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smolm-autoreg-bpe-counterfactual-babylm-aann-prototypical_only-3e-4

This model was trained from scratch on the kanishka/counterfactual_babylm_prototypical_only dataset. It achieves the following results on the evaluation set:

  • Loss: 3.4082
  • Accuracy: 0.4080

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: 0.0003
  • train_batch_size: 32
  • eval_batch_size: 64
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 32000
  • num_epochs: 20.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy
3.7341 1.0 18593 3.8768 0.3468
3.4322 2.0 37186 3.6158 0.3751
3.2902 3.0 55779 3.4817 0.3883
3.21 4.0 74372 3.4286 0.3960
3.1498 5.0 92965 3.4151 0.3978
3.0981 6.0 111558 3.3790 0.4022
3.0651 7.0 130151 3.3750 0.4034
3.0292 8.0 148744 3.3879 0.4041
3.0031 9.0 167337 3.3773 0.4046
2.9713 10.0 185930 3.3769 0.4061
2.9529 11.0 204523 3.3778 0.4069
2.9286 12.0 223116 3.3612 0.4077
2.9065 13.0 241709 3.3686 0.4073
2.8837 14.0 260302 3.3861 0.4078
2.8621 15.0 278895 3.3851 0.4077
2.8487 16.0 297488 3.3876 0.4080
2.8243 17.0 316081 3.3908 0.4081
2.8078 18.0 334674 3.3952 0.4082
2.7887 19.0 353267 3.4020 0.4082
2.7716 20.0 371860 3.4082 0.4080

Framework versions

  • Transformers 4.36.0
  • Pytorch 2.1.1+cu121
  • Datasets 2.15.0
  • Tokenizers 0.15.0
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Dataset used to train kanishka/smolm-autoreg-bpe-counterfactual-babylm-aann-prototypical_only-3e-4

Evaluation results

  • Accuracy on kanishka/counterfactual_babylm_prototypical_only
    self-reported
    0.408