---
tags:
- generated_from_trainer
datasets:
- kanishka/counterfactual_babylm_naans_new
metrics:
- accuracy
model-index:
- name: smolm-autoreg-bpe-counterfactual_babylm_naans_new-1e-4
  results:
  - task:
      name: Causal Language Modeling
      type: text-generation
    dataset:
      name: kanishka/counterfactual_babylm_naans_new
      type: kanishka/counterfactual_babylm_naans_new
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.4066641958384616
---

<!-- 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_naans_new-1e-4

This model was trained from scratch on the kanishka/counterfactual_babylm_naans_new dataset.
It achieves the following results on the evaluation set:
- Loss: 3.4162
- Accuracy: 0.4067

## 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 4.0514        | 1.0   | 18595  | 4.2368          | 0.3093   |
| 3.5633        | 2.0   | 37190  | 3.7425          | 0.3637   |
| 3.3923        | 3.0   | 55785  | 3.5711          | 0.3809   |
| 3.2852        | 4.0   | 74380  | 3.5150          | 0.3880   |
| 3.2225        | 5.0   | 92975  | 3.4473          | 0.3934   |
| 3.1717        | 6.0   | 111570 | 3.4466          | 0.3969   |
| 3.128         | 7.0   | 130165 | 3.4203          | 0.3993   |
| 3.0952        | 8.0   | 148760 | 3.3999          | 0.4015   |
| 3.0633        | 9.0   | 167355 | 3.4023          | 0.4025   |
| 3.0408        | 10.0  | 185950 | 3.4020          | 0.4035   |
| 3.0104        | 11.0  | 204545 | 3.3966          | 0.4037   |
| 2.9874        | 12.0  | 223140 | 3.3944          | 0.4045   |
| 2.9712        | 13.0  | 241735 | 3.3882          | 0.4057   |
| 2.9451        | 14.0  | 260330 | 3.3960          | 0.4058   |
| 2.9277        | 15.0  | 278925 | 3.4037          | 0.4061   |
| 2.9085        | 16.0  | 297520 | 3.4048          | 0.4062   |
| 2.8914        | 17.0  | 316115 | 3.4033          | 0.4061   |
| 2.8772        | 18.0  | 334710 | 3.4094          | 0.4066   |
| 2.8635        | 19.0  | 353305 | 3.4112          | 0.4067   |
| 2.8506        | 20.0  | 371900 | 3.4162          | 0.4067   |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.19.1