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metadata
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: smolm-autoreg-bpe-counterfactual-babylm-only_other_det_removal-1e-4
    results: []

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

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

  • Loss: 3.4247
  • Accuracy: 0.4065

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
4.0532 1.0 18597 4.2579 0.3085
3.566 2.0 37194 3.7605 0.3620
3.3886 3.0 55791 3.5962 0.3806
3.2899 4.0 74388 3.5175 0.3894
3.2214 5.0 92985 3.4618 0.3939
3.1702 6.0 111582 3.4252 0.3979
3.1294 7.0 130179 3.4255 0.3995
3.0899 8.0 148776 3.4190 0.4010
3.0639 9.0 167373 3.4041 0.4027
3.0329 10.0 185970 3.4231 0.4029
3.0093 11.0 204567 3.4100 0.4045
2.9859 12.0 223164 3.4097 0.4049
2.9662 13.0 241761 3.4043 0.4053
2.9424 14.0 260358 3.4046 0.4057
2.928 15.0 278955 3.4079 0.4059
2.908 16.0 297552 3.4119 0.4061
2.8912 17.0 316149 3.4119 0.4062
2.8716 18.0 334746 3.4159 0.4064
2.8589 19.0 353343 3.4223 0.4065
2.8424 20.0 371940 3.4247 0.4065

Framework versions

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