---
tags:
- generated_from_trainer
datasets:
- kanishka/counterfactual_babylm_aann_indef_articles_with_pl_nouns_removal
metrics:
- accuracy
model-index:
- name: smolm-autoreg-bpe-counterfactual-babylm-indef_articles_with_pl_nouns-removal-1e-4
  results:
  - task:
      name: Causal Language Modeling
      type: text-generation
    dataset:
      name: kanishka/counterfactual_babylm_aann_indef_articles_with_pl_nouns_removal
      type: kanishka/counterfactual_babylm_aann_indef_articles_with_pl_nouns_removal
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.40685132585936323
---

<!-- 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-indef_articles_with_pl_nouns-removal-1e-4

This model was trained from scratch on the kanishka/counterfactual_babylm_aann_indef_articles_with_pl_nouns_removal dataset.
It achieves the following results on the evaluation set:
- Loss: 3.4203
- Accuracy: 0.4069

## 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 4.0459        | 1.0   | 18601  | 4.2512          | 0.3119   |
| 3.5647        | 2.0   | 37202  | 3.7353          | 0.3623   |
| 3.3872        | 3.0   | 55803  | 3.5881          | 0.3793   |
| 3.2888        | 4.0   | 74404  | 3.5327          | 0.3882   |
| 3.2221        | 5.0   | 93005  | 3.4746          | 0.3931   |
| 3.1699        | 6.0   | 111606 | 3.4427          | 0.3965   |
| 3.1314        | 7.0   | 130207 | 3.4235          | 0.3991   |
| 3.0928        | 8.0   | 148808 | 3.4092          | 0.4010   |
| 3.0595        | 9.0   | 167409 | 3.4074          | 0.4025   |
| 3.0344        | 10.0  | 186010 | 3.4222          | 0.4023   |
| 3.0028        | 11.0  | 204611 | 3.4034          | 0.4043   |
| 2.9831        | 12.0  | 223212 | 3.4022          | 0.4043   |
| 2.9626        | 13.0  | 241813 | 3.4060          | 0.4054   |
| 2.9442        | 14.0  | 260414 | 3.4008          | 0.4060   |
| 2.9257        | 15.0  | 279015 | 3.4016          | 0.4065   |
| 2.909         | 16.0  | 297616 | 3.4037          | 0.4065   |
| 2.8892        | 17.0  | 316217 | 3.4125          | 0.4063   |
| 2.872         | 18.0  | 334818 | 3.4132          | 0.4066   |
| 2.8568        | 19.0  | 353419 | 3.4158          | 0.4069   |
| 2.8385        | 20.0  | 372020 | 3.4203          | 0.4069   |


### Framework versions

- Transformers 4.36.0
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0