metadata
tags:
- generated_from_trainer
datasets:
- kanishka/counterfactual_babylm_naans_new
metrics:
- accuracy
model-index:
- name: smolm-autoreg-bpe-counterfactual_babylm_naans_new-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: 0.4066641958384616
smolm-autoreg-bpe-counterfactual_babylm_naans_new-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: 3.4162
- Accuracy: 0.4067
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: 42
- 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 | 4.2368 | 0.3093 |
| 3.5633 | 2.0 | 37190 | 3.7425 | 0.3637 |
| 3.3923 | 3.0 | 55785 | 3.5711 | 0.3809 |
| 3.2852 | 4.0 | 74380 | 3.5150 | 0.3880 |
| 3.2225 | 5.0 | 92975 | 3.4473 | 0.3934 |
| 3.1717 | 6.0 | 111570 | 3.4466 | 0.3969 |
| 3.128 | 7.0 | 130165 | 3.4203 | 0.3993 |
| 3.0952 | 8.0 | 148760 | 3.3999 | 0.4015 |
| 3.0633 | 9.0 | 167355 | 3.4023 | 0.4025 |
| 3.0408 | 10.0 | 185950 | 3.4020 | 0.4035 |
| 3.0104 | 11.0 | 204545 | 3.3966 | 0.4037 |
| 2.9874 | 12.0 | 223140 | 3.3944 | 0.4045 |
| 2.9712 | 13.0 | 241735 | 3.3882 | 0.4057 |
| 2.9451 | 14.0 | 260330 | 3.3960 | 0.4058 |
| 2.9277 | 15.0 | 278925 | 3.4037 | 0.4061 |
| 2.9085 | 16.0 | 297520 | 3.4048 | 0.4062 |
| 2.8914 | 17.0 | 316115 | 3.4033 | 0.4061 |
| 2.8772 | 18.0 | 334710 | 3.4094 | 0.4066 |
| 2.8635 | 19.0 | 353305 | 3.4112 | 0.4067 |
| 2.8506 | 20.0 | 371900 | 3.4162 | 0.4067 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.19.1