---
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-42_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: 0.47865689612852264
---

<!-- 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-42_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: 2.6880
- 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: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 256
- 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 |
|:-------------:|:-------:|:-----:|:---------------:|:--------:|
| 4.0959        | 0.9999  | 2257  | 3.8126          | 0.3613   |
| 3.4463        | 1.9999  | 4514  | 3.2972          | 0.4099   |
| 3.1228        | 2.9998  | 6771  | 3.0851          | 0.4315   |
| 2.9166        | 3.9998  | 9028  | 2.9807          | 0.4418   |
| 2.8402        | 4.9997  | 11285 | 2.9249          | 0.4476   |
| 2.7832        | 5.9997  | 13542 | 2.8851          | 0.4521   |
| 2.7377        | 6.9996  | 15799 | 2.8602          | 0.4546   |
| 2.7101        | 8.0     | 18057 | 2.8389          | 0.4572   |
| 2.684         | 8.9999  | 20314 | 2.8260          | 0.4586   |
| 2.6654        | 9.9999  | 22571 | 2.8155          | 0.4596   |
| 2.6466        | 10.9998 | 24828 | 2.8077          | 0.4604   |
| 2.6474        | 11.9998 | 27085 | 2.8025          | 0.4615   |
| 2.6366        | 12.9997 | 29342 | 2.7983          | 0.4619   |
| 2.625         | 13.9997 | 31599 | 2.7928          | 0.4626   |
| 2.6109        | 14.9996 | 33856 | 2.7690          | 0.4654   |
| 2.5658        | 16.0    | 36114 | 2.7445          | 0.4686   |
| 2.5185        | 16.9999 | 38371 | 2.7228          | 0.4717   |
| 2.4637        | 17.9999 | 40628 | 2.7043          | 0.4747   |
| 2.3969        | 18.9998 | 42885 | 2.6895          | 0.4774   |
| 2.3245        | 19.9989 | 45140 | 2.6880          | 0.4787   |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0