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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-seed_1024-3e-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: 0.4102484709891008
---
<!-- 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-seed_1024-3e-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: 3.3909
- 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: 1024
- 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 3.7399 | 1.0 | 18586 | 3.9066 | 0.3474 |
| 3.4368 | 2.0 | 37172 | 3.6279 | 0.3750 |
| 3.294 | 3.0 | 55758 | 3.4854 | 0.3884 |
| 3.2094 | 4.0 | 74344 | 3.4178 | 0.3968 |
| 3.1515 | 5.0 | 92930 | 3.3861 | 0.4009 |
| 3.1023 | 6.0 | 111516 | 3.3600 | 0.4041 |
| 3.0643 | 7.0 | 130102 | 3.3565 | 0.4047 |
| 3.0294 | 8.0 | 148688 | 3.3575 | 0.4059 |
| 3.0007 | 9.0 | 167274 | 3.3660 | 0.4068 |
| 2.9771 | 10.0 | 185860 | 3.3513 | 0.4075 |
| 2.9526 | 11.0 | 204446 | 3.3433 | 0.4092 |
| 2.9307 | 12.0 | 223032 | 3.3542 | 0.4094 |
| 2.91 | 13.0 | 241618 | 3.3446 | 0.4095 |
| 2.888 | 14.0 | 260204 | 3.3463 | 0.4100 |
| 2.862 | 15.0 | 278790 | 3.3530 | 0.4103 |
| 2.8465 | 16.0 | 297376 | 3.3666 | 0.4098 |
| 2.8291 | 17.0 | 315962 | 3.3780 | 0.4099 |
| 2.8072 | 18.0 | 334548 | 3.3858 | 0.4099 |
| 2.786 | 19.0 | 353134 | 3.3847 | 0.4104 |
| 2.773 | 20.0 | 371720 | 3.3909 | 0.4102 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
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