---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: smolm-autoreg-bpe-counterfactual_babylm_aann_low_variability_numeral_1024-1e-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_aann_low_variability_numeral_1024-1e-3

This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.3975
- Accuracy: 0.4113

## 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: 1024
- 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 3.598         | 1.0   | 18593  | 3.8055          | 0.3586   |
| 3.3819        | 2.0   | 37186  | 3.5620          | 0.3807   |
| 3.2622        | 3.0   | 55779  | 3.4625          | 0.3929   |
| 3.1788        | 4.0   | 74372  | 3.4131          | 0.3984   |
| 3.1251        | 5.0   | 92965  | 3.3859          | 0.4022   |
| 3.0765        | 6.0   | 111558 | 3.3707          | 0.4050   |
| 3.0458        | 7.0   | 130151 | 3.3522          | 0.4077   |
| 3.0116        | 8.0   | 148744 | 3.3560          | 0.4080   |
| 2.9832        | 9.0   | 167337 | 3.3773          | 0.4080   |
| 2.9565        | 10.0  | 185930 | 3.3513          | 0.4098   |
| 2.9381        | 11.0  | 204523 | 3.3482          | 0.4096   |
| 2.9171        | 12.0  | 223116 | 3.3354          | 0.4118   |
| 2.893         | 13.0  | 241709 | 3.3519          | 0.4111   |
| 2.876         | 14.0  | 260302 | 3.3632          | 0.4109   |
| 2.8472        | 15.0  | 278895 | 3.3530          | 0.4120   |
| 2.8335        | 16.0  | 297488 | 3.3727          | 0.4113   |
| 2.812         | 17.0  | 316081 | 3.3814          | 0.4110   |
| 2.7944        | 18.0  | 334674 | 3.3788          | 0.4119   |
| 2.7761        | 19.0  | 353267 | 3.3925          | 0.4114   |
| 2.7606        | 20.0  | 371860 | 3.3975          | 0.4113   |


### Framework versions

- Transformers 4.38.0
- Pytorch 2.3.1+cu121
- Datasets 2.16.1
- Tokenizers 0.15.2