--- license: apache-2.0 tags: - generated_from_trainer metrics: - accuracy - precision - recall - f1 model-index: - name: bert-finetuned-gesture-prediction-9-classes results: [] --- # bert-finetuned-gesture-prediction-9-classes This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset. It achieves the following results on the validation set: - Loss: 0.6948 - Accuracy: 0.8332 - Precision: 0.8352 - Recall: 0.8332 - F1: 0.8311 It achieves the following results on the test set: - Loss: 0.6337 - Accuracy: 0.8297 - Precision: 0.8365 - Recall: 0.8297 - F1: 0.8281 ## 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-9-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 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| | 1.6408 | 1.0 | 87 | 1.0168 | 0.7110 | 0.6825 | 0.7110 | 0.6559 | | 0.7629 | 2.0 | 174 | 0.7777 | 0.7977 | 0.7863 | 0.7977 | 0.7856 | | 0.4526 | 3.0 | 261 | 0.6951 | 0.8263 | 0.8276 | 0.8263 | 0.8199 | | 0.285 | 4.0 | 348 | 0.6948 | 0.8332 | 0.8352 | 0.8332 | 0.8311 | | 0.1788 | 5.0 | 435 | 0.7196 | 0.8277 | 0.8296 | 0.8277 | 0.8260 | | 0.1246 | 6.0 | 522 | 0.7677 | 0.8314 | 0.8357 | 0.8314 | 0.8284 | | 0.0866 | 7.0 | 609 | 0.7865 | 0.8407 | 0.8433 | 0.8407 | 0.8391 | | 0.0629 | 8.0 | 696 | 0.8168 | 0.8435 | 0.8457 | 0.8435 | 0.8420 | | 0.0489 | 9.0 | 783 | 0.8292 | 0.8417 | 0.8439 | 0.8417 | 0.8395 | | 0.0398 | 10.0 | 870 | 0.8391 | 0.8443 | 0.8461 | 0.8443 | 0.8422 | ### Framework versions - Transformers 4.26.1 - Pytorch 1.13.1+cu116 - Datasets 2.10.1 - Tokenizers 0.13.2