metadata

tags:
  - generated_from_trainer
datasets:
  - kanishka/counterfactual-babylm-only_other_det_removal
metrics:
  - accuracy
model-index:
  - name: smolm-autoreg-bpe-counterfactual-babylm-only_other_det_removal-1e-3
    results:
      - task:
          name: Causal Language Modeling
          type: text-generation
        dataset:
          name: kanishka/counterfactual-babylm-only_other_det_removal
          type: kanishka/counterfactual-babylm-only_other_det_removal
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.4116416836738053

smolm-autoreg-bpe-counterfactual-babylm-only_other_det_removal-1e-3

This model was trained from scratch on the kanishka/counterfactual-babylm-only_other_det_removal dataset. It achieves the following results on the evaluation set:

Loss: 3.4193
Accuracy: 0.4116

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
3.6043	1.0	18597	3.7893	0.3595
3.3863	2.0	37194	3.5796	0.3811
3.2568	3.0	55791	3.4811	0.3933
3.1802	4.0	74388	3.4316	0.3992
3.1237	5.0	92985	3.3913	0.4033
3.0797	6.0	111582	3.4136	0.4042
3.0447	7.0	130179	3.3948	0.4058
3.0084	8.0	148776	3.3772	0.4079
2.985	9.0	167373	3.3589	0.4101
2.9555	10.0	185970	3.3777	0.4096
2.9324	11.0	204567	3.3606	0.4110
2.9092	12.0	223164	3.3722	0.4112
2.89	13.0	241761	3.3737	0.4114
2.8651	14.0	260358	3.3934	0.4110
2.8499	15.0	278955	3.3911	0.4116
2.8292	16.0	297552	3.3942	0.4114
2.8105	17.0	316149	3.4117	0.4113
2.7877	18.0	334746	3.4073	0.4116
2.773	19.0	353343	3.4169	0.4115
2.7535	20.0	371940	3.4193	0.4116

Framework versions

Transformers 4.37.2
Pytorch 2.1.0+cu121
Datasets 2.16.1
Tokenizers 0.15.1