---
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