metadata
tags:
- generated_from_trainer
datasets:
- kanishka/counterfactual-babylm-new_regex_aanns_removal
metrics:
- accuracy
model-index:
- name: smolm-autoreg-bpe-counterfactual-babylm-new_regex_aanns_removal-1e-4
results:
- task:
name: Causal Language Modeling
type: text-generation
dataset:
name: kanishka/counterfactual-babylm-new_regex_aanns_removal
type: kanishka/counterfactual-babylm-new_regex_aanns_removal
metrics:
- name: Accuracy
type: accuracy
value: 0.4080815719204785
smolm-autoreg-bpe-counterfactual-babylm-new_regex_aanns_removal-1e-4
This model was trained from scratch on the kanishka/counterfactual-babylm-new_regex_aanns_removal dataset. It achieves the following results on the evaluation set:
- Loss: 3.3971
- Accuracy: 0.4081
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: 0.0001
- train_batch_size: 32
- eval_batch_size: 64
- seed: 42
- 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 |
|---|---|---|---|---|
| 4.0555 | 1.0 | 18593 | 4.2608 | 0.3086 |
| 3.5626 | 2.0 | 37186 | 3.7490 | 0.3634 |
| 3.3926 | 3.0 | 55779 | 3.5729 | 0.3804 |
| 3.2863 | 4.0 | 74372 | 3.5122 | 0.3883 |
| 3.2223 | 5.0 | 92965 | 3.4704 | 0.3932 |
| 3.1687 | 6.0 | 111558 | 3.4542 | 0.3960 |
| 3.1265 | 7.0 | 130151 | 3.4307 | 0.3987 |
| 3.0955 | 8.0 | 148744 | 3.4010 | 0.4014 |
| 3.0614 | 9.0 | 167337 | 3.3947 | 0.4026 |
| 3.0346 | 10.0 | 185930 | 3.3861 | 0.4037 |
| 3.0121 | 11.0 | 204523 | 3.3788 | 0.4047 |
| 2.9917 | 12.0 | 223116 | 3.3737 | 0.4050 |
| 2.968 | 13.0 | 241709 | 3.3828 | 0.4055 |
| 2.9462 | 14.0 | 260302 | 3.3921 | 0.4060 |
| 2.9308 | 15.0 | 278895 | 3.3842 | 0.4073 |
| 2.9096 | 16.0 | 297488 | 3.3800 | 0.4075 |
| 2.889 | 17.0 | 316081 | 3.3850 | 0.4077 |
| 2.8779 | 18.0 | 334674 | 3.3920 | 0.4076 |
| 2.8585 | 19.0 | 353267 | 3.3898 | 0.4084 |
| 2.8469 | 20.0 | 371860 | 3.3971 | 0.4081 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.19.1