--- license: apache-2.0 tags: - generated_from_trainer metrics: - accuracy - precision - recall - f1 model-index: - name: distilbert-finetuned-gesture-prediction-9-classes results: [] --- # distilbert-finetuned-gesture-prediction-9-classes This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on the None dataset. It achieves the following results on the validation set: - Loss: 0.6479 - Accuracy: 0.8214 - Precision: 0.8230 - Recall: 0.8214 - F1: 0.8172 It achieves the following results on the test set: - Loss: 0.6475 - Accuracy: 0.8144 - Precision: 0.8144 - Recall: 0.8144 - F1: 0.8095 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data The model has been trained on 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 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| | 1.6636 | 1.0 | 87 | 0.9715 | 0.7270 | 0.6909 | 0.7270 | 0.6897 | | 0.7503 | 2.0 | 174 | 0.7360 | 0.7987 | 0.7874 | 0.7987 | 0.7879 | | 0.5283 | 3.0 | 261 | 0.6831 | 0.8056 | 0.8046 | 0.8056 | 0.8005 | | 0.3853 | 4.0 | 348 | 0.6479 | 0.8214 | 0.8230 | 0.8214 | 0.8172 | | 0.28 | 5.0 | 435 | 0.6570 | 0.8314 | 0.8348 | 0.8314 | 0.8289 | | 0.2163 | 6.0 | 522 | 0.6887 | 0.8322 | 0.8346 | 0.8322 | 0.8298 | | 0.158 | 7.0 | 609 | 0.7078 | 0.8336 | 0.8362 | 0.8336 | 0.8311 | | 0.1308 | 8.0 | 696 | 0.7197 | 0.8415 | 0.8444 | 0.8415 | 0.8394 | | 0.1061 | 9.0 | 783 | 0.7362 | 0.8419 | 0.8441 | 0.8419 | 0.8394 | | 0.0947 | 10.0 | 870 | 0.7412 | 0.8435 | 0.8458 | 0.8435 | 0.8410 | ### Framework versions - Transformers 4.26.1 - Pytorch 1.13.1+cu116 - Datasets 2.10.1 - Tokenizers 0.13.2