CoolFace
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kanishka/smolm-autoreg-bpe-counterfactual-babylm-pipps_and_keys_to_it_all_10k-1e-3

sourceHugging Faceupdated 3y agoView on Hugging Face
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Model Card

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smolm-autoreg-bpe-counterfactual-babylm-pippsandkeystoitall10k-1e-3

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

  • —Loss: 3.3502
  • —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: 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
3.61571.0188443.71430.3599
3.39792.0376883.50620.3804
3.26633.0565323.39500.3932
3.18874.0753763.36940.3977
3.13285.0942203.33610.4009
3.09256.01130643.32360.4038
3.05377.01319083.31650.4050
3.02898.01507523.31420.4063
2.99799.01695963.29590.4083
2.973410.01884403.29760.4096
2.950111.02072843.30260.4094
2.930212.02261283.30360.4097
2.906713.02449723.31010.4103
2.88514.02638163.30630.4106
2.868615.02826603.31950.4098
2.847416.03015043.32750.4106
2.823517.03203483.32970.4108
2.809118.03391923.33850.4105
2.789919.03580363.34330.4102
2.771820.03768803.35020.4102

Framework versions

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