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End of training
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metadata
tags:
  - generated_from_trainer
datasets:
  - kanishka/counterfactual-babylm-random_removal
metrics:
  - accuracy
model-index:
  - name: smolm-autoreg-bpe-counterfactual-babylm-random_removal-1e-4
    results:
      - task:
          name: Causal Language Modeling
          type: text-generation
        dataset:
          name: kanishka/counterfactual-babylm-random_removal
          type: kanishka/counterfactual-babylm-random_removal
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.40612524722144594

smolm-autoreg-bpe-counterfactual-babylm-random_removal-1e-4

This model was trained from scratch on the kanishka/counterfactual-babylm-random_removal dataset. It achieves the following results on the evaluation set:

  • Loss: 3.4340
  • Accuracy: 0.4061

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: 42
  • 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
4.0553 1.0 18586 4.2477 0.3104
3.572 2.0 37172 3.7583 0.3622
3.394 3.0 55758 3.5857 0.3796
3.2886 4.0 74344 3.4992 0.3883
3.2289 5.0 92930 3.4729 0.3932
3.176 6.0 111516 3.4186 0.3977
3.1344 7.0 130102 3.4150 0.3990
3.0979 8.0 148688 3.4191 0.4009
3.0701 9.0 167274 3.4137 0.4016
3.0392 10.0 185860 3.4201 0.4029
3.0154 11.0 204446 3.4057 0.4039
2.9892 12.0 223032 3.4152 0.4046
2.9688 13.0 241618 3.4149 0.4047
2.9542 14.0 260204 3.4117 0.4051
2.9338 15.0 278790 3.4235 0.4052
2.9143 16.0 297376 3.4130 0.4059
2.8967 17.0 315962 3.4165 0.4059
2.8824 18.0 334548 3.4299 0.4059
2.863 19.0 353134 3.4312 0.4061
2.8521 20.0 371720 3.4340 0.4061

Framework versions

  • Transformers 4.37.2
  • Pytorch 2.1.0+cu121
  • Datasets 2.16.1
  • Tokenizers 0.15.1