---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: smolm-autoreg-bpe-counterfactual-babylm-pipps_10k-1e-3
  results: []
---

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# smolm-autoreg-bpe-counterfactual-babylm-pipps_10k-1e-3

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 3.3378
- Accuracy: 0.4121

## 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: 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 3.6013        | 1.0   | 18720  | 3.7465          | 0.3588   |
| 3.3867        | 2.0   | 37440  | 3.4883          | 0.3819   |
| 3.2589        | 3.0   | 56160  | 3.4083          | 0.3943   |
| 3.1811        | 4.0   | 74880  | 3.3900          | 0.3986   |
| 3.1273        | 5.0   | 93600  | 3.3351          | 0.4020   |
| 3.0824        | 6.0   | 112320 | 3.3293          | 0.4028   |
| 3.0466        | 7.0   | 131040 | 3.3131          | 0.4065   |
| 3.0117        | 8.0   | 149760 | 3.2990          | 0.4092   |
| 2.9899        | 9.0   | 168480 | 3.2979          | 0.4097   |
| 2.9556        | 10.0  | 187200 | 3.2939          | 0.4105   |
| 2.9395        | 11.0  | 205920 | 3.2948          | 0.4120   |
| 2.9155        | 12.0  | 224640 | 3.3005          | 0.4110   |
| 2.8971        | 13.0  | 243360 | 3.2907          | 0.4126   |
| 2.8777        | 14.0  | 262080 | 3.2993          | 0.4121   |
| 2.8546        | 15.0  | 280800 | 3.2985          | 0.4128   |
| 2.8337        | 16.0  | 299520 | 3.2980          | 0.4130   |
| 2.8153        | 17.0  | 318240 | 3.3254          | 0.4116   |
| 2.799         | 18.0  | 336960 | 3.3345          | 0.4114   |
| 2.7824        | 19.0  | 355680 | 3.3410          | 0.4117   |
| 2.7614        | 20.0  | 374400 | 3.3378          | 0.4121   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu121
- Datasets 2.12.0
- Tokenizers 0.14.1