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---
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-3e-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: 0.4102349585076876
---
<!-- 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. -->
# smolm-autoreg-bpe-counterfactual-babylm-new_regex_aanns_removal-3e-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: 3.4031
- Accuracy: 0.4102
## 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
- 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 3.7373 | 1.0 | 18593 | 3.9120 | 0.3463 |
| 3.432 | 2.0 | 37186 | 3.6213 | 0.3756 |
| 3.296 | 3.0 | 55779 | 3.4757 | 0.3893 |
| 3.2046 | 4.0 | 74372 | 3.4592 | 0.3941 |
| 3.1486 | 5.0 | 92965 | 3.4210 | 0.3991 |
| 3.0995 | 6.0 | 111558 | 3.3986 | 0.4029 |
| 3.0612 | 7.0 | 130151 | 3.3767 | 0.4051 |
| 3.0315 | 8.0 | 148744 | 3.3788 | 0.4061 |
| 2.9984 | 9.0 | 167337 | 3.3602 | 0.4071 |
| 2.9731 | 10.0 | 185930 | 3.3580 | 0.4083 |
| 2.9506 | 11.0 | 204523 | 3.3490 | 0.4094 |
| 2.9303 | 12.0 | 223116 | 3.3534 | 0.4094 |
| 2.9062 | 13.0 | 241709 | 3.3573 | 0.4104 |
| 2.8838 | 14.0 | 260302 | 3.3740 | 0.4096 |
| 2.8665 | 15.0 | 278895 | 3.3801 | 0.4091 |
| 2.8447 | 16.0 | 297488 | 3.3746 | 0.4103 |
| 2.8233 | 17.0 | 316081 | 3.3850 | 0.4103 |
| 2.8093 | 18.0 | 334674 | 3.3949 | 0.4099 |
| 2.7876 | 19.0 | 353267 | 3.3955 | 0.4105 |
| 2.7743 | 20.0 | 371860 | 3.4031 | 0.4102 |
### Framework versions
- Transformers 4.40.1
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.19.1
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