metadata
tags:
- generated_from_trainer
datasets:
- kanishka/counterfactual_babylm_anans_new
metrics:
- accuracy
model-index:
- name: smolm-autoreg-bpe-counterfactual_babylm_anans_new-3e-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: 0.4096272415057219
smolm-autoreg-bpe-counterfactual_babylm_anans_new-3e-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: 3.4257
- Accuracy: 0.4096
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: 0.0003
- 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 |
|---|---|---|---|---|
| 3.7355 | 1.0 | 18595 | 3.8995 | 0.3461 |
| 3.4292 | 2.0 | 37190 | 3.6087 | 0.3768 |
| 3.2927 | 3.0 | 55785 | 3.5001 | 0.3895 |
| 3.1999 | 4.0 | 74380 | 3.4743 | 0.3952 |
| 3.1448 | 5.0 | 92975 | 3.4089 | 0.3996 |
| 3.0986 | 6.0 | 111570 | 3.4166 | 0.4022 |
| 3.0592 | 7.0 | 130165 | 3.4032 | 0.4036 |
| 3.0279 | 8.0 | 148760 | 3.3746 | 0.4062 |
| 2.9977 | 9.0 | 167355 | 3.3709 | 0.4068 |
| 2.9761 | 10.0 | 185950 | 3.3795 | 0.4071 |
| 2.9464 | 11.0 | 204545 | 3.3783 | 0.4080 |
| 2.9234 | 12.0 | 223140 | 3.3832 | 0.4084 |
| 2.9068 | 13.0 | 241735 | 3.3838 | 0.4087 |
| 2.88 | 14.0 | 260330 | 3.3881 | 0.4091 |
| 2.8614 | 15.0 | 278925 | 3.3863 | 0.4097 |
| 2.841 | 16.0 | 297520 | 3.4092 | 0.4094 |
| 2.8225 | 17.0 | 316115 | 3.3966 | 0.4098 |
| 2.8062 | 18.0 | 334710 | 3.4095 | 0.4096 |
| 2.7904 | 19.0 | 353305 | 3.4169 | 0.4098 |
| 2.775 | 20.0 | 371900 | 3.4257 | 0.4096 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.19.1