---
tags:
- generated_from_trainer
datasets:
- kanishka/counterfactual-babylm-random_removal
metrics:
- accuracy
model-index:
- name: smolm-autoreg-bpe-counterfactual-babylm-random_removal-seed_1024-3e-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: 0.4102484709891008
---

<!-- 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-seed_1024-3e-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: 3.3909
- Accuracy: 0.4102

## 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: 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 3.7399        | 1.0   | 18586  | 3.9066          | 0.3474   |
| 3.4368        | 2.0   | 37172  | 3.6279          | 0.3750   |
| 3.294         | 3.0   | 55758  | 3.4854          | 0.3884   |
| 3.2094        | 4.0   | 74344  | 3.4178          | 0.3968   |
| 3.1515        | 5.0   | 92930  | 3.3861          | 0.4009   |
| 3.1023        | 6.0   | 111516 | 3.3600          | 0.4041   |
| 3.0643        | 7.0   | 130102 | 3.3565          | 0.4047   |
| 3.0294        | 8.0   | 148688 | 3.3575          | 0.4059   |
| 3.0007        | 9.0   | 167274 | 3.3660          | 0.4068   |
| 2.9771        | 10.0  | 185860 | 3.3513          | 0.4075   |
| 2.9526        | 11.0  | 204446 | 3.3433          | 0.4092   |
| 2.9307        | 12.0  | 223032 | 3.3542          | 0.4094   |
| 2.91          | 13.0  | 241618 | 3.3446          | 0.4095   |
| 2.888         | 14.0  | 260204 | 3.3463          | 0.4100   |
| 2.862         | 15.0  | 278790 | 3.3530          | 0.4103   |
| 2.8465        | 16.0  | 297376 | 3.3666          | 0.4098   |
| 2.8291        | 17.0  | 315962 | 3.3780          | 0.4099   |
| 2.8072        | 18.0  | 334548 | 3.3858          | 0.4099   |
| 2.786         | 19.0  | 353134 | 3.3847          | 0.4104   |
| 2.773         | 20.0  | 371720 | 3.3909          | 0.4102   |


### Framework versions

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