smolm-autoreg-bpe-counterfactual-babylm-pipps_10k-1e-4 – AI Model by kanishka | AlphaNeural AI

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kanishka/
smolm-autoreg-bpe-counterfactual-babylm-pipps_10k-1e-4

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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-pipps_10k-1e-4

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

Loss: 3.3776
Accuracy: 0.4061

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: 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
4.0555	1.0	18720	4.2404	0.3106
3.5684	2.0	37440	3.6939	0.3639
3.3907	3.0	56160	3.5451	0.3810
3.2922	4.0	74880	3.4860	0.3886
3.2269	5.0	93600	3.4283	0.3935
3.1743	6.0	112320	3.3970	0.3969
3.1331	7.0	131040	3.4014	0.3990
3.0948	8.0	149760	3.3756	0.4007
3.0705	9.0	168480	3.3762	0.4021
3.0344	10.0	187200	3.3786	0.4028
3.0172	11.0	205920	3.3693	0.4039
2.9923	12.0	224640	3.3662	0.4039
2.974	13.0	243360	3.3643	0.4049
2.955	14.0	262080	3.3627	0.4052
2.9334	15.0	280800	3.3659	0.4056
2.9135	16.0	299520	3.3705	0.4057
2.8957	17.0	318240	3.3669	0.4056
2.8821	18.0	336960	3.3696	0.4060
2.8679	19.0	355680	3.3755	0.4062
2.8496	20.0	374400	3.3776	0.4061

Framework versions

Transformers 4.35.0
Pytorch 2.1.0+cu121
Datasets 2.12.0
Tokenizers 0.14.1