bge-small-en-v1.5-prompt-screener
This model was trained to test English prompts and single-turn English conversations using the fine-grained data in the agentlans/prompt-screening-dataset
- Input format:
<|user|>prompt<|assistant|>reply. For very long messages, use the special token<|...|>. - Output: whether the prompt and answer meet minimal safety, quality, and refusal criteria.
This model is a fine-tuned version of BAAI/bge-small-en-v1.5. It achieves the following results on the evaluation set:
- Loss: 0.2614
- Accuracy: 0.9052
- Num Input Tokens Seen: 92144640
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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5.0
Training results
Framework versions
- Transformers 5.0.0.dev0
- Pytorch 2.9.1+cu128
- Datasets 4.4.1
- Tokenizers 0.22.1
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Base model
BAAI/bge-small-en-v1.5