---
tags:
- generated_from_trainer
datasets:
- kanishka/counterfactual-babylm-random_removal
metrics:
- accuracy
model-index:
- name: smolm-autoreg-bpe-counterfactual-babylm-random_removal-1e-4
  results:
  - task:
      name: Causal Language Modeling
      type: text-generation
    dataset:
      name: kanishka/counterfactual-babylm-random_removal
      type: kanishka/counterfactual-babylm-random_removal
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.40612524722144594
---

<!-- 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-random_removal-1e-4

This model was trained from scratch on the kanishka/counterfactual-babylm-random_removal dataset.
It achieves the following results on the evaluation set:
- Loss: 3.4340
- Accuracy: 0.4061

## 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 4.0553        | 1.0   | 18586  | 4.2477          | 0.3104   |
| 3.572         | 2.0   | 37172  | 3.7583          | 0.3622   |
| 3.394         | 3.0   | 55758  | 3.5857          | 0.3796   |
| 3.2886        | 4.0   | 74344  | 3.4992          | 0.3883   |
| 3.2289        | 5.0   | 92930  | 3.4729          | 0.3932   |
| 3.176         | 6.0   | 111516 | 3.4186          | 0.3977   |
| 3.1344        | 7.0   | 130102 | 3.4150          | 0.3990   |
| 3.0979        | 8.0   | 148688 | 3.4191          | 0.4009   |
| 3.0701        | 9.0   | 167274 | 3.4137          | 0.4016   |
| 3.0392        | 10.0  | 185860 | 3.4201          | 0.4029   |
| 3.0154        | 11.0  | 204446 | 3.4057          | 0.4039   |
| 2.9892        | 12.0  | 223032 | 3.4152          | 0.4046   |
| 2.9688        | 13.0  | 241618 | 3.4149          | 0.4047   |
| 2.9542        | 14.0  | 260204 | 3.4117          | 0.4051   |
| 2.9338        | 15.0  | 278790 | 3.4235          | 0.4052   |
| 2.9143        | 16.0  | 297376 | 3.4130          | 0.4059   |
| 2.8967        | 17.0  | 315962 | 3.4165          | 0.4059   |
| 2.8824        | 18.0  | 334548 | 3.4299          | 0.4059   |
| 2.863         | 19.0  | 353134 | 3.4312          | 0.4061   |
| 2.8521        | 20.0  | 371720 | 3.4340          | 0.4061   |


### Framework versions

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