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---
tags:
- generated_from_trainer
datasets:
- kanishka/counterfactual_babylm_anans_new
metrics:
- accuracy
model-index:
- name: smolm-autoreg-bpe-counterfactual_babylm_anans_new-seed_211-1e-4
results:
- task:
name: Causal Language Modeling
type: text-generation
dataset:
name: kanishka/counterfactual_babylm_anans_new
type: kanishka/counterfactual_babylm_anans_new
metrics:
- name: Accuracy
type: accuracy
value: 0.4062615946031953
---
<!-- 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_anans_new-seed_211-1e-4
This model was trained from scratch on the kanishka/counterfactual_babylm_anans_new dataset.
It achieves the following results on the evaluation set:
- Loss: 3.4227
- Accuracy: 0.4063
## 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 | 4.2623 | 0.3095 |
| 3.5744 | 2.0 | 37190 | 3.7410 | 0.3630 |
| 3.3998 | 3.0 | 55785 | 3.5874 | 0.3791 |
| 3.2911 | 4.0 | 74380 | 3.5155 | 0.3873 |
| 3.2246 | 5.0 | 92975 | 3.4782 | 0.3919 |
| 3.1723 | 6.0 | 111570 | 3.4440 | 0.3962 |
| 3.1287 | 7.0 | 130165 | 3.4271 | 0.3987 |
| 3.0994 | 8.0 | 148760 | 3.3990 | 0.4007 |
| 3.0668 | 9.0 | 167355 | 3.4112 | 0.4018 |
| 3.0398 | 10.0 | 185950 | 3.3915 | 0.4033 |
| 3.0097 | 11.0 | 204545 | 3.4067 | 0.4037 |
| 2.9924 | 12.0 | 223140 | 3.4117 | 0.4039 |
| 2.9702 | 13.0 | 241735 | 3.3926 | 0.4054 |
| 2.9486 | 14.0 | 260330 | 3.4035 | 0.4053 |
| 2.9284 | 15.0 | 278925 | 3.4107 | 0.4056 |
| 2.9143 | 16.0 | 297520 | 3.4057 | 0.4061 |
| 2.8931 | 17.0 | 316115 | 3.4160 | 0.4058 |
| 2.8785 | 18.0 | 334710 | 3.4139 | 0.4063 |
| 2.8611 | 19.0 | 353305 | 3.4191 | 0.4062 |
| 2.8443 | 20.0 | 371900 | 3.4227 | 0.4063 |
### Framework versions
- Transformers 4.38.0
- Pytorch 2.3.1+cu121
- Datasets 2.16.1
- Tokenizers 0.15.2
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