metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets: qfrodicio/gesture-prediction-21-classes
metrics:
  - accuracy
  - precision
  - recall
  - f1
model-index:
  - name: distilbert-finetuned-gesture-prediction-21-classes
    results: []

distilbert-finetuned-gesture-prediction-21-classes

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

Loss: 0.8430
Accuracy: 0.8077
Precision: 0.8063
Recall: 0.8077
F1: 0.8038

It achieves the following results on the test set:

Loss: 0.8332
Accuracy: 0.7934
Precision: 0.7925
Recall: 0.7934
F1: 0.7875

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

This 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
2.2082	1.0	104	1.3318	0.6956	0.6361	0.6956	0.6473
1.1512	2.0	208	1.0114	0.7604	0.7463	0.7604	0.7368
0.8152	3.0	312	0.8805	0.7860	0.7677	0.7860	0.7698
0.6142	4.0	416	0.8486	0.8025	0.8035	0.8025	0.7961
0.4726	5.0	520	0.8651	0.7992	0.7987	0.7992	0.7894
0.3677	6.0	624	0.8430	0.8077	0.8063	0.8077	0.8038
0.2967	7.0	728	0.8564	0.8037	0.8029	0.8037	0.7995
0.2494	8.0	832	0.8567	0.8077	0.8054	0.8077	0.8041
0.2163	9.0	936	0.8789	0.8075	0.8060	0.8075	0.8035
0.193	10.0	1040	0.8880	0.8077	0.8072	0.8077	0.8032

Framework versions

Transformers 4.26.1
Pytorch 1.13.1+cu116
Datasets 2.10.1
Tokenizers 0.13.2