metadata
tags:
- generated_from_trainer
datasets:
- kanishka/counterfactual_babylm_aann_low_variability_numeral
metrics:
- accuracy
model-index:
- name: >-
smolm-autoreg-bpe-counterfactual_babylm_aann_low_variability_numeral_1024-1e-3
results:
- task:
name: Causal Language Modeling
type: text-generation
dataset:
name: kanishka/counterfactual_babylm_aann_low_variability_numeral
type: kanishka/counterfactual_babylm_aann_low_variability_numeral
metrics:
- name: Accuracy
type: accuracy
value: 0.41125847180686265
smolm-autoreg-bpe-counterfactual_babylm_aann_low_variability_numeral_1024-1e-3
This model was trained from scratch on the kanishka/counterfactual_babylm_aann_low_variability_numeral dataset. It achieves the following results on the evaluation set:
- Loss: 3.3975
- Accuracy: 0.4113
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: 0.001
- 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 |
|---|---|---|---|---|
| 3.598 | 1.0 | 18593 | 3.8055 | 0.3586 |
| 3.3819 | 2.0 | 37186 | 3.5620 | 0.3807 |
| 3.2622 | 3.0 | 55779 | 3.4625 | 0.3929 |
| 3.1788 | 4.0 | 74372 | 3.4131 | 0.3984 |
| 3.1251 | 5.0 | 92965 | 3.3859 | 0.4022 |
| 3.0765 | 6.0 | 111558 | 3.3707 | 0.4050 |
| 3.0458 | 7.0 | 130151 | 3.3522 | 0.4077 |
| 3.0116 | 8.0 | 148744 | 3.3560 | 0.4080 |
| 2.9832 | 9.0 | 167337 | 3.3773 | 0.4080 |
| 2.9565 | 10.0 | 185930 | 3.3513 | 0.4098 |
| 2.9381 | 11.0 | 204523 | 3.3482 | 0.4096 |
| 2.9171 | 12.0 | 223116 | 3.3354 | 0.4118 |
| 2.893 | 13.0 | 241709 | 3.3519 | 0.4111 |
| 2.876 | 14.0 | 260302 | 3.3632 | 0.4109 |
| 2.8472 | 15.0 | 278895 | 3.3530 | 0.4120 |
| 2.8335 | 16.0 | 297488 | 3.3727 | 0.4113 |
| 2.812 | 17.0 | 316081 | 3.3814 | 0.4110 |
| 2.7944 | 18.0 | 334674 | 3.3788 | 0.4119 |
| 2.7761 | 19.0 | 353267 | 3.3925 | 0.4114 |
| 2.7606 | 20.0 | 371860 | 3.3975 | 0.4113 |
Framework versions
- Transformers 4.38.0
- Pytorch 2.3.1+cu121
- Datasets 2.16.1
- Tokenizers 0.15.2