balanced-augmented-roberta-large-gest-pred-seqeval-partialmatch-2

Jsevisal/balanced-augmented-roberta-large-gest-pred-seqeval-partialmatch-2

balanced-augmented-roberta-large-gest-pred-seqeval-partialmatch-2 is a token classification model from Jsevisal. Use it when you need labels on individual words, such as names. It is set up for transformers. The card lists the license as other.

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

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Datasets

Jsevisal/balanced_augmented_dataset_2

Model card

From the Hugging Face model README

balanced-augmented-roberta-large-gest-pred-seqeval-partialmatch-2

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

Loss: 0.3718
Precision: 0.9171
Recall: 0.9183
F1: 0.9144
Accuracy: 0.9173

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: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
2.8924	1.0	52	2.1510	0.3032	0.2572	0.2464	0.4120
1.8492	2.0	104	1.3548	0.5880	0.5350	0.5046	0.6440
1.1692	3.0	156	0.8621	0.7443	0.6770	0.6775	0.7468
0.7452	4.0	208	0.6391	0.7779	0.7919	0.7691	0.8159
0.5185	5.0	260	0.6401	0.8197	0.8000	0.7868	0.8109
0.3536	6.0	312	0.4251	0.8808	0.8684	0.8675	0.8820
0.2411	7.0	364	0.4748	0.8709	0.8659	0.8613	0.8800
0.1762	8.0	416	0.3809	0.8991	0.8721	0.8812	0.8971
0.1377	9.0	468	0.3977	0.9062	0.8950	0.8953	0.9022
0.1026	10.0	520	0.4637	0.9068	0.8887	0.8897	0.8951
0.0763	11.0	572	0.4210	0.9079	0.9066	0.9020	0.9012
0.0554	12.0	624	0.4950	0.8962	0.8837	0.8809	0.8850
0.0419	13.0	676	0.4643	0.9043	0.9007	0.8969	0.8961
0.0358	14.0	728	0.3718	0.9171	0.9183	0.9144	0.9173
0.0264	15.0	780	0.4456	0.9349	0.9042	0.9132	0.9123
0.0178	16.0	832	0.4296	0.9362	0.9169	0.9227	0.9193
0.015	17.0	884	0.3900	0.9302	0.9235	0.9240	0.9254
0.0105	18.0	936	0.4335	0.9284	0.9161	0.9181	0.9168
0.0116	19.0	988	0.4426	0.9285	0.9138	0.9166	0.9138
0.0104	20.0	1040	0.4410	0.9276	0.9141	0.9163	0.9138

Framework versions

Transformers 4.28.1
Pytorch 2.0.0+cu118
Datasets 2.11.0
Tokenizers 0.13.3

LICENSE

Copyright (c) 2014, Universidad Carlos III de Madrid. Todos los derechos reservados. Este software es propiedad de la Universidad Carlos III de Madrid, grupo de investigación Robots Sociales. La Universidad Carlos III de Madrid es titular en exclusiva de los derechos de propiedad intelectual de este software. Queda prohibido cualquier uso indebido o no autorizado, entre estos, a título enunciativo pero no limitativo, la reproducción, fijación, distribución, comunicación pública, ingeniería inversa y/o transformación sobre dicho software, ya sea total o parcialmente, siendo el responsable del uso indebido o no autorizado también responsable de las consecuencias legales que pudieran derivarse de sus actos.

Task: Token Classification
Library: transformers
Type: roberta
License: other
Created: Mar 30, 2023
Updated: Jun 23, 2025