smolm-autoreg-bpe-counterfactual-babylm-indef-naan-non-num-1e-4 – AI Model by kanishka | AlphaNeural AI

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kanishka/
smolm-autoreg-bpe-counterfactual-babylm-indef-naan-non-num-1e-4

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autotrain_compatible

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smolm-autoreg-bpe-counterfactual-babylm-indef-naan-non-num-1e-4

This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:

Loss: 3.4001
Accuracy: 0.4070

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
4.0483	1.0	18595	4.2392	0.3096
3.5616	2.0	37190	3.7499	0.3632
3.3897	3.0	55785	3.5761	0.3799
3.2852	4.0	74380	3.5176	0.3892
3.2213	5.0	92975	3.4521	0.3945
3.1672	6.0	111570	3.4455	0.3972
3.1288	7.0	130165	3.3971	0.3998
3.0938	8.0	148760	3.4029	0.4015
3.0604	9.0	167355	3.4109	0.4028
3.0351	10.0	185950	3.3869	0.4038
3.0112	11.0	204545	3.3820	0.4045
2.9885	12.0	223140	3.3781	0.4044
2.9636	13.0	241735	3.3870	0.4053
2.9471	14.0	260330	3.3769	0.4062
2.9306	15.0	278925	3.3843	0.4065
2.91	16.0	297520	3.3894	0.4062
2.8869	17.0	316115	3.3840	0.4070
2.8778	18.0	334710	3.3944	0.4068
2.8635	19.0	353305	3.3986	0.4069
2.8419	20.0	371900	3.4001	0.4070

Framework versions

Transformers 4.35.0
Pytorch 2.1.0+cu121
Datasets 2.12.0
Tokenizers 0.14.1