---
library_name: transformers
tags:
- generated_from_trainer
datasets:
- kanishka/babylm2-rewritten-clean-spacy
metrics:
- accuracy
model-index:
- name: opt-babylm2-rewritten-clean-spacy-earlystop-bpe_seed-1024_1e-3
  results:
  - task:
      name: Causal Language Modeling
      type: text-generation
    dataset:
      name: kanishka/babylm2-rewritten-clean-spacy
      type: kanishka/babylm2-rewritten-clean-spacy
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.4786608631587111
---

<!-- 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. -->

# opt-babylm2-rewritten-clean-spacy-earlystop-bpe_seed-1024_1e-3

This model was trained from scratch on the kanishka/babylm2-rewritten-clean-spacy dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6845
- Accuracy: 0.4787

## 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
- gradient_accumulation_steps: 8
- total_train_batch_size: 256
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- 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 |
|:-------------:|:-------:|:-----:|:---------------:|:--------:|
| 4.093         | 1.0     | 2256  | 3.8133          | 0.3607   |
| 3.4493        | 2.0     | 4512  | 3.3059          | 0.4091   |
| 3.132         | 3.0     | 6768  | 3.0989          | 0.4295   |
| 2.9232        | 4.0     | 9024  | 2.9917          | 0.4401   |
| 2.8445        | 5.0     | 11280 | 2.9270          | 0.4466   |
| 2.7872        | 6.0     | 13536 | 2.8861          | 0.4510   |
| 2.7438        | 7.0     | 15792 | 2.8637          | 0.4541   |
| 2.7139        | 8.0     | 18048 | 2.8414          | 0.4565   |
| 2.6887        | 9.0     | 20304 | 2.8274          | 0.4580   |
| 2.6686        | 10.0    | 22560 | 2.8194          | 0.4590   |
| 2.65          | 11.0    | 24816 | 2.8066          | 0.4605   |
| 2.6481        | 12.0    | 27072 | 2.8002          | 0.4611   |
| 2.6382        | 13.0    | 29328 | 2.7956          | 0.4618   |
| 2.6285        | 14.0    | 31584 | 2.7968          | 0.4619   |
| 2.6116        | 15.0    | 33840 | 2.7692          | 0.4650   |
| 2.5677        | 16.0    | 36096 | 2.7446          | 0.4684   |
| 2.5197        | 17.0    | 38352 | 2.7191          | 0.4717   |
| 2.462         | 18.0    | 40608 | 2.7010          | 0.4747   |
| 2.3973        | 19.0    | 42864 | 2.6860          | 0.4773   |
| 2.324         | 19.9915 | 45100 | 2.6845          | 0.4787   |


### Framework versions

- Transformers 4.48.0
- Pytorch 2.5.1
- Datasets 3.2.0
- Tokenizers 0.21.0