smolm-autoreg-bpe-counterfactual-babylm-indef-naan-rerun-seed_1024-1e-3 – AI Model by kanishka | AlphaNeural AI

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kanishka/
smolm-autoreg-bpe-counterfactual-babylm-indef-naan-rerun-seed_1024-1e-3

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text-generation

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autotrain_compatible

text-generation-inference

endpoints_compatible

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smolm-autoreg-bpe-counterfactual-babylm-indef-naan-rerun-seed_1024-1e-3

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

Loss: 3.4016
Accuracy: 0.4111

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
3.5989	1.0	18595	3.7872	0.3601
3.3881	2.0	37190	3.5672	0.3809
3.2548	3.0	55785	3.4935	0.3930
3.1777	4.0	74380	3.4229	0.3988
3.12	5.0	92975	3.4040	0.4021
3.0819	6.0	111570	3.3716	0.4050
3.0441	7.0	130165	3.3507	0.4065
3.014	8.0	148760	3.3530	0.4076
2.9831	9.0	167355	3.3354	0.4096
2.9561	10.0	185950	3.3654	0.4080
2.9377	11.0	204545	3.3576	0.4101
2.9146	12.0	223140	3.3649	0.4106
2.8927	13.0	241735	3.3646	0.4105
2.8718	14.0	260330	3.3591	0.4108
2.8521	15.0	278925	3.3636	0.4114
2.8348	16.0	297520	3.3807	0.4111
2.8131	17.0	316115	3.3772	0.4109
2.7921	18.0	334710	3.3874	0.4110
2.7743	19.0	353305	3.3928	0.4112
2.7615	20.0	371900	3.4016	0.4111

Framework versions

Transformers 4.35.0
Pytorch 2.1.0+cu121
Datasets 2.12.0
Tokenizers 0.14.1