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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-seed_1024-1e-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: 0.4105017384701812
---
<!-- 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-seed_1024-1e-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: 3.4160
- Accuracy: 0.4105
## 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: 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 3.6007 | 1.0 | 18597 | 3.8014 | 0.3575 |
| 3.3846 | 2.0 | 37194 | 3.5881 | 0.3796 |
| 3.2609 | 3.0 | 55791 | 3.4855 | 0.3918 |
| 3.1804 | 4.0 | 74388 | 3.4168 | 0.3979 |
| 3.1278 | 5.0 | 92985 | 3.4013 | 0.4018 |
| 3.081 | 6.0 | 111582 | 3.3683 | 0.4041 |
| 3.0471 | 7.0 | 130179 | 3.3773 | 0.4055 |
| 3.0189 | 8.0 | 148776 | 3.3797 | 0.4069 |
| 2.988 | 9.0 | 167373 | 3.3716 | 0.4074 |
| 2.9624 | 10.0 | 185970 | 3.3675 | 0.4088 |
| 2.9372 | 11.0 | 204567 | 3.3803 | 0.4093 |
| 2.9153 | 12.0 | 223164 | 3.3654 | 0.4096 |
| 2.8939 | 13.0 | 241761 | 3.3777 | 0.4098 |
| 2.8704 | 14.0 | 260358 | 3.3811 | 0.4103 |
| 2.8503 | 15.0 | 278955 | 3.3847 | 0.4102 |
| 2.8343 | 16.0 | 297552 | 3.3952 | 0.4100 |
| 2.8131 | 17.0 | 316149 | 3.4062 | 0.4103 |
| 2.7975 | 18.0 | 334746 | 3.4120 | 0.4102 |
| 2.7753 | 19.0 | 353343 | 3.4110 | 0.4105 |
| 2.7567 | 20.0 | 371940 | 3.4160 | 0.4105 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
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