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leomaurodesenv/electra-base-discriminator-jailbreakv-28k

Abliteration classifier · v1.0.0
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  • no classification signals present (no abliterated, uncensored, or known producer/method markers)
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Downloads · lifetime
159
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Model age
2d ago
created 2026-09-13
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Sep 13 → Sep 16 · 4 snapshots · spans 3 days

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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
2026-09-13 21:56
Last updated on HF
2026-09-16 00:18

Files by quantization

Auxiliary files 7 files 418 MB
model.safetensors 418 MB 09e6eeeb download
training_args.bin 5.14 KB 9e1bd4cc download
tokenizer.json 695 KB 05a08d51 download
README.md 2.16 KB 9b54147a 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-jailbreakv-28k
    results: []

electra-base-discriminator-jailbreakv-28k

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: 0.0000
  • Accuracy: 1.0

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
0.0003 1.0 1121 0.0001 1.0
0.0001 2.0 2242 0.0000 1.0
0.0000 3.0 3363 0.0000 1.0
0.0000 4.0 4484 0.0000 1.0
0.0000 5.0 5605 0.0000 1.0
0.0000 6.0 6726 0.0000 1.0
0.0000 7.0 7847 0.0000 1.0
0.0000 8.0 8968 0.0000 1.0
0.0000 9.0 10089 0.0000 1.0
0.0000 10.0 11210 0.0000 1.0

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. 2026-09-16End of traininged6d4bc2.2 KB
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  2. 2026-09-15Training in progress, epoch 1e126cae2.2 KB
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  3. 2026-09-15End of training32a45f42.2 KB
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  4. 2026-09-15Training in progress, epoch 1a039a3e2.1 KB
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  5. 2026-09-14End of training3e751192.2 KB
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  6. 2026-09-14Training in progress, epoch 1aa7e7fb2.1 KB
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  7. 2026-09-14End of training4b66b602.2 KB
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  8. 2026-09-14Training in progress, epoch 1621f2122.1 KB
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  9. 2026-09-13End of training4672e042.2 KB
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  10. 2026-09-13Training in progress, epoch 18b461bd2.2 KB
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