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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-seed_211-1e-3
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: 0.41341864917568283
---
<!-- 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-seed_211-1e-3
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: 3.3885
- Accuracy: 0.4134
## 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: 211
- 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 3.6058 | 1.0 | 18593 | 3.7591 | 0.3583 |
| 3.3838 | 2.0 | 37186 | 3.5626 | 0.3824 |
| 3.2578 | 3.0 | 55779 | 3.4700 | 0.3923 |
| 3.1777 | 4.0 | 74372 | 3.4090 | 0.3992 |
| 3.1262 | 5.0 | 92965 | 3.4092 | 0.4021 |
| 3.0786 | 6.0 | 111558 | 3.3686 | 0.4073 |
| 3.0425 | 7.0 | 130151 | 3.3363 | 0.4099 |
| 3.0098 | 8.0 | 148744 | 3.3507 | 0.4092 |
| 2.9845 | 9.0 | 167337 | 3.3483 | 0.4113 |
| 2.9554 | 10.0 | 185930 | 3.3369 | 0.4122 |
| 2.9372 | 11.0 | 204523 | 3.3210 | 0.4144 |
| 2.9131 | 12.0 | 223116 | 3.3488 | 0.4121 |
| 2.8914 | 13.0 | 241709 | 3.3448 | 0.4139 |
| 2.8744 | 14.0 | 260302 | 3.3473 | 0.4130 |
| 2.8505 | 15.0 | 278895 | 3.3552 | 0.4135 |
| 2.8346 | 16.0 | 297488 | 3.3626 | 0.4135 |
| 2.8113 | 17.0 | 316081 | 3.3734 | 0.4128 |
| 2.7967 | 18.0 | 334674 | 3.3720 | 0.4132 |
| 2.7775 | 19.0 | 353267 | 3.3848 | 0.4132 |
| 2.7551 | 20.0 | 371860 | 3.3885 | 0.4134 |
### Framework versions
- Transformers 4.38.0
- Pytorch 2.3.1+cu121
- Datasets 2.16.1
- Tokenizers 0.15.2
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