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kanishka/smolm-autoreg-bpe-counterfactual_babylm_naans_new-1e-4

sourceHugging Faceupdated 2y agoView on Hugging Face
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Model Card

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smolm-autoreg-bpe-counterfactualbabylmnaans_new-1e-4

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

  • —Loss: 3.4162
  • —Accuracy: 0.4067

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: 0.0001
  • —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
4.05141.0185954.23680.3093
3.56332.0371903.74250.3637
3.39233.0557853.57110.3809
3.28524.0743803.51500.3880
3.22255.0929753.44730.3934
3.17176.01115703.44660.3969
3.1287.01301653.42030.3993
3.09528.01487603.39990.4015
3.06339.01673553.40230.4025
3.040810.01859503.40200.4035
3.010411.02045453.39660.4037
2.987412.02231403.39440.4045
2.971213.02417353.38820.4057
2.945114.02603303.39600.4058
2.927715.02789253.40370.4061
2.908516.02975203.40480.4062
2.891417.03161153.40330.4061
2.877218.03347103.40940.4066
2.863519.03533053.41120.4067
2.850620.03719003.41620.4067

Framework versions

  • —Transformers 4.40.1
  • —Pytorch 2.1.0+cu121
  • —Datasets 2.16.1
  • —Tokenizers 0.19.1