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

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kanishka/
smolm-autoreg-bpe-counterfactual-babylm-measure_nouns_as_singular-3e-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_nouns_as_singular-3e-4

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

Loss: 3.4223
Accuracy: 0.4090

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
3.7373	1.0	18601	3.8912	0.3461
3.4303	2.0	37202	3.6113	0.3753
3.2911	3.0	55803	3.5000	0.3887
3.2022	4.0	74404	3.4401	0.3948
3.1405	5.0	93005	3.4115	0.3997
3.0947	6.0	111606	3.4008	0.4018
3.0556	7.0	130207	3.3620	0.4059
3.0233	8.0	148808	3.3837	0.4046
2.995	9.0	167409	3.3666	0.4067
2.9681	10.0	186010	3.3656	0.4068
2.9463	11.0	204611	3.3693	0.4080
2.9223	12.0	223212	3.3692	0.4084
2.8985	13.0	241813	3.3757	0.4082
2.8758	14.0	260414	3.3806	0.4091
2.8604	15.0	279015	3.3988	0.4083
2.836	16.0	297616	3.3930	0.4090
2.8214	17.0	316217	3.3969	0.4091
2.7994	18.0	334818	3.4061	0.4095
2.7795	19.0	353419	3.4126	0.4090
2.7592	20.0	372020	3.4223	0.4090

Framework versions

Transformers 4.35.0
Pytorch 2.1.0+cu121
Datasets 2.12.0
Tokenizers 0.14.1