bert-half-fakern – AI Model by stegostegosaur | AlphaNeural AI

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stegostegosaur/
bert-half-fakern

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text-classification

generated_from_trainer

google-bert/bert-base-uncased

autotrain_compatible

endpoints_compatible

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bert-half-fakern

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: 0.0282
Accuracy: 0.9955
F1: 0.9955
Precision: 0.9955
Recall: 0.9955

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: 5e-05
train_batch_size: 8
eval_batch_size: 16
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 5
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
0.0822	1.0	5281	0.0729	0.9834	0.9834	0.9839	0.9834
0.0053	2.0	10562	0.0252	0.9930	0.9930	0.9930	0.9930
0.0156	3.0	15843	0.0306	0.9951	0.9951	0.9951	0.9951
0.0045	4.0	21124	0.0306	0.9955	0.9955	0.9955	0.9955
0.0061	5.0	26405	0.0282	0.9955	0.9955	0.9955	0.9955

Framework versions

Transformers 4.52.4
Pytorch 2.6.0+cu124
Datasets 2.14.4
Tokenizers 0.21.1