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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-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
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