Benign10MGPT2_fromP_BFall_10KGen_toP_0.75 – AI Model by AustinCarthy | AlphaNeural AI

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AustinCarthy/
Benign10MGPT2_fromP_BFall_10KGen_toP_0.75

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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Benign10MGPT2_fromP_BFall_10KGen_toP_0.75

This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.1046
Accuracy: 0.9898
F1: 0.8806
Precision: 0.9952
Recall: 0.7896
Roc Auc Score: 0.8947
Tpr At Fpr 0.01: 0.7606

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: 2e-05
train_batch_size: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5.0
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall	Roc Auc Score	Tpr At Fpr 0.01
0.0104	1.0	13125	0.0568	0.9869	0.8415	0.9964	0.7282	0.8640	0.7054
0.0078	2.0	26250	0.0722	0.9871	0.8440	0.9932	0.7338	0.8668	0.6516
0.0047	3.0	39375	0.0675	0.9900	0.8833	0.9913	0.7966	0.8981	0.7312
0.0011	4.0	52500	0.0811	0.9904	0.8888	0.9936	0.804	0.9019	0.7698
0.0	5.0	65625	0.1046	0.9898	0.8806	0.9952	0.7896	0.8947	0.7606

Framework versions

Transformers 4.29.1
Pytorch 1.9.0+cu111
Datasets 2.10.1
Tokenizers 0.13.2