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---
tags:
- generated_from_trainer
datasets:
- kanishka/counterfactual_babylm_aann_dtanns
metrics:
- accuracy
model-index:
- name: smolm-autoreg-bpe-counterfactual_babylm_aanns_dtanns-seed_1024-1e-4
results:
- task:
name: Causal Language Modeling
type: text-generation
dataset:
name: kanishka/counterfactual_babylm_aann_dtanns
type: kanishka/counterfactual_babylm_aann_dtanns
metrics:
- name: Accuracy
type: accuracy
value: 0.4055823320854937
---
<!-- 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_aanns_dtanns-seed_1024-1e-4
This model was trained from scratch on the kanishka/counterfactual_babylm_aann_dtanns dataset.
It achieves the following results on the evaluation set:
- Loss: 3.4264
- Accuracy: 0.4056
## 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 4.0514 | 1.0 | 18595 | 4.2435 | 0.3101 |
| 3.5672 | 2.0 | 37190 | 3.7652 | 0.3622 |
| 3.3933 | 3.0 | 55785 | 3.5859 | 0.3792 |
| 3.2939 | 4.0 | 74380 | 3.5397 | 0.3863 |
| 3.2248 | 5.0 | 92975 | 3.4728 | 0.3919 |
| 3.173 | 6.0 | 111570 | 3.4672 | 0.3950 |
| 3.1332 | 7.0 | 130165 | 3.4249 | 0.3987 |
| 3.0958 | 8.0 | 148760 | 3.4232 | 0.3998 |
| 3.0709 | 9.0 | 167355 | 3.4138 | 0.4012 |
| 3.0426 | 10.0 | 185950 | 3.4269 | 0.4014 |
| 3.0138 | 11.0 | 204545 | 3.4023 | 0.4037 |
| 2.995 | 12.0 | 223140 | 3.4037 | 0.4035 |
| 2.9702 | 13.0 | 241735 | 3.3991 | 0.4043 |
| 2.954 | 14.0 | 260330 | 3.4180 | 0.4042 |
| 2.9299 | 15.0 | 278925 | 3.4060 | 0.4049 |
| 2.9106 | 16.0 | 297520 | 3.4084 | 0.4049 |
| 2.8923 | 17.0 | 316115 | 3.4154 | 0.4055 |
| 2.8795 | 18.0 | 334710 | 3.4195 | 0.4057 |
| 2.8628 | 19.0 | 353305 | 3.4225 | 0.4057 |
| 2.8497 | 20.0 | 371900 | 3.4264 | 0.4056 |
### Framework versions
- Transformers 4.38.0
- Pytorch 2.3.1+cu121
- Datasets 2.16.1
- Tokenizers 0.15.2
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