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

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

balanced-augmented-roberta-large-gest-pred-seqeval-partialmatch 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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At a glance

Task: Token Classification
Library: transformers
License: other
Model type: roberta
Access: Public
Created: Apr 18, 2023
Updated: Sep 14, 2023
SHA: 21e95ddf

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Datasets

Jsevisal/balanced_augmented_dataset

Model card

From the Hugging Face model README

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

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

Loss: 0.9293
Precision: 0.8334
Recall: 0.8067
F1: 0.8133
Accuracy: 0.8081

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
3.1537	1.0	32	2.4492	0.2359	0.1166	0.1062	0.3068
2.2261	2.0	64	1.7166	0.4414	0.4662	0.3968	0.5253
1.435	3.0	96	1.3082	0.7000	0.6169	0.6234	0.6470
0.9158	4.0	128	1.1422	0.7472	0.6822	0.6968	0.7028
0.569	5.0	160	0.9870	0.7668	0.7303	0.7394	0.7512
0.3464	6.0	192	1.0410	0.7667	0.7496	0.7450	0.7517
0.2418	7.0	224	1.0642	0.8023	0.7644	0.7672	0.7602
0.166	8.0	256	0.9678	0.8125	0.7816	0.7882	0.7996
0.1205	9.0	288	0.9804	0.8258	0.7855	0.7963	0.7895
0.1029	10.0	320	1.0475	0.8009	0.7854	0.7847	0.7911
0.0689	11.0	352	1.0477	0.8252	0.7929	0.7985	0.8006
0.0596	12.0	384	0.9293	0.8334	0.8067	0.8133	0.8081
0.0453	13.0	416	1.0440	0.8253	0.7964	0.8048	0.7990
0.0343	14.0	448	1.0528	0.8352	0.8076	0.8111	0.8123
0.028	15.0	480	1.0848	0.8468	0.8134	0.8189	0.8091
0.02	16.0	512	1.1202	0.8388	0.8125	0.8157	0.8198
0.0185	17.0	544	1.0653	0.8394	0.8059	0.8136	0.8139
0.0138	18.0	576	1.1089	0.8479	0.8074	0.8174	0.8214
0.0134	19.0	608	1.1192	0.8409	0.8072	0.8143	0.8161
0.0129	20.0	640	1.1172	0.8366	0.8060	0.8122	0.8123

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: Apr 18, 2023
Updated: Sep 14, 2023