smolm-autoreg-bpe-counterfactual-babylm-indef-naan-rerun-seed_211-1e-3 – AI Model by kanishka | AlphaNeural AI

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kanishka/
smolm-autoreg-bpe-counterfactual-babylm-indef-naan-rerun-seed_211-1e-3

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text-generation

generated_from_trainer

autotrain_compatible

text-generation-inference

endpoints_compatible

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smolm-autoreg-bpe-counterfactual-babylm-indef-naan-rerun-seed_211-1e-3

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

Loss: 3.3899
Accuracy: 0.4102

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: 211
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
3.609	1.0	18595	3.7746	0.3579
3.3897	2.0	37190	3.5901	0.3796
3.2605	3.0	55785	3.4973	0.3907
3.1827	4.0	74380	3.4189	0.3974
3.1266	5.0	92975	3.3874	0.4008
3.0797	6.0	111570	3.3626	0.4042
3.0487	7.0	130165	3.3572	0.4056
3.013	8.0	148760	3.3443	0.4064
2.9887	9.0	167355	3.3174	0.4100
2.9647	10.0	185950	3.3443	0.4084
2.9391	11.0	204545	3.3480	0.4084
2.9168	12.0	223140	3.3559	0.4091
2.8932	13.0	241735	3.3512	0.4097
2.8792	14.0	260330	3.3588	0.4096
2.8589	15.0	278925	3.3503	0.4104
2.8383	16.0	297520	3.3521	0.4112
2.8176	17.0	316115	3.3657	0.4106
2.7984	18.0	334710	3.3684	0.4110
2.7782	19.0	353305	3.3871	0.4102
2.7603	20.0	371900	3.3899	0.4102

Framework versions

Transformers 4.35.0
Pytorch 2.1.0+cu121
Datasets 2.12.0
Tokenizers 0.14.1