library_name: transformers
license: apache-2.0
base_model: google-bert/bert-base-uncased
tags:
- generated_from_trainer
metrics: - accuracy
model-index: - name: bert-base-uncased-trustairlab-jailbreak-augmented
results: []
bert-base-uncased-trustairlab-jailbreak-augmented
This model is a fine-tuned version of google-bert/bert-base-uncased on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1342
- Accuracy: 0.9599
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.5340 | 1.0 | 4240 | 0.2055 | 0.9272 |
| 0.2717 | 2.0 | 8480 | 0.1629 | 0.9479 |
| 0.1147 | 3.0 | 12720 | 0.1591 | 0.9542 |
| 0.2369 | 4.0 | 16960 | 0.1604 | 0.9573 |
| 0.1724 | 5.0 | 21200 | 0.1340 | 0.9597 |
| 0.0943 | 6.0 | 25440 | 0.1593 | 0.9613 |
| 0.0648 | 7.0 | 29680 | 0.1767 | 0.9611 |
| 0.0906 | 8.0 | 33920 | 0.1880 | 0.9614 |
Framework versions
- Transformers 5.2.0
- Pytorch 2.10.0+cu128
- Datasets 4.5.0
- Tokenizers 0.22.2