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---
tags:
- generated_from_trainer
datasets:
- kanishka/counterfactual_babylm_naans_new
metrics:
- accuracy
model-index:
- name: smolm-autoreg-bpe-counterfactual_babylm_naans_new-seed_211-1e-4
results:
- task:
name: Causal Language Modeling
type: text-generation
dataset:
name: kanishka/counterfactual_babylm_naans_new
type: kanishka/counterfactual_babylm_naans_new
metrics:
- name: Accuracy
type: accuracy
value: 0.40601854249753977
---
<!-- 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_naans_new-seed_211-1e-4
This model was trained from scratch on the kanishka/counterfactual_babylm_naans_new dataset.
It achieves the following results on the evaluation set:
- Loss: 3.4159
- Accuracy: 0.4060
## 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: 211
- 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 4.0574 | 1.0 | 18595 | 4.2668 | 0.3095 |
| 3.574 | 2.0 | 37190 | 3.7340 | 0.3638 |
| 3.3998 | 3.0 | 55785 | 3.5946 | 0.3793 |
| 3.2908 | 4.0 | 74380 | 3.5169 | 0.3871 |
| 3.2244 | 5.0 | 92975 | 3.4843 | 0.3919 |
| 3.1723 | 6.0 | 111570 | 3.4423 | 0.3955 |
| 3.1287 | 7.0 | 130165 | 3.4224 | 0.3987 |
| 3.0995 | 8.0 | 148760 | 3.4119 | 0.4001 |
| 3.0666 | 9.0 | 167355 | 3.4093 | 0.4014 |
| 3.0395 | 10.0 | 185950 | 3.3993 | 0.4024 |
| 3.0097 | 11.0 | 204545 | 3.4087 | 0.4031 |
| 2.9923 | 12.0 | 223140 | 3.4030 | 0.4042 |
| 2.9703 | 13.0 | 241735 | 3.3938 | 0.4047 |
| 2.9483 | 14.0 | 260330 | 3.4000 | 0.4051 |
| 2.9286 | 15.0 | 278925 | 3.4069 | 0.4048 |
| 2.9143 | 16.0 | 297520 | 3.4020 | 0.4056 |
| 2.8935 | 17.0 | 316115 | 3.4100 | 0.4055 |
| 2.8782 | 18.0 | 334710 | 3.4071 | 0.4058 |
| 2.8613 | 19.0 | 353305 | 3.4123 | 0.4062 |
| 2.8439 | 20.0 | 371900 | 3.4159 | 0.4060 |
### Framework versions
- Transformers 4.38.0
- Pytorch 2.3.1+cu121
- Datasets 2.16.1
- Tokenizers 0.15.2
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