CoolFace
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kanishka/smolm-autoreg-bpe-counterfactual-babylm-indef-naan-rerun-seed_1024-1e-3

sourceHugging Faceupdated 3y agoView on Hugging Face
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Model Card

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smolm-autoreg-bpe-counterfactual-babylm-indef-naan-rerun-seed_1024-1e-3

This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:

  • —Loss: 3.4016
  • —Accuracy: 0.4111

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: 0.001
  • —trainbatchsize: 32
  • —evalbatchsize: 64
  • —seed: 1024
  • —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • —lrschedulertype: linear
  • —lrschedulerwarmup_steps: 32000
  • —num_epochs: 20.0
  • —mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation LossAccuracy
3.59891.0185953.78720.3601
3.38812.0371903.56720.3809
3.25483.0557853.49350.3930
3.17774.0743803.42290.3988
3.125.0929753.40400.4021
3.08196.01115703.37160.4050
3.04417.01301653.35070.4065
3.0148.01487603.35300.4076
2.98319.01673553.33540.4096
2.956110.01859503.36540.4080
2.937711.02045453.35760.4101
2.914612.02231403.36490.4106
2.892713.02417353.36460.4105
2.871814.02603303.35910.4108
2.852115.02789253.36360.4114
2.834816.02975203.38070.4111
2.813117.03161153.37720.4109
2.792118.03347103.38740.4110
2.774319.03533053.39280.4112
2.761520.03719003.40160.4111

Framework versions

  • —Transformers 4.35.0
  • —Pytorch 2.1.0+cu121
  • —Datasets 2.12.0
  • —Tokenizers 0.14.1