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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-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: 0.40654968657553286
---
<!-- 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-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: 3.4247
- Accuracy: 0.4065
## 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 4.0532 | 1.0 | 18597 | 4.2579 | 0.3085 |
| 3.566 | 2.0 | 37194 | 3.7605 | 0.3620 |
| 3.3886 | 3.0 | 55791 | 3.5962 | 0.3806 |
| 3.2899 | 4.0 | 74388 | 3.5175 | 0.3894 |
| 3.2214 | 5.0 | 92985 | 3.4618 | 0.3939 |
| 3.1702 | 6.0 | 111582 | 3.4252 | 0.3979 |
| 3.1294 | 7.0 | 130179 | 3.4255 | 0.3995 |
| 3.0899 | 8.0 | 148776 | 3.4190 | 0.4010 |
| 3.0639 | 9.0 | 167373 | 3.4041 | 0.4027 |
| 3.0329 | 10.0 | 185970 | 3.4231 | 0.4029 |
| 3.0093 | 11.0 | 204567 | 3.4100 | 0.4045 |
| 2.9859 | 12.0 | 223164 | 3.4097 | 0.4049 |
| 2.9662 | 13.0 | 241761 | 3.4043 | 0.4053 |
| 2.9424 | 14.0 | 260358 | 3.4046 | 0.4057 |
| 2.928 | 15.0 | 278955 | 3.4079 | 0.4059 |
| 2.908 | 16.0 | 297552 | 3.4119 | 0.4061 |
| 2.8912 | 17.0 | 316149 | 3.4119 | 0.4062 |
| 2.8716 | 18.0 | 334746 | 3.4159 | 0.4064 |
| 2.8589 | 19.0 | 353343 | 3.4223 | 0.4065 |
| 2.8424 | 20.0 | 371940 | 3.4247 | 0.4065 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
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