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metadata
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: smolm-autoreg-bpe-counterfactual-babylm-pipps_removal-seed_1024-1e-3
    results: []

smolm-autoreg-bpe-counterfactual-babylm-pipps_removal-seed_1024-1e-3

This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 3.4120
  • Accuracy: 0.4103

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
  • train_batch_size: 32
  • eval_batch_size: 64
  • seed: 1024
  • 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
3.5992 1.0 18593 3.7873 0.3590
3.3841 2.0 37186 3.5957 0.3798
3.2517 3.0 55779 3.4368 0.3935
3.1729 4.0 74372 3.4158 0.3977
3.1228 5.0 92965 3.4132 0.4017
3.074 6.0 111558 3.3903 0.4035
3.0396 7.0 130151 3.3731 0.4067
3.0136 8.0 148744 3.3697 0.4065
2.9841 9.0 167337 3.3754 0.4067
2.9561 10.0 185930 3.3766 0.4088
2.9356 11.0 204523 3.3834 0.4089
2.9099 12.0 223116 3.3625 0.4105
2.8924 13.0 241709 3.3680 0.4097
2.8738 14.0 260302 3.3766 0.4103
2.8485 15.0 278895 3.3746 0.4108
2.834 16.0 297488 3.3823 0.4107
2.8108 17.0 316081 3.3894 0.4108
2.7936 18.0 334674 3.4001 0.4101
2.7783 19.0 353267 3.4030 0.4107
2.755 20.0 371860 3.4120 0.4103

Framework versions

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