CoolFace
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kanishka/smolm-autoreg-bpe-counterfactual-babylm-indef-naan-rerun-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-indef-naan-rerun-seed_211-1e-3

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

  • —Loss: 3.3899
  • —Accuracy: 0.4102

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
3.6091.0185953.77460.3579
3.38972.0371903.59010.3796
3.26053.0557853.49730.3907
3.18274.0743803.41890.3974
3.12665.0929753.38740.4008
3.07976.01115703.36260.4042
3.04877.01301653.35720.4056
3.0138.01487603.34430.4064
2.98879.01673553.31740.4100
2.964710.01859503.34430.4084
2.939111.02045453.34800.4084
2.916812.02231403.35590.4091
2.893213.02417353.35120.4097
2.879214.02603303.35880.4096
2.858915.02789253.35030.4104
2.838316.02975203.35210.4112
2.817617.03161153.36570.4106
2.798418.03347103.36840.4110
2.778219.03533053.38710.4102
2.760320.03719003.38990.4102

Framework versions

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