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

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

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

  • Loss: 3.4044
  • Accuracy: 0.4112

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: 128
  • 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
3.5972 1.0 18595 3.7848 0.3596
3.3783 2.0 37190 3.5924 0.3811
3.2531 3.0 55785 3.4617 0.3919
3.1768 4.0 74380 3.4215 0.3983
3.1209 5.0 92975 3.3891 0.4028
3.0769 6.0 111570 3.3921 0.4039
3.0421 7.0 130165 3.3538 0.4070
3.0089 8.0 148760 3.3607 0.4076
2.9842 9.0 167355 3.3492 0.4094
2.9595 10.0 185950 3.3596 0.4097
2.9382 11.0 204545 3.3544 0.4101
2.9125 12.0 223140 3.3588 0.4107
2.8929 13.0 241735 3.3648 0.4109
2.8689 14.0 260330 3.3662 0.4110
2.8494 15.0 278925 3.3657 0.4116
2.8316 16.0 297520 3.3748 0.4114
2.8151 17.0 316115 3.3865 0.4114
2.797 18.0 334710 3.3825 0.4115
2.7759 19.0 353305 3.4028 0.4111
2.7566 20.0 371900 3.4044 0.4112

Framework versions

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