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kanishka/smolm-autoreg-bpe-counterfactual-babylm-all_det_removal-seed_211-1e-3

sourceHugging Faceupdated 3y agoView on Hugging Face
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Model Card

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smolm-autoreg-bpe-counterfactual-babylm-alldetremoval-seed_211-1e-3

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

  • —Loss: 3.3932
  • —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: 211
  • —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
3.60691.0185953.79790.3582
3.3852.0371903.55750.3809
3.26063.0557853.42870.3945
3.17644.0743803.41490.3985
3.12515.0929753.39290.4017
3.07956.01115703.38340.4039
3.04547.01301653.35270.4071
3.01858.01487603.34560.4078
2.98799.01673553.36030.4079
2.959910.01859503.34280.4097
2.938211.02045453.34250.4117
2.912412.02231403.35370.4100
2.891513.02417353.35430.4104
2.871314.02603303.34780.4116
2.854515.02789253.35610.4110
2.830616.02975203.37030.4106
2.81717.03161153.37760.4109
2.793818.03347103.38610.4107
2.776819.03533053.38230.4116
2.75920.03719003.39320.4111

Framework versions

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