.0 | 7992 | 1.1184 | 0.7023 |
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| 0.9093 | 7.0 | 9324 | 1.1419 | 0.6240 |
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| 1.1656 | 8.0 | 10656 | 1.3607 | 0.5707 |
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| 1.0431 | 9.0 | 11988 | 1.1602 | 0.6464 |
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| 0.9917 | 10.0 | 13320 | 1.2718 | 0.6244 |
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| 1.1101 | 11.0 | 14652 | 1.1973 | 0.6158 |
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| 1.1094 | 12.0 | 15984 | 1.1642 | 0.6128 |
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| 1.0501 | 13.0 | 17316 | 1.2592 | 0.6205 |
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| 0.9821 | 14.0 | 18648 | 1.1294 | 0.6543 |
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| 1.026 | 15.0 | 19980 | 1.1774 | 0.6338 |
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| 1.0622 | 16.0 | 21312 | 1.2379 | 0.6338 |
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| 1.0199 | 17.0 | 22644 | 1.2025 | 0.6111 |
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| 0.9903 | 18.0 | 23976 | 1.1224 | 0.6233 |
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| 0.9544 | 19.0 | 25308 | 1.1009 | 0.6436 |
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| 0.977 | 20.0 | 26640 | 1.0633 | 0.6500 |
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| 0.9161 | 21.0 | 27972 | 1.0481 | 0.6507 |
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| 0.8816 | 22.0 | 29304 | 1.0135 | 0.6620 |
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| 0.8664 | 23.0 | 30636 | 1.0119 | 0.6830 |
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| 0.8187 | 24.0 | 31968 | 0.9681 | 0.6915 |
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| 0.7799 | 25.0 | 33300 | 1.0124 | 0.6719 |
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| 0.7501 | 26.0 | 34632 | 0.9501 | 0.6928 |
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| 0.7308 | 27.0 | 35964 | 0.9140 | 0.6963 |
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| 0.6957 | 28.0 | 37296 | 0.9413 | 0.7007 |
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| 0.6812 | 29.0 | 38628 | 0.9235 | 0.7055 |
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| 0.6701 | 30.0 | 39960 | 0.9108 | 0.7065 |
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| 0.649 | 31.0 | 41292 | 0.9012 | 0.7084 |
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| 0.6345 | 32.0 | 42624 | 0.8936 | 0.7084 |
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### Framework versions
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- Transformers 4.48.0.dev0
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- Pytorch 2.5.1+cu124
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- Datasets 3.2.0
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- Tokenizers 0.21.0
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