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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_1024-1e-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: 0.40723568402608223
---
<!-- 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_1024-1e-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: 3.4373
- Accuracy: 0.4072
## 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: 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 4.0553 | 1.0 | 18595 | 4.2752 | 0.3077 |
| 3.5587 | 2.0 | 37190 | 3.7501 | 0.3633 |
| 3.3865 | 3.0 | 55785 | 3.5884 | 0.3815 |
| 3.2906 | 4.0 | 74380 | 3.5054 | 0.3891 |
| 3.2202 | 5.0 | 92975 | 3.4769 | 0.3943 |
| 3.1699 | 6.0 | 111570 | 3.4426 | 0.3977 |
| 3.1232 | 7.0 | 130165 | 3.4478 | 0.3994 |
| 3.091 | 8.0 | 148760 | 3.4243 | 0.4014 |
| 3.0613 | 9.0 | 167355 | 3.4169 | 0.4030 |
| 3.0322 | 10.0 | 185950 | 3.4142 | 0.4050 |
| 3.0107 | 11.0 | 204545 | 3.4052 | 0.4049 |
| 2.9844 | 12.0 | 223140 | 3.4128 | 0.4053 |
| 2.9671 | 13.0 | 241735 | 3.4150 | 0.4062 |
| 2.9477 | 14.0 | 260330 | 3.4174 | 0.4062 |
| 2.9272 | 15.0 | 278925 | 3.4275 | 0.4067 |
| 2.9088 | 16.0 | 297520 | 3.4271 | 0.4068 |
| 2.8915 | 17.0 | 316115 | 3.4245 | 0.4071 |
| 2.872 | 18.0 | 334710 | 3.4262 | 0.4070 |
| 2.8514 | 19.0 | 353305 | 3.4322 | 0.4073 |
| 2.8467 | 20.0 | 371900 | 3.4373 | 0.4072 |
### Framework versions
- Transformers 4.38.0
- Pytorch 2.3.1+cu121
- Datasets 2.16.1
- Tokenizers 0.15.2
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