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metadata
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: >-
      smolm-autoreg-bpe-counterfactual-babylm-measure_nps_as_singular-seed_211-1e-4
    results: []

smolm-autoreg-bpe-counterfactual-babylm-measure_nps_as_singular-seed_211-1e-4

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

  • Loss: 3.4453
  • Accuracy: 0.4059

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
  • train_batch_size: 32
  • eval_batch_size: 64
  • seed: 211
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 32000
  • num_epochs: 20.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy
4.0492 1.0 18601 4.2903 0.3076
3.5701 2.0 37202 3.7600 0.3619
3.3901 3.0 55803 3.5643 0.3811
3.2877 4.0 74404 3.4952 0.3893
3.2176 5.0 93005 3.4699 0.3940
3.1687 6.0 111606 3.4478 0.3967
3.1232 7.0 130207 3.4306 0.3992
3.0903 8.0 148808 3.4360 0.4007
3.0619 9.0 167409 3.4178 0.4020
3.0326 10.0 186010 3.4113 0.4025
3.0057 11.0 204611 3.4085 0.4036
2.9825 12.0 223212 3.4075 0.4043
2.9605 13.0 241813 3.4155 0.4047
2.9399 14.0 260414 3.4355 0.4047
2.9261 15.0 279015 3.4277 0.4055
2.9036 16.0 297616 3.4246 0.4057
2.8909 17.0 316217 3.4307 0.4058
2.8715 18.0 334818 3.4373 0.4058
2.8532 19.0 353419 3.4386 0.4062
2.8408 20.0 372020 3.4453 0.4059

Framework versions

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