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leomaurodesenv/electra-base-discriminator-trustairlab-jailbreak-augmented

Abliteration classifier · v1.0.0
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Unclassified

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UNKNOWN
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  • no classification signals present (no abliterated, uncensored, or known producer/method markers)
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Model age
4d ago
created 2026-09-12
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Metadata

License
apache-2.0
Tags
transformers safetensors electra text-classification generated_from_trainer base_model:google/electra-base-discriminator base_model:finetune:google/electra-base-discriminator license:apache-2.0 endpoints_compatible region:us

Related

Total size
418 MB
Files
7
Quantizations
1
Registered
2026-09-12 00:55
Last updated on HF
2026-09-13 11:45

Files by quantization

Auxiliary files 7 files 418 MB
model.safetensors 418 MB b416e7cb download
training_args.bin 5.14 KB 1f2df05a download
tokenizer.json 695 KB 05a08d51 download
README.md 1.86 KB 0906add8 download
.gitattributes 1.48 KB a6344aac download
config.json 1.01 KB f7796a57 download
tokenizer_config.json 322 B 76929107 download

README current version from Hugging Face


library_name: transformers
license: apache-2.0
base_model: google/electra-base-discriminator
tags:

  • generated_from_trainer
    metrics:
  • accuracy
    model-index:
  • name: electra-base-discriminator-trustairlab-jailbreak
    results: []

electra-base-discriminator-trustairlab-jailbreak

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

  • Loss: 0.1905
  • Accuracy: 0.9388

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
0.2734 1.0 605 0.2173 0.9359
0.1792 2.0 1210 0.1904 0.9384
0.2315 3.0 1815 0.2045 0.9392
0.1664 4.0 2420 0.1956 0.9379
0.0775 5.0 3025 0.2416 0.9388

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. 2026-09-13End of training50173792.1 KB
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  2. 2026-09-13Training in progress, epoch 15f9c5a02 KB
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  3. 2026-09-13End of training3cf58c22.1 KB
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  4. 2026-09-12Training in progress, epoch 13b012951.9 KB
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  5. 2026-09-12End of trainingbb9e43a2.1 KB
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  6. 2026-09-12Training in progress, epoch 1808acbb2 KB
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  7. 2026-09-12End of training684ef672.1 KB
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  8. 2026-09-12Training in progress, epoch 1b3ed0492 KB
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  9. 2026-09-12End of training43554b32.1 KB
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  10. 2026-09-12Training in progress, epoch 143c17ea1.9 KB
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