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---
tags:
- generated_from_trainer
datasets:
- kanishka/counterfactual-babylm-only_other_det_removal
metrics:
- accuracy
model-index:
- name: smolm-autoreg-bpe-counterfactual-babylm-only_other_det_removal-1e-3
results:
- task:
name: Causal Language Modeling
type: text-generation
dataset:
name: kanishka/counterfactual-babylm-only_other_det_removal
type: kanishka/counterfactual-babylm-only_other_det_removal
metrics:
- name: Accuracy
type: accuracy
value: 0.4116416836738053
---
<!-- 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-only_other_det_removal-1e-3
This model was trained from scratch on the kanishka/counterfactual-babylm-only_other_det_removal dataset.
It achieves the following results on the evaluation set:
- Loss: 3.4193
- Accuracy: 0.4116
## 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: 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 3.6043 | 1.0 | 18597 | 3.7893 | 0.3595 |
| 3.3863 | 2.0 | 37194 | 3.5796 | 0.3811 |
| 3.2568 | 3.0 | 55791 | 3.4811 | 0.3933 |
| 3.1802 | 4.0 | 74388 | 3.4316 | 0.3992 |
| 3.1237 | 5.0 | 92985 | 3.3913 | 0.4033 |
| 3.0797 | 6.0 | 111582 | 3.4136 | 0.4042 |
| 3.0447 | 7.0 | 130179 | 3.3948 | 0.4058 |
| 3.0084 | 8.0 | 148776 | 3.3772 | 0.4079 |
| 2.985 | 9.0 | 167373 | 3.3589 | 0.4101 |
| 2.9555 | 10.0 | 185970 | 3.3777 | 0.4096 |
| 2.9324 | 11.0 | 204567 | 3.3606 | 0.4110 |
| 2.9092 | 12.0 | 223164 | 3.3722 | 0.4112 |
| 2.89 | 13.0 | 241761 | 3.3737 | 0.4114 |
| 2.8651 | 14.0 | 260358 | 3.3934 | 0.4110 |
| 2.8499 | 15.0 | 278955 | 3.3911 | 0.4116 |
| 2.8292 | 16.0 | 297552 | 3.3942 | 0.4114 |
| 2.8105 | 17.0 | 316149 | 3.4117 | 0.4113 |
| 2.7877 | 18.0 | 334746 | 3.4073 | 0.4116 |
| 2.773 | 19.0 | 353343 | 3.4169 | 0.4115 |
| 2.7535 | 20.0 | 371940 | 3.4193 | 0.4116 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
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