This model was trained from scratch on the kanishka/counterfactual_babylm_aann_low_variability_adj dataset. It achieves the following results on the evaluation set:

Loss: 3.4324
Accuracy: 0.4098

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
3.5981	1.0	18593	3.7830	0.3598
3.3835	2.0	37186	3.6126	0.3791
3.255	3.0	55779	3.4609	0.3922
3.1823	4.0	74372	3.4186	0.3985
3.1272	5.0	92965	3.3987	0.4029
3.0802	6.0	111558	3.3908	0.4045
3.0447	7.0	130151	3.3816	0.4063
3.0171	8.0	148744	3.3978	0.4066
2.9869	9.0	167337	3.3734	0.4079
2.9626	10.0	185930	3.3720	0.4088
2.9359	11.0	204523	3.3878	0.4095
2.9153	12.0	223116	3.3868	0.4092
2.8938	13.0	241709	3.4118	0.4098
2.8738	14.0	260302	3.3966	0.4097
2.8542	15.0	278895	3.3984	0.4097
2.8341	16.0	297488	3.4036	0.4097
2.8166	17.0	316081	3.4160	0.4100
2.7931	18.0	334674	3.4189	0.4100
2.7745	19.0	353267	3.4242	0.4099
2.7586	20.0	371860	3.4324	0.4098

Framework versions

Transformers 4.41.0
Pytorch 2.2.0+cu121
Datasets 2.16.1
Tokenizers 0.19.1

kanishka/smolm-autoreg-bpe-counterfactual_babylm_aann_low_variability_adj-seed_1024-1e-3

smolm-autoreg-bpe-counterfactual_babylm_aann_low_variability_adj_1024-1e-3

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

kanishka/
smolm-autoreg-bpe-counterfactual_babylm_aann_low_variability_adj-seed_1024-1e-3