Modelpublic

buelfhood/conplag1_modernbert_ep30_bs16_lr1e-05_l256_s42_ppy_loss

sourceHugging Faceapache-2.0updated 11mo agoView on Hugging Face

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Model Card

conplag1modernbertep30bs16lr1e-05l256s42ppyloss

This model is a fine-tuned version of answerdotai/ModernBERT-base on an unknown dataset. It achieves the following results on the evaluation set:

—Loss: 0.4871
—Accuracy: 0.8102
—Recall: 0.6316
—Precision: 0.6667
—F1: 0.6486
—F Beta Score: 0.6420

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: 1e-05
—trainbatchsize: 16
—evalbatchsize: 16
—seed: 42
—optimizer: Use OptimizerNames.ADAMWTORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
—lrschedulertype: linear
—num_epochs: 30

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Recall	Precision	F1	F Beta Score
0.6141	1.0	40	0.6335	0.4891	0.8947	0.34	0.4928	0.5957
0.6037	2.0	80	0.5559	0.6642	0.7632	0.4394	0.5577	0.6221
0.5435	3.0	120	0.7329	0.7956	0.2632	1.0	0.4167	0.3403
0.3798	4.0	160	0.4871	0.8102	0.6316	0.6667	0.6486	0.6420
0.3456	5.0	200	0.4915	0.7956	0.6579	0.625	0.6410	0.6474
0.3091	6.0	240	0.9186	0.8540	0.5	0.95	0.6552	0.5853
0.1557	7.0	280	1.0793	0.8467	0.4737	0.9474	0.6316	0.5598

Framework versions

—Transformers 4.51.3
—Pytorch 2.8.0+cu128
—Datasets 3.1.0
—Tokenizers 0.21.4