metadata

license: mit
tags:
  - generated_from_trainer
datasets: qfrodicio/gesture-prediction-21-classes
metrics:
  - accuracy
  - precision
  - recall
  - f1
model-index:
  - name: roberta-finetuned-gesture-prediction-21-classes
    results: []

roberta-finetuned-gesture-prediction-21-classes

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

Loss: 0.7782
Accuracy: 0.8185
Precision: 0.8116
Recall: 0.8185
F1: 0.8072

It achieves the following results on the evaluation set:

Loss: 0.8142
Accuracy: 0.8154
Precision: 0.8189
Recall: 0.8154
F1: 0.8125

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

The model has been trained with the qfrodicio/gesture-prediction-21-classes dataset

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 2e-05
weight_decay: 0.01
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	Accuracy	Precision	Recall	F1
2.2147	1.0	104	1.3857	0.7406	0.6887	0.7406	0.7013
1.2291	2.0	208	0.9750	0.7907	0.7597	0.7907	0.7618
0.836	3.0	312	0.8609	0.8028	0.7813	0.8028	0.7829
0.6129	4.0	416	0.8059	0.8078	0.8030	0.8078	0.7973
0.4747	5.0	520	0.7782	0.8185	0.8116	0.8185	0.8072
0.3639	6.0	624	0.7825	0.8175	0.8170	0.8175	0.8108
0.295	7.0	728	0.7913	0.8365	0.8283	0.8365	0.8280
0.236	8.0	832	0.7619	0.8273	0.8230	0.8273	0.8229
0.1989	9.0	936	0.7880	0.8309	0.8258	0.8309	0.8261
0.1879	10.0	1040	0.7915	0.8314	0.8247	0.8314	0.8264

Framework versions

Transformers 4.26.1
Pytorch 1.13.1+cu116
Datasets 2.10.1
Tokenizers 0.13.2