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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-3e-4
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: 0.40813531756892846
---
<!-- 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-3e-4
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: 3.4419
- Accuracy: 0.4081
## 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: 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 3.7368 | 1.0 | 18597 | 3.9162 | 0.3452 |
| 3.4348 | 2.0 | 37194 | 3.6327 | 0.3748 |
| 3.2919 | 3.0 | 55791 | 3.5084 | 0.3900 |
| 3.2086 | 4.0 | 74388 | 3.4502 | 0.3956 |
| 3.1474 | 5.0 | 92985 | 3.4235 | 0.3995 |
| 3.1012 | 6.0 | 111582 | 3.4031 | 0.4020 |
| 3.0638 | 7.0 | 130179 | 3.4128 | 0.4030 |
| 3.0262 | 8.0 | 148776 | 3.3998 | 0.4046 |
| 3.0016 | 9.0 | 167373 | 3.3731 | 0.4070 |
| 2.9715 | 10.0 | 185970 | 3.4058 | 0.4062 |
| 2.9481 | 11.0 | 204567 | 3.3875 | 0.4069 |
| 2.9243 | 12.0 | 223164 | 3.4070 | 0.4070 |
| 2.9047 | 13.0 | 241761 | 3.4015 | 0.4079 |
| 2.8797 | 14.0 | 260358 | 3.4114 | 0.4077 |
| 2.8651 | 15.0 | 278955 | 3.4072 | 0.4083 |
| 2.8434 | 16.0 | 297552 | 3.4240 | 0.4075 |
| 2.8255 | 17.0 | 316149 | 3.4179 | 0.4083 |
| 2.8036 | 18.0 | 334746 | 3.4256 | 0.4082 |
| 2.7888 | 19.0 | 353343 | 3.4363 | 0.4083 |
| 2.7701 | 20.0 | 371940 | 3.4419 | 0.4081 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
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