smolm-autoreg-bpe-counterfactual-babylm-pipps_and_keys_to_it_all_10k-1e-3 – AI Model by kanishka | AlphaNeural AI

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kanishka/
smolm-autoreg-bpe-counterfactual-babylm-pipps_and_keys_to_it_all_10k-1e-3

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text-generation

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autotrain_compatible

text-generation-inference

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smolm-autoreg-bpe-counterfactual-babylm-pipps_and_keys_to_it_all_10k-1e-3

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

Loss: 3.3502
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: 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
3.6157	1.0	18844	3.7143	0.3599
3.3979	2.0	37688	3.5062	0.3804
3.2663	3.0	56532	3.3950	0.3932
3.1887	4.0	75376	3.3694	0.3977
3.1328	5.0	94220	3.3361	0.4009
3.0925	6.0	113064	3.3236	0.4038
3.0537	7.0	131908	3.3165	0.4050
3.0289	8.0	150752	3.3142	0.4063
2.9979	9.0	169596	3.2959	0.4083
2.9734	10.0	188440	3.2976	0.4096
2.9501	11.0	207284	3.3026	0.4094
2.9302	12.0	226128	3.3036	0.4097
2.9067	13.0	244972	3.3101	0.4103
2.885	14.0	263816	3.3063	0.4106
2.8686	15.0	282660	3.3195	0.4098
2.8474	16.0	301504	3.3275	0.4106
2.8235	17.0	320348	3.3297	0.4108
2.8091	18.0	339192	3.3385	0.4105
2.7899	19.0	358036	3.3433	0.4102
2.7718	20.0	376880	3.3502	0.4102

Framework versions

Transformers 4.35.0
Pytorch 2.1.0+cu121
Datasets 2.12.0
Tokenizers 0.14.1