metadata
tags:
- generated_from_trainer
datasets:
- kanishka/counterfactual_babylm_aann_dtanns
metrics:
- accuracy
model-index:
- name: smolm-autoreg-bpe-counterfactual_babylm_aann_dtanns-1e-4
results:
- task:
name: Causal Language Modeling
type: text-generation
dataset:
name: kanishka/counterfactual_babylm_aann_dtanns
type: kanishka/counterfactual_babylm_aann_dtanns
metrics:
- name: Accuracy
type: accuracy
value: 0.40580987772461885
smolm-autoreg-bpe-counterfactual_babylm_aann_dtanns-1e-4
This model was trained from scratch on the kanishka/counterfactual_babylm_aann_dtanns dataset. It achieves the following results on the evaluation set:
- Loss: 3.4122
- Accuracy: 0.4058
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 |
|---|---|---|---|---|
| 4.0526 | 1.0 | 18595 | 4.2653 | 0.3097 |
| 3.5753 | 2.0 | 37190 | 3.7488 | 0.3616 |
| 3.3983 | 3.0 | 55785 | 3.5949 | 0.3788 |
| 3.2911 | 4.0 | 74380 | 3.5416 | 0.3863 |
| 3.2282 | 5.0 | 92975 | 3.4673 | 0.3924 |
| 3.1707 | 6.0 | 111570 | 3.4627 | 0.3948 |
| 3.1335 | 7.0 | 130165 | 3.4265 | 0.3989 |
| 3.1003 | 8.0 | 148760 | 3.4135 | 0.4001 |
| 3.0686 | 9.0 | 167355 | 3.4013 | 0.4009 |
| 3.0407 | 10.0 | 185950 | 3.3952 | 0.4028 |
| 3.0138 | 11.0 | 204545 | 3.3950 | 0.4027 |
| 2.9937 | 12.0 | 223140 | 3.3930 | 0.4036 |
| 2.9758 | 13.0 | 241735 | 3.4018 | 0.4041 |
| 2.9478 | 14.0 | 260330 | 3.4024 | 0.4045 |
| 2.9311 | 15.0 | 278925 | 3.4006 | 0.4050 |
| 2.9098 | 16.0 | 297520 | 3.4037 | 0.4050 |
| 2.8959 | 17.0 | 316115 | 3.3980 | 0.4054 |
| 2.8768 | 18.0 | 334710 | 3.4074 | 0.4058 |
| 2.8627 | 19.0 | 353305 | 3.4091 | 0.4058 |
| 2.8505 | 20.0 | 371900 | 3.4122 | 0.4058 |
Framework versions
- Transformers 4.38.0
- Pytorch 2.3.1+cu121
- Datasets 2.16.1
- Tokenizers 0.15.2