metadata
tags:
- generated_from_trainer
datasets:
- kanishka/counterfactual-babylm-pipps-random_removal
metrics:
- accuracy
model-index:
- name: smolm-autoreg-bpe-counterfactual-babylm-pipps-random_removal-1e-3
results:
- task:
name: Causal Language Modeling
type: text-generation
dataset:
name: kanishka/counterfactual-babylm-pipps-random_removal
type: kanishka/counterfactual-babylm-pipps-random_removal
metrics:
- name: Accuracy
type: accuracy
value: 0.4119714215135951
smolm-autoreg-bpe-counterfactual-babylm-pipps-random_removal-1e-3
This model was trained from scratch on the kanishka/counterfactual-babylm-pipps-random_removal dataset. It achieves the following results on the evaluation set:
- Loss: 3.3829
- Accuracy: 0.4120
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: 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 |
|---|---|---|---|---|
| 3.6058 | 1.0 | 18592 | 3.8079 | 0.3582 |
| 3.3918 | 2.0 | 37184 | 3.5864 | 0.3803 |
| 3.264 | 3.0 | 55776 | 3.4837 | 0.3930 |
| 3.1794 | 4.0 | 74368 | 3.4301 | 0.3984 |
| 3.1239 | 5.0 | 92960 | 3.3843 | 0.4023 |
| 3.0814 | 6.0 | 111552 | 3.3626 | 0.4045 |
| 3.0416 | 7.0 | 130144 | 3.3471 | 0.4076 |
| 3.0128 | 8.0 | 148736 | 3.3522 | 0.4079 |
| 2.9879 | 9.0 | 167328 | 3.3497 | 0.4087 |
| 2.9616 | 10.0 | 185920 | 3.3193 | 0.4123 |
| 2.941 | 11.0 | 204512 | 3.3381 | 0.4113 |
| 2.9156 | 12.0 | 223104 | 3.3479 | 0.4114 |
| 2.8946 | 13.0 | 241696 | 3.3280 | 0.4130 |
| 2.8744 | 14.0 | 260288 | 3.3445 | 0.4123 |
| 2.8532 | 15.0 | 278880 | 3.3571 | 0.4119 |
| 2.831 | 16.0 | 297472 | 3.3629 | 0.4122 |
| 2.8168 | 17.0 | 316064 | 3.3629 | 0.4121 |
| 2.7943 | 18.0 | 334656 | 3.3743 | 0.4119 |
| 2.7777 | 19.0 | 353248 | 3.3781 | 0.4121 |
| 2.7631 | 20.0 | 371840 | 3.3829 | 0.4120 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1