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kanishka/smolm-autoreg-bpe-counterfactual-babylm-pipps_10k-3e-4

sourceHugging Faceupdated 3y agoView on Hugging Face
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Model Card

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smolm-autoreg-bpe-counterfactual-babylm-pipps_10k-3e-4

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

  • —Loss: 3.3363
  • —Accuracy: 0.4103

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
  • —trainbatchsize: 32
  • —evalbatchsize: 64
  • —seed: 42
  • —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
3.73691.0187203.86740.3466
3.43642.0374403.55870.3765
3.29513.0561603.45720.3899
3.21094.0748803.38450.3966
3.15295.0936003.36010.4002
3.10476.01123203.32060.4031
3.06727.01310403.31010.4060
3.03098.01497603.30010.4068
3.00749.01684803.31870.4071
2.971910.01872003.29610.4085
2.955411.02059203.28810.4098
2.930412.02246403.31150.4086
2.911513.02433603.31580.4094
2.891714.02620803.29290.4107
2.869215.02808003.31070.4105
2.847716.02995203.32040.4102
2.828917.03182403.31730.4099
2.813218.03369603.32930.4102
2.796319.03556803.32990.4104
2.776520.03744003.33630.4103

Framework versions

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