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

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

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

  • Loss: 3.4056
  • 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: 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
3.6071 1.0 18588 3.7805 0.3590
3.3943 2.0 37176 3.5796 0.3806
3.2625 3.0 55764 3.4678 0.3915
3.1838 4.0 74352 3.3962 0.3998
3.1277 5.0 92940 3.3849 0.4017
3.0813 6.0 111528 3.3874 0.4040
3.0519 7.0 130116 3.3394 0.4079
3.0181 8.0 148704 3.3441 0.4085
2.9888 9.0 167292 3.3545 0.4088
2.9602 10.0 185880 3.3501 0.4088
2.942 11.0 204468 3.3509 0.4095
2.9174 12.0 223056 3.3709 0.4093
2.8989 13.0 241644 3.3608 0.4107
2.8757 14.0 260232 3.3651 0.4101
2.8506 15.0 278820 3.3638 0.4109
2.8373 16.0 297408 3.3724 0.4107
2.8195 17.0 315996 3.3819 0.4108
2.7983 18.0 334584 3.3819 0.4110
2.7786 19.0 353172 3.3970 0.4103
2.7635 20.0 371760 3.4056 0.4103

Framework versions

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