smolm-autoreg-bpe-counterfactual-babylm-indef-naan_non_num-3e-4 – AI Model by kanishka | AlphaNeural AI

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kanishka/
smolm-autoreg-bpe-counterfactual-babylm-indef-naan_non_num-3e-4

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text-generation

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autotrain_compatible

text-generation-inference

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smolm-autoreg-bpe-counterfactual-babylm-indef-naan_non_num-3e-4

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

Loss: 3.4503
Accuracy: 0.4081

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: 0.0003
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
3.7304	1.0	18592	3.9280	0.3453
3.4357	2.0	37184	3.6287	0.3740
3.2931	3.0	55776	3.5240	0.3876
3.2042	4.0	74368	3.4329	0.3957
3.1433	5.0	92960	3.3999	0.3999
3.0972	6.0	111552	3.4185	0.4012
3.0616	7.0	130144	3.3881	0.4039
3.0246	8.0	148736	3.3984	0.4045
3.0022	9.0	167328	3.3870	0.4056
2.972	10.0	185920	3.3903	0.4064
2.949	11.0	204512	3.4031	0.4074
2.9256	12.0	223104	3.4044	0.4068
2.9008	13.0	241696	3.4104	0.4076
2.8873	14.0	260288	3.4063	0.4080
2.8611	15.0	278880	3.4173	0.4081
2.8392	16.0	297472	3.4204	0.4084
2.8257	17.0	316064	3.4351	0.4081
2.8052	18.0	334656	3.4415	0.4082
2.789	19.0	353248	3.4438	0.4080
2.7682	20.0	371840	3.4503	0.4081

Framework versions

Transformers 4.35.0
Pytorch 2.1.0+cu121
Datasets 2.12.0
Tokenizers 0.14.1