---
tags:
- generated_from_trainer
datasets:
- kanishka/counterfactual-babylm-random_removal
metrics:
- accuracy
model-index:
- name: smolm-autoreg-bpe-counterfactual-babylm-random_removal-3e-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: 0.4106218559881334
---

<!-- 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-3e-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: 3.4045
- Accuracy: 0.4106

## 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: 0.0003
- 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 3.7431        | 1.0   | 18586  | 3.8860          | 0.3481   |
| 3.4382        | 2.0   | 37172  | 3.6288          | 0.3759   |
| 3.2958        | 3.0   | 55758  | 3.5019          | 0.3891   |
| 3.2055        | 4.0   | 74344  | 3.4541          | 0.3957   |
| 3.1533        | 5.0   | 92930  | 3.4028          | 0.4006   |
| 3.1056        | 6.0   | 111516 | 3.3805          | 0.4035   |
| 3.0671        | 7.0   | 130102 | 3.3833          | 0.4042   |
| 3.0331        | 8.0   | 148688 | 3.3669          | 0.4069   |
| 3.0072        | 9.0   | 167274 | 3.3616          | 0.4083   |
| 2.9771        | 10.0  | 185860 | 3.3777          | 0.4078   |
| 2.9534        | 11.0  | 204446 | 3.3741          | 0.4089   |
| 2.9279        | 12.0  | 223032 | 3.3845          | 0.4092   |
| 2.9063        | 13.0  | 241618 | 3.3689          | 0.4105   |
| 2.8913        | 14.0  | 260204 | 3.3711          | 0.4105   |
| 2.8704        | 15.0  | 278790 | 3.3779          | 0.4099   |
| 2.8491        | 16.0  | 297376 | 3.3760          | 0.4112   |
| 2.83          | 17.0  | 315962 | 3.3752          | 0.4116   |
| 2.8136        | 18.0  | 334548 | 3.3912          | 0.4108   |
| 2.7924        | 19.0  | 353134 | 3.3984          | 0.4107   |
| 2.7792        | 20.0  | 371720 | 3.4045          | 0.4106   |


### Framework versions

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