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

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

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

Loss: 3.4150
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
3.7341	1.0	18595	3.8906	0.3472
3.4306	2.0	37190	3.6129	0.3759
3.2908	3.0	55785	3.4801	0.3892
3.2021	4.0	74380	3.4485	0.3959
3.1441	5.0	92975	3.4113	0.3998
3.0961	6.0	111570	3.3924	0.4024
3.0618	7.0	130165	3.3638	0.4049
3.0304	8.0	148760	3.3868	0.4056
2.9947	9.0	167355	3.3636	0.4067
2.9713	10.0	185950	3.3487	0.4074
2.9485	11.0	204545	3.3592	0.4080
2.9264	12.0	223140	3.3667	0.4078
2.9002	13.0	241735	3.3745	0.4085
2.8817	14.0	260330	3.3875	0.4088
2.8636	15.0	278925	3.3870	0.4087
2.8432	16.0	297520	3.3943	0.4086
2.8196	17.0	316115	3.3889	0.4092
2.8045	18.0	334710	3.4119	0.4089
2.7885	19.0	353305	3.4091	0.4090
2.768	20.0	371900	3.4150	0.4090

Framework versions

Transformers 4.35.0
Pytorch 2.1.0+cu121
Datasets 2.12.0
Tokenizers 0.14.1