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

smolm-autoreg-bpe-counterfactual_babylm_aanns_dtanns-seed_211-1e-4

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

  • Loss: 3.4323
  • Accuracy: 0.4055

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
4.0524 1.0 18595 4.2811 0.3084
3.5716 2.0 37190 3.7750 0.3615
3.3913 3.0 55785 3.6008 0.3779
3.2921 4.0 74380 3.5102 0.3883
3.2283 5.0 92975 3.4789 0.3930
3.1673 6.0 111570 3.4379 0.3962
3.127 7.0 130165 3.4175 0.3988
3.0935 8.0 148760 3.4272 0.3998
3.0679 9.0 167355 3.4150 0.4011
3.0402 10.0 185950 3.4148 0.4023
3.0082 11.0 204545 3.4169 0.4029
2.988 12.0 223140 3.4130 0.4035
2.967 13.0 241735 3.3969 0.4045
2.9457 14.0 260330 3.4080 0.4049
2.9268 15.0 278925 3.4129 0.4045
2.911 16.0 297520 3.4159 0.4047
2.8964 17.0 316115 3.4221 0.4051
2.8758 18.0 334710 3.4286 0.4054
2.858 19.0 353305 3.4265 0.4054
2.8493 20.0 371900 3.4323 0.4055

Framework versions

  • Transformers 4.38.0
  • Pytorch 2.3.1+cu121
  • Datasets 2.16.1
  • Tokenizers 0.15.2