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---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: smolm-autoreg-bpe-counterfactual-babylm-only_measure_nps_as_singular_removal-seed_211-1e-3
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# smolm-autoreg-bpe-counterfactual-babylm-only_measure_nps_as_singular_removal-seed_211-1e-3
This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.4372
- Accuracy: 0.4092
## 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: 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 3.6018 | 1.0 | 18600 | 3.7779 | 0.3590 |
| 3.3799 | 2.0 | 37200 | 3.5990 | 0.3799 |
| 3.2535 | 3.0 | 55800 | 3.4629 | 0.3928 |
| 3.1731 | 4.0 | 74400 | 3.4447 | 0.3979 |
| 3.1186 | 5.0 | 93000 | 3.4295 | 0.4009 |
| 3.0776 | 6.0 | 111600 | 3.4004 | 0.4034 |
| 3.0407 | 7.0 | 130200 | 3.3850 | 0.4053 |
| 3.0066 | 8.0 | 148800 | 3.3648 | 0.4061 |
| 2.9851 | 9.0 | 167400 | 3.3985 | 0.4074 |
| 2.953 | 10.0 | 186000 | 3.3964 | 0.4077 |
| 2.9321 | 11.0 | 204600 | 3.3816 | 0.4088 |
| 2.9082 | 12.0 | 223200 | 3.3780 | 0.4093 |
| 2.8881 | 13.0 | 241800 | 3.4020 | 0.4090 |
| 2.8698 | 14.0 | 260400 | 3.4057 | 0.4091 |
| 2.8441 | 15.0 | 279000 | 3.3906 | 0.4094 |
| 2.8256 | 16.0 | 297600 | 3.4051 | 0.4094 |
| 2.808 | 17.0 | 316200 | 3.4108 | 0.4093 |
| 2.7945 | 18.0 | 334800 | 3.4283 | 0.4094 |
| 2.7744 | 19.0 | 353400 | 3.4362 | 0.4094 |
| 2.7567 | 20.0 | 372000 | 3.4372 | 0.4092 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
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