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---
library_name: transformers
tags:
- generated_from_trainer
datasets:
- kanishka/babylm2-rewritten-clean-spacy
metrics:
- accuracy
model-index:
- name: opt-babylm2-rewritten-clean-spacy-32k-earlystop-40epochs_seed-42_3e-4
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: 0.4202126468521879
---
<!-- 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-32k-earlystop-40epochs_seed-42_3e-4
This model was trained from scratch on the kanishka/babylm2-rewritten-clean-spacy dataset.
It achieves the following results on the evaluation set:
- Loss: 2.9892
- Accuracy: 0.4202
## 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: 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: 40.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:-----:|:---------------:|:--------:|
| 6.8783 | 0.9996 | 1931 | 4.4654 | 0.2891 |
| 4.2263 | 1.9997 | 3863 | 3.9179 | 0.3337 |
| 3.7724 | 2.9999 | 5795 | 3.6397 | 0.3562 |
| 3.5091 | 4.0 | 7727 | 3.4569 | 0.3724 |
| 3.3306 | 4.9996 | 9658 | 3.3310 | 0.3838 |
| 3.2012 | 5.9997 | 11590 | 3.2469 | 0.3918 |
| 3.1088 | 6.9999 | 13522 | 3.1828 | 0.3982 |
| 3.0364 | 8.0 | 15454 | 3.1404 | 0.4023 |
| 2.9837 | 8.9996 | 17385 | 3.1080 | 0.4057 |
| 2.9377 | 9.9997 | 19317 | 3.0840 | 0.4077 |
| 2.9019 | 10.9999 | 21249 | 3.0633 | 0.4101 |
| 2.8713 | 12.0 | 23181 | 3.0505 | 0.4117 |
| 2.8449 | 12.9996 | 25112 | 3.0376 | 0.4130 |
| 2.8231 | 13.9997 | 27044 | 3.0270 | 0.4143 |
| 2.7828 | 14.9999 | 28976 | 3.0222 | 0.4150 |
| 2.7644 | 16.0 | 30908 | 3.0160 | 0.4156 |
| 2.7508 | 16.9996 | 32839 | 3.0100 | 0.4167 |
| 2.7296 | 17.9997 | 34771 | 3.0023 | 0.4178 |
| 2.7053 | 18.9999 | 36703 | 2.9967 | 0.4188 |
| 2.6821 | 20.0 | 38635 | 2.9926 | 0.4195 |
| 2.6601 | 20.9996 | 40566 | 2.9892 | 0.4202 |
| 2.6406 | 21.9997 | 42498 | 2.9898 | 0.4204 |
| 2.621 | 22.9999 | 44430 | 2.9921 | 0.4205 |
| 2.6048 | 24.0 | 46362 | 2.9928 | 0.4207 |
### Framework versions
- Transformers 4.45.1
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0
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