wav2vec2-jailbreak-classification
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: 0.0099
- Accuracy: 0.9959
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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- 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: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.0229 | 1.0 | 62 | 0.0578 | 0.9898 |
0.005 | 2.0 | 124 | 0.0264 | 0.9939 |
0.0024 | 3.0 | 186 | 0.0129 | 0.9959 |
0.0016 | 4.0 | 248 | 0.0013 | 1.0 |
0.0013 | 5.0 | 310 | 0.0012 | 1.0 |
Framework versions
- Transformers 4.53.3
- Pytorch 2.7.1+cu126
- Datasets 4.0.0
- Tokenizers 0.21.2
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Base model
facebook/wav2vec2-base