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assoni2002/wav2vec2-jailbreak-classification_new

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  • files 6
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  • author_summary 5 models
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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
92
9 last 30d - cooling
Likes
0
Descendants
1
in 1 direct fork
Model age
14mo ago
created 2025-07-31
Downloads over time
Now95→from38↑150%
35577910138 on Jul 30, 202595 on Oct 1295 on Oct 11Jul '25Sep '25Nov '25JanMarMayJulSep
Jul 30, 2025 → Oct 12 · 103 snapshots · spans 439 days

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Metadata

License
apache-2.0
Tags
transformers safetensors wav2vec2 audio-classification generated_from_trainer base_model:facebook/wav2vec2-base base_model:finetune:facebook/wav2vec2-base license:apache-2.0 endpoints_compatible region:us

Related

Total size
361 MB
Files
6
Quantizations
1
Registered
2026-08-22 13:56
Last updated on HF
2025-08-06 20:41

Files by quantization

Auxiliary files 6 files 361 MB
model.safetensors 361 MB 401ceedb download
training_args.bin 5.70 KB 5a89eec9 download
config.json 2.29 KB c9a3d02f download
README.md 1.86 KB 75107acc download
.gitattributes 1.48 KB a6344aac download
preprocessor_config.json 215 B a0b7227f download

README current version from Hugging Face


library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:

  • generated_from_trainer
    metrics:
  • accuracy
    model-index:
  • name: wav2vec2-jailbreak-classification_new
    results: []

wav2vec2-jailbreak-classification_new

This model is a fine-tuned version of facebook/wav2vec2-base on an unknown dataset.
It achieves the following results on the evaluation set:

  • Loss: 0.0627
  • 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: 1e-05
  • train_batch_size: 32
  • eval_batch_size: 64
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 128
  • optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.562 1.0 31 0.4704 0.9693
0.2247 2.0 62 0.1643 0.9959
0.0949 3.0 93 0.0689 0.9980
0.0591 4.0 124 0.0476 0.9959
0.0381 5.0 155 0.0331 0.9980
0.0333 6.0 186 0.0314 0.9980

Framework versions

  • Transformers 4.53.3
  • Pytorch 2.7.1+cu126
  • Datasets 4.0.0
  • Tokenizers 0.21.2

README history 1 version

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

  1. 2025-08-01End of training4f2bc7d1.9 KB
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