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Jsevisal/
ft-roberta-gest-pred-seqeval-partialmatch

Name: ft-roberta-gest-pred-seqeval-partialmatch
Rating: 2.5 (6 reviews)

generated_from_trainer

Jsevisal/gesture_pred

other

autotrain_compatible

endpoints_compatible

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roberta-gest-pred-seqeval-partialmatch

This model is a fine-tuned version of xlm-roberta-large-finetuned-conll03-english on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.6258
Precision: 0.7927
Recall: 0.7354
F1: 0.7381
Accuracy: 0.8323

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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
1.8351	1.0	147	0.9547	0.5114	0.4560	0.4404	0.7414
0.8448	2.0	294	0.6491	0.7273	0.6873	0.6768	0.8103
0.5622	3.0	441	0.7047	0.7169	0.6724	0.6631	0.8044
0.3594	4.0	588	0.6258	0.7927	0.7354	0.7381	0.8323
0.2304	5.0	735	0.7149	0.7861	0.7029	0.7086	0.8389
0.1566	6.0	882	0.7313	0.8518	0.8039	0.7852	0.8549
0.1021	7.0	1029	0.7592	0.8084	0.7493	0.7462	0.8639
0.0718	8.0	1176	0.8252	0.8115	0.7470	0.7336	0.8591
0.0518	9.0	1323	0.9014	0.8112	0.7495	0.7343	0.8639
0.0395	10.0	1470	0.9160	0.8093	0.7469	0.7331	0.8633

Framework versions

Transformers 4.27.3
Pytorch 1.13.1+cu116
Datasets 2.10.1
Tokenizers 0.13.2

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.

Jsevisal/ft-roberta-gest-pred-seqeval-partialmatch

roberta-gest-pred-seqeval-partialmatch

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

LICENSE

Jsevisal/
ft-roberta-gest-pred-seqeval-partialmatch