smolm-autoreg-bpe-counterfactual_babylm_measure_nps_as_singular_new-1e-3
This model was trained from scratch on the kanishka/counterfactual_babylm_measure_nps_as_singular_new dataset. It achieves the following results on the evaluation set:
- Loss: 3.4116
- Accuracy: 0.4111
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 | 18602 | 3.7886 | 0.3573 |
3.379 | 2.0 | 37204 | 3.5653 | 0.3798 |
3.2515 | 3.0 | 55806 | 3.4692 | 0.3918 |
3.1729 | 4.0 | 74408 | 3.4193 | 0.3983 |
3.1139 | 5.0 | 93010 | 3.3907 | 0.4026 |
3.0709 | 6.0 | 111612 | 3.3642 | 0.4043 |
3.0297 | 7.0 | 130214 | 3.3545 | 0.4067 |
2.9988 | 8.0 | 148816 | 3.3596 | 0.4080 |
2.9717 | 9.0 | 167418 | 3.3723 | 0.4087 |
2.9432 | 10.0 | 186020 | 3.3579 | 0.4093 |
2.9217 | 11.0 | 204622 | 3.3701 | 0.4098 |
2.8986 | 12.0 | 223224 | 3.3646 | 0.4103 |
2.8745 | 13.0 | 241826 | 3.3676 | 0.4105 |
2.8518 | 14.0 | 260428 | 3.3750 | 0.4110 |
2.8328 | 15.0 | 279030 | 3.3722 | 0.4111 |
2.8089 | 16.0 | 297632 | 3.3797 | 0.4115 |
2.7911 | 17.0 | 316234 | 3.3882 | 0.4109 |
2.773 | 18.0 | 334836 | 3.3951 | 0.4115 |
2.7517 | 19.0 | 353438 | 3.4023 | 0.4112 |
2.7342 | 20.0 | 372040 | 3.4116 | 0.4111 |
Framework versions
- Transformers 4.38.0
- Pytorch 2.3.1+cu121
- Datasets 2.16.1
- Tokenizers 0.15.2
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Dataset used to train kanishka/smolm-autoreg-bpe-counterfactual_babylm_measure_nps_as_singular_new-1e-3
Evaluation results
- Accuracy on kanishka/counterfactual_babylm_measure_nps_as_singular_newself-reported0.411