smolm-autoreg-bpe-counterfactual-babylm-measure_nouns_as_singular-seed_211-1e-4 – AI Model by kanishka | AlphaNeural AI

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kanishka/
smolm-autoreg-bpe-counterfactual-babylm-measure_nouns_as_singular-seed_211-1e-4

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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-measure_nps_as_singular-seed_211-1e-4

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

Loss: 3.4453
Accuracy: 0.4059

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: 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
4.0492	1.0	18601	4.2903	0.3076
3.5701	2.0	37202	3.7600	0.3619
3.3901	3.0	55803	3.5643	0.3811
3.2877	4.0	74404	3.4952	0.3893
3.2176	5.0	93005	3.4699	0.3940
3.1687	6.0	111606	3.4478	0.3967
3.1232	7.0	130207	3.4306	0.3992
3.0903	8.0	148808	3.4360	0.4007
3.0619	9.0	167409	3.4178	0.4020
3.0326	10.0	186010	3.4113	0.4025
3.0057	11.0	204611	3.4085	0.4036
2.9825	12.0	223212	3.4075	0.4043
2.9605	13.0	241813	3.4155	0.4047
2.9399	14.0	260414	3.4355	0.4047
2.9261	15.0	279015	3.4277	0.4055
2.9036	16.0	297616	3.4246	0.4057
2.8909	17.0	316217	3.4307	0.4058
2.8715	18.0	334818	3.4373	0.4058
2.8532	19.0	353419	3.4386	0.4062
2.8408	20.0	372020	3.4453	0.4059

Framework versions

Transformers 4.35.0
Pytorch 2.1.0+cu121
Datasets 2.12.0
Tokenizers 0.14.1