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lapa-llm/fineweb-nemotron-edu-score

sourceHugging Facemitupdated 11mo agoView on Hugging Face
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fineweb-nemotron-edu-score

This model is a fine-tuned version of intfloat/multilingual-e5-base on an transferred from English dataset. It achieves the following results on the evaluation set:

  • —Loss: 0.0489
  • —Precision: 0.9571
  • —Recall: 0.9605
  • —F1 Macro: 0.9588
  • —Accuracy: 0.9632

Model description

This model measure educational value of the given text for humans, as labelled by Nemotron-340B model.

Intended uses & limitations

Data filtering and evaluation of pretraining data at scale.

Training and evaluation data

Take a look at https://github.com/lapa-llm/lapa-llm/blob/main/pretraining/quality-classifiers/fineweb_hf.py

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • —learning_rate: 3e-05
  • —trainbatchsize: 32
  • —evalbatchsize: 128
  • —seed: 0
  • —distributed_type: multi-GPU
  • —num_devices: 8
  • —totaltrainbatch_size: 256
  • —totalevalbatch_size: 1024
  • —optimizer: Use OptimizerNames.ADAMWTORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
  • —lrschedulertype: linear
  • —num_epochs: 4

Training results

Training LossEpochStepValidation LossPrecisionRecallF1 MacroAccuracy
No log001.02570.33340.50.40010.6668
0.05621.37932000.05200.95370.95490.95430.9593
0.05172.75864000.04890.95710.96050.95880.9632

Framework versions

  • —Transformers 4.56.1
  • —Pytorch 2.6.0a0+ecf3bae40a.nv25.01
  • —Datasets 4.0.0
  • —Tokenizers 0.22.0