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agentlans/granite-embedding-107m-multilingual-chat-screener

sourceHugging Faceapache-2.0updated 8mo agoView on Hugging Face
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granite-embedding-107m-multilingual-chat-screener

This model was trained to filter multilingual multi-turn conversation datasets according to the requirements set out in agentlans/chat-annotated.

  • —Input format: <|user|>prompt<|assistant|>reply<|user|>prompt2<|assistant|>reply2.... For very long messages, use the special token <|...|>.
  • —Output: whether the input conversation meets the minimal safety, quality, and refusal criteria.

This model is a fine-tuned version of ibm-granite/granite-embedding-107m-multilingual. It achieves the following results on the evaluation set:

  • —Loss: 0.4081
  • —Accuracy: 0.8229
  • —Num Input Tokens Seen: 51197440

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
  • —trainbatchsize: 8
  • —evalbatchsize: 8
  • —seed: 42
  • —optimizer: Use OptimizerNames.ADAMWTORCHFUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • —lrschedulertype: 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