RoBerta_pubHealth

adity12345/RoBerta_pubHealth

RoBerta_pubHealth is a text classification model from adity12345. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.

should probably proofread and complete it, then remove this comment. --

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Hugging Face

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At a glance

Task: Text Classification
Library: transformers
License: mit
Model type: xlm-roberta
Access: Public
Created: Jul 8, 2025
Updated: Jul 8, 2025
SHA: 5d6680df

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Base models

FacebookAI/xlm-roberta-base

Model card

From the Hugging Face model README

RoBerta_pubHealth

This model is a fine-tuned version of FacebookAI/xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.5020
Accuracy: 0.795
Auc: 0.883
Precision: 0.908
Recall: 0.738
F1: 0.814
F1-macro: 0.793
F1-micro: 0.795
F1-weighted: 0.798

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: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 32
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	Auc	Precision	Recall	F1	F1-macro	F1-micro	F1-weighted
0.5384	0.3960	100	0.4643	0.773	0.838	0.887	0.718	0.793	0.771	0.773	0.776
0.4741	0.7921	200	0.4453	0.779	0.843	0.93	0.688	0.791	0.778	0.779	0.781
0.43	1.1861	300	0.4406	0.791	0.857	0.909	0.73	0.809	0.789	0.791	0.794
0.4253	1.5822	400	0.4639	0.74	0.85	0.972	0.588	0.733	0.739	0.74	0.738
0.4126	1.9782	500	0.4164	0.784	0.869	0.933	0.694	0.796	0.783	0.784	0.786
0.3775	2.3723	600	0.4987	0.739	0.854	0.983	0.579	0.729	0.738	0.739	0.736
0.3617	2.7683	700	0.4202	0.786	0.875	0.915	0.715	0.802	0.785	0.786	0.789
0.3309	3.1624	800	0.4239	0.787	0.883	0.895	0.736	0.808	0.785	0.787	0.79
0.3069	3.5584	900	0.4535	0.805	0.887	0.889	0.776	0.829	0.802	0.805	0.808
0.3071	3.9545	1000	0.4527	0.801	0.89	0.919	0.738	0.819	0.8	0.801	0.804
0.2605	4.3485	1100	0.4896	0.783	0.879	0.887	0.736	0.805	0.781	0.783	0.786
0.2609	4.7446	1200	0.5020	0.795	0.883	0.908	0.738	0.814	0.793	0.795	0.798

Framework versions

Transformers 4.53.0
Pytorch 2.6.0+cu124
Datasets 2.14.4
Tokenizers 0.21.2

Task: Text Classification
Library: transformers
Type: xlm-roberta
License: mit
Created: Jul 8, 2025
Updated: Jul 8, 2025