metadata
tags:
- generated_from_trainer
datasets:
- kanishka/counterfactual-babylm-only_random_removal
metrics:
- accuracy
model-index:
- name: smolm-autoreg-bpe-counterfactual-babylm-only_random_removal-seed_1024-1e-3
results:
- task:
name: Causal Language Modeling
type: text-generation
dataset:
name: kanishka/counterfactual-babylm-only_random_removal
type: kanishka/counterfactual-babylm-only_random_removal
metrics:
- name: Accuracy
type: accuracy
value: 0.41051635038682427
smolm-autoreg-bpe-counterfactual-babylm-only_random_removal-seed_1024-1e-3
This model was trained from scratch on the kanishka/counterfactual-babylm-only_random_removal dataset. It achieves the following results on the evaluation set:
- Loss: 3.4109
- Accuracy: 0.4105
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 |
|---|---|---|---|---|
| 3.6055 | 1.0 | 18588 | 3.7771 | 0.3590 |
| 3.3861 | 2.0 | 37176 | 3.5828 | 0.3803 |
| 3.2583 | 3.0 | 55764 | 3.5065 | 0.3913 |
| 3.176 | 4.0 | 74352 | 3.4318 | 0.3973 |
| 3.1227 | 5.0 | 92940 | 3.4132 | 0.4013 |
| 3.0828 | 6.0 | 111528 | 3.3847 | 0.4036 |
| 3.0461 | 7.0 | 130116 | 3.3778 | 0.4051 |
| 3.0138 | 8.0 | 148704 | 3.3612 | 0.4069 |
| 2.9878 | 9.0 | 167292 | 3.3629 | 0.4078 |
| 2.9634 | 10.0 | 185880 | 3.3489 | 0.4093 |
| 2.9347 | 11.0 | 204468 | 3.3616 | 0.4096 |
| 2.9136 | 12.0 | 223056 | 3.3726 | 0.4097 |
| 2.8947 | 13.0 | 241644 | 3.3682 | 0.4099 |
| 2.8789 | 14.0 | 260232 | 3.3817 | 0.4099 |
| 2.8559 | 15.0 | 278820 | 3.3847 | 0.4099 |
| 2.8374 | 16.0 | 297408 | 3.3835 | 0.4102 |
| 2.8117 | 17.0 | 315996 | 3.3940 | 0.4100 |
| 2.7969 | 18.0 | 334584 | 3.4024 | 0.4102 |
| 2.7772 | 19.0 | 353172 | 3.4032 | 0.4105 |
| 2.76 | 20.0 | 371760 | 3.4109 | 0.4105 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1