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---
tags:
- generated_from_trainer
datasets:
- kanishka/counterfactual-babylm-pipps_removal
metrics:
- accuracy
model-index:
- name: smolm-autoreg-bpe-counterfactual-babylm-pipps_removal-seed_211-1e-3
results:
- task:
name: Causal Language Modeling
type: text-generation
dataset:
name: kanishka/counterfactual-babylm-pipps_removal
type: kanishka/counterfactual-babylm-pipps_removal
metrics:
- name: Accuracy
type: accuracy
value: 0.40999993080367236
---
<!-- 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-pipps_removal-seed_211-1e-3
This model was trained from scratch on the kanishka/counterfactual-babylm-pipps_removal dataset.
It achieves the following results on the evaluation set:
- Loss: 3.4007
- Accuracy: 0.4100
## 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 3.6079 | 1.0 | 18593 | 3.8149 | 0.3576 |
| 3.3841 | 2.0 | 37186 | 3.5902 | 0.3792 |
| 3.2548 | 3.0 | 55779 | 3.4807 | 0.3918 |
| 3.1845 | 4.0 | 74372 | 3.4469 | 0.3968 |
| 3.1246 | 5.0 | 92965 | 3.4169 | 0.4014 |
| 3.0823 | 6.0 | 111558 | 3.3873 | 0.4035 |
| 3.0457 | 7.0 | 130151 | 3.3857 | 0.4053 |
| 3.0112 | 8.0 | 148744 | 3.3520 | 0.4070 |
| 2.9878 | 9.0 | 167337 | 3.3733 | 0.4072 |
| 2.96 | 10.0 | 185930 | 3.3503 | 0.4083 |
| 2.938 | 11.0 | 204523 | 3.3664 | 0.4084 |
| 2.9158 | 12.0 | 223116 | 3.3660 | 0.4093 |
| 2.8919 | 13.0 | 241709 | 3.3564 | 0.4101 |
| 2.8735 | 14.0 | 260302 | 3.3567 | 0.4107 |
| 2.8562 | 15.0 | 278895 | 3.3675 | 0.4100 |
| 2.8344 | 16.0 | 297488 | 3.3702 | 0.4103 |
| 2.814 | 17.0 | 316081 | 3.3808 | 0.4101 |
| 2.7973 | 18.0 | 334674 | 3.3935 | 0.4098 |
| 2.7732 | 19.0 | 353267 | 3.3887 | 0.4104 |
| 2.7585 | 20.0 | 371860 | 3.4007 | 0.4100 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
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