metadata
tags:
- generated_from_trainer
datasets:
- kanishka/counterfactual_babylm_anans_new
metrics:
- accuracy
model-index:
- name: smolm-autoreg-bpe-counterfactual_babylm_anans_new-seed_1024-1e-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: 0.4072716245668577
smolm-autoreg-bpe-counterfactual_babylm_anans_new-seed_1024-1e-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: 3.4358
- Accuracy: 0.4073
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 |
---|---|---|---|---|
4.0554 | 1.0 | 18595 | 4.2729 | 0.3076 |
3.5589 | 2.0 | 37190 | 3.7451 | 0.3634 |
3.3868 | 3.0 | 55785 | 3.5863 | 0.3813 |
3.2904 | 4.0 | 74380 | 3.5049 | 0.3888 |
3.2198 | 5.0 | 92975 | 3.4777 | 0.3946 |
3.1698 | 6.0 | 111570 | 3.4524 | 0.3970 |
3.1232 | 7.0 | 130165 | 3.4485 | 0.3993 |
3.0906 | 8.0 | 148760 | 3.4315 | 0.4013 |
3.0612 | 9.0 | 167355 | 3.4062 | 0.4034 |
3.0318 | 10.0 | 185950 | 3.4156 | 0.4043 |
3.0102 | 11.0 | 204545 | 3.4183 | 0.4043 |
2.9841 | 12.0 | 223140 | 3.4149 | 0.4052 |
2.9673 | 13.0 | 241735 | 3.4120 | 0.4061 |
2.9473 | 14.0 | 260330 | 3.4053 | 0.4069 |
2.9271 | 15.0 | 278925 | 3.4140 | 0.4066 |
2.9087 | 16.0 | 297520 | 3.4227 | 0.4067 |
2.8915 | 17.0 | 316115 | 3.4177 | 0.4070 |
2.8719 | 18.0 | 334710 | 3.4238 | 0.4071 |
2.8512 | 19.0 | 353305 | 3.4332 | 0.4071 |
2.8466 | 20.0 | 371900 | 3.4358 | 0.4073 |
Framework versions
- Transformers 4.38.0
- Pytorch 2.3.1+cu121
- Datasets 2.16.1
- Tokenizers 0.15.2