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leomaurodesenv/bert-base-uncased-jailbreakv-28k

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  • files 7
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  • author_summary 30 models
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Downloads · lifetime
354
150 last 30d - stable
Likes
16
Model age
6w ago
created 2026-09-13
Downloads over time
Now533→from0↑0%
01953915860 on Sep 13533 on Oct 31SepOct
Sep 13 → Oct 31 · 49 snapshots · spans 48 days

Genealogy 0 direct forks

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Metadata

License
mit
Tags
transformers safetensors bert text-classification generated_from_trainer base_model:google-bert/bert-base-uncased base_model:finetune:google-bert/bert-base-uncased license:apache-2.0 text-embeddings-inference endpoints_compatible region:us

Related

Total size
418 MB
Files
7
Quantizations
1
Registered
2026-09-13 15:56
Last updated on HF
2026-09-15 18:47

Files by quantization

Auxiliary files 7 files 418 MB
model.safetensors 418 MB 350a1ec1 download
training_args.bin 5.14 KB fbc43302 download
tokenizer.json 695 KB 05a08d51 download
README.md 2.01 KB 527c5e3a download
.gitattributes 1.48 KB a6344aac download
config.json 923 B 4a52bd90 download
tokenizer_config.json 322 B 76929107 download

README current version from Hugging Face


library_name: transformers
license: mit
base_model: FacebookAI/roberta-base
tags:

  • generated_from_trainer
    metrics:
  • accuracy
    model-index:
  • name: roberta-base-trustairlab-jailbreak-augmented
    results: []

roberta-base-trustairlab-jailbreak-augmented

This model is a fine-tuned version of FacebookAI/roberta-base on an unknown dataset.
It achieves the following results on the evaluation set:

  • Loss: 0.1497
  • Accuracy: 0.9564

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
0.7089 1.0 4240 0.2427 0.9236
0.2055 2.0 8480 0.1981 0.9365
0.1062 3.0 12720 0.1940 0.9459
0.2229 4.0 16960 0.1855 0.9521
0.3277 5.0 21200 0.1498 0.9559
0.2119 6.0 25440 0.1607 0.9595
0.0957 7.0 29680 0.1673 0.9591
0.0421 8.0 33920 0.1794 0.9594

Framework versions

  • Transformers 5.2.0
  • Pytorch 2.10.0+cu128
  • Datasets 4.5.0
  • Tokenizers 0.22.2

README history 10 versions

The author's README evolved over time. Click a version to see its content at that point.

  1. 2026-09-15End of trainingcd08adb2.1 KB
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  2. 2026-09-15Training in progress, epoch 154d088c1.9 KB
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  3. 2026-09-15End of training9cf5a182.1 KB
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  4. 2026-09-15Training in progress, epoch 18226d772.1 KB
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  5. 2026-09-14End of training82cdff42.1 KB
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  6. 2026-09-14Training in progress, epoch 1467587e2.1 KB
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  7. 2026-09-14End of training9afb8be2.1 KB
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  8. 2026-09-14Training in progress, epoch 1e1011691.8 KB
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  9. 2026-09-13End of training616ba7a2.1 KB
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  10. 2026-09-13Training in progress, epoch 143e0a332 KB
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