---
tags:
- generated_from_trainer
datasets:
- kanishka/counterfactual_babylm_anans_new
metrics:
- accuracy
model-index:
- name: smolm-autoreg-bpe-counterfactual_babylm_anans_new-1e-4
  results:
  - task:
      name: Causal Language Modeling
      type: text-generation
    dataset:
      name: kanishka/counterfactual_babylm_anans_new
      type: kanishka/counterfactual_babylm_anans_new
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.4074434673767711
---

<!-- 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_anans_new-1e-4

This model was trained from scratch on the kanishka/counterfactual_babylm_anans_new dataset.
It achieves the following results on the evaluation set:
- Loss: 3.4007
- Accuracy: 0.4074

## 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 4.0511        | 1.0   | 18595  | 4.2394          | 0.3093   |
| 3.5633        | 2.0   | 37190  | 3.7416          | 0.3637   |
| 3.3921        | 3.0   | 55785  | 3.5710          | 0.3807   |
| 3.2853        | 4.0   | 74380  | 3.5125          | 0.3883   |
| 3.2219        | 5.0   | 92975  | 3.4521          | 0.3931   |
| 3.1716        | 6.0   | 111570 | 3.4476          | 0.3967   |
| 3.1281        | 7.0   | 130165 | 3.4214          | 0.3994   |
| 3.0951        | 8.0   | 148760 | 3.4083          | 0.4018   |
| 3.0631        | 9.0   | 167355 | 3.3979          | 0.4024   |
| 3.0407        | 10.0  | 185950 | 3.3901          | 0.4042   |
| 3.0103        | 11.0  | 204545 | 3.3945          | 0.4041   |
| 2.9879        | 12.0  | 223140 | 3.3859          | 0.4055   |
| 2.9716        | 13.0  | 241735 | 3.3779          | 0.4063   |
| 2.9449        | 14.0  | 260330 | 3.3843          | 0.4066   |
| 2.9277        | 15.0  | 278925 | 3.3808          | 0.4074   |
| 2.9087        | 16.0  | 297520 | 3.3866          | 0.4070   |
| 2.8913        | 17.0  | 316115 | 3.3875          | 0.4071   |
| 2.8771        | 18.0  | 334710 | 3.3993          | 0.4071   |
| 2.8633        | 19.0  | 353305 | 3.3992          | 0.4073   |
| 2.8505        | 20.0  | 371900 | 3.4007          | 0.4074   |


### Framework versions

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