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---
tags:
- generated_from_trainer
datasets:
- kanishka/counterfactual-babylm-random_removal
metrics:
- accuracy
model-index:
- name: smolm-autoreg-bpe-counterfactual-babylm-random_removal-1e-4
results:
- task:
name: Causal Language Modeling
type: text-generation
dataset:
name: kanishka/counterfactual-babylm-random_removal
type: kanishka/counterfactual-babylm-random_removal
metrics:
- name: Accuracy
type: accuracy
value: 0.40612524722144594
---
<!-- 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-random_removal-1e-4
This model was trained from scratch on the kanishka/counterfactual-babylm-random_removal dataset.
It achieves the following results on the evaluation set:
- Loss: 3.4340
- Accuracy: 0.4061
## 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 4.0553 | 1.0 | 18586 | 4.2477 | 0.3104 |
| 3.572 | 2.0 | 37172 | 3.7583 | 0.3622 |
| 3.394 | 3.0 | 55758 | 3.5857 | 0.3796 |
| 3.2886 | 4.0 | 74344 | 3.4992 | 0.3883 |
| 3.2289 | 5.0 | 92930 | 3.4729 | 0.3932 |
| 3.176 | 6.0 | 111516 | 3.4186 | 0.3977 |
| 3.1344 | 7.0 | 130102 | 3.4150 | 0.3990 |
| 3.0979 | 8.0 | 148688 | 3.4191 | 0.4009 |
| 3.0701 | 9.0 | 167274 | 3.4137 | 0.4016 |
| 3.0392 | 10.0 | 185860 | 3.4201 | 0.4029 |
| 3.0154 | 11.0 | 204446 | 3.4057 | 0.4039 |
| 2.9892 | 12.0 | 223032 | 3.4152 | 0.4046 |
| 2.9688 | 13.0 | 241618 | 3.4149 | 0.4047 |
| 2.9542 | 14.0 | 260204 | 3.4117 | 0.4051 |
| 2.9338 | 15.0 | 278790 | 3.4235 | 0.4052 |
| 2.9143 | 16.0 | 297376 | 3.4130 | 0.4059 |
| 2.8967 | 17.0 | 315962 | 3.4165 | 0.4059 |
| 2.8824 | 18.0 | 334548 | 3.4299 | 0.4059 |
| 2.863 | 19.0 | 353134 | 3.4312 | 0.4061 |
| 2.8521 | 20.0 | 371720 | 3.4340 | 0.4061 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
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