End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: bert-base-uncased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: bert-base-detect-jailbreak
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# bert-base-detect-jailbreak
+
+This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1676
+- Accuracy: 0.9463
+- Precision: 0.7756
+- Recall: 0.7089
+- F1: 0.7407
+- Balanced Accuracy: 0.8420
+- Mcc: 0.7118
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 2e-05
+- train_batch_size: 16
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     | Balanced Accuracy | Mcc    |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-----------------:|:------:|
+| 0.16          | 1.0   | 685  | 0.1588          | 0.9504   | 0.7967    | 0.7305 | 0.7622 | 0.8539            | 0.7354 |
+| 0.1094        | 2.0   | 1370 | 0.1731          | 0.9477   | 0.7711    | 0.7380 | 0.7542 | 0.8557            | 0.7252 |
+| 0.1255        | 3.0   | 2055 | 0.1881          | 0.9502   | 0.8045    | 0.7154 | 0.7573 | 0.8471            | 0.7312 |
+| 0.0686        | 4.0   | 2740 | 0.2148          | 0.9507   | 0.8056    | 0.7204 | 0.7606 | 0.8496            | 0.7347 |
+| 0.048         | 5.0   | 3425 | 0.2793          | 0.9493   | 0.8136    | 0.6927 | 0.7483 | 0.8367            | 0.7232 |
+| 0.0276        | 6.0   | 4110 | 0.3122          | 0.9477   | 0.7960    | 0.6977 | 0.7436 | 0.8380            | 0.7166 |
+| 0.0194        | 7.0   | 4795 | 0.3583          | 0.9480   | 0.8224    | 0.6650 | 0.7354 | 0.8237            | 0.7118 |
+| 0.0173        | 8.0   | 5480 | 0.3802          | 0.9461   | 0.7809    | 0.7003 | 0.7384 | 0.8381            | 0.7097 |
+| 0.0121        | 9.0   | 6165 | 0.3939          | 0.9463   | 0.7880    | 0.6927 | 0.7373 | 0.8350            | 0.7093 |
+| 0.0052        | 10.0  | 6850 | 0.3984          | 0.9472   | 0.7914    | 0.6977 | 0.7416 | 0.8377            | 0.7141 |
+
+
+### Framework versions
+
+- Transformers 4.57.2
+- Pytorch 2.9.0+cu126
+- Datasets 4.0.0
+- Tokenizers 0.22.1

model.safetensors

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