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leomaurodesenv/roberta-base-disaster-tweet-jailbreaking-augmented

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  • author_summary 30 models
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Abliteration classifier · v1.0.0
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Downloads · lifetime
230
8 last 30d - cooling
Likes
0
Model age
7w ago
created 2026-08-21
Downloads over time
Now231→from168↑38%
165189213237168 on Aug 19231 on Oct 11231 on Oct 4AugSepOct
Aug 19 → Oct 11 · 48 snapshots · spans 53 days

Genealogy 0 direct forks

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Metadata

License
mit
Tags
transformers safetensors roberta text-classification generated_from_trainer base_model:FacebookAI/roberta-base base_model:finetune:FacebookAI/roberta-base license:mit text-embeddings-inference endpoints_compatible region:us

Related

Total size
476 MB
Files
7
Quantizations
1
Registered
2026-08-22 13:56
Last updated on HF
2026-08-22 00:26

Files by quantization

Auxiliary files 7 files 479 MB
model.safetensors 476 MB 20ff395a download
training_args.bin 5.14 KB a0b0fd99 download
tokenizer.json 3.39 MB 7e19d907 download
README.md 2.08 KB 03540fbd download
.gitattributes 1.48 KB a6344aac download
config.json 847 B 513a45f3 download
tokenizer_config.json 359 B a6d24b8e 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-disaster-tweet-jailbreaking-augmented
    results: []

roberta-base-disaster-tweet-jailbreaking-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: 0.1776
  • Accuracy: 0.9717

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
  • 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
0.6028 1.0 1680 0.5656 0.7125
0.4653 2.0 3360 0.4785 0.8196
0.4870 3.0 5040 0.3783 0.8982
0.0446 4.0 6720 0.3292 0.9318
0.1025 5.0 8400 0.2381 0.9565
0.0945 6.0 10080 0.2062 0.9670
0.0005 7.0 11760 0.1778 0.9717
0.0009 8.0 13440 0.1945 0.9723
0.0002 9.0 15120 0.1848 0.9759
0.0001 10.0 16800 0.1804 0.9765

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. 2026-08-22End of traininge8238622.1 KB
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  2. 2026-08-21Training in progress, epoch 141eee861.8 KB
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  3. 2026-08-21End of training2a56da41.8 KB
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  4. 2026-08-21Training in progress, epoch 12aef6131.8 KB
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  5. 2026-08-21End of trainingc5f7a242.1 KB
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  6. 2026-08-21Training in progress, epoch 180baeba1.7 KB
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  7. 2026-08-21End of training374d92b2.1 KB
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  8. 2026-08-21Training in progress, epoch 1f72c9771.8 KB
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  9. 2026-08-21End of training779db642.1 KB
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  10. 2026-08-21Training in progress, epoch 15eee7b41.7 KB
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