--- license: mit base_model: microsoft/deberta-base tags: - generated_from_keras_callback model-index: - name: INTENT results: [] --- # INTENT This is intent classification for customer order service, Features such as placing, Tracking and managment of orders, - Handles payment issues such as making and refund of payment - Options for delivery , address for shipping and also account management like editing, update account and delete account - - Options for contacting human agent - You can also sends complaints here - model is a fine-tuned version of [microsoft/deberta-base](https://huggingface.co/microsoft/deberta-base) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.0084 - Train Accuracy: 0.9987 - Validation Loss: 0.0019 - Validation Accuracy: 0.9995 - Epoch: 1 ## Model description Enter intent , you will get the label number depicting the intent - 'get_refund': 0, - 'change_order': 1, - 'contact_customer_service': 2, - 'recover_password': 3, - 'create_account': 4, - 'check_invoices': 5, - 'payment_issue': 6, - 'place_order': 7, - 'delete_account': 8, - 'set_up_shipping_address': 9, - 'delivery_options': 10, - 'track_order': 11, - 'change_shipping_address': 12, - 'track_refund': 13, - 'check_refund_policy': 14, - 'review': 15, - 'contact_human_agent': 16, - 'delivery_period': 17, - 'edit_account': 18, - 'registration_problems': 19, - 'get_invoice': 20, - 'switch_account': 21, - 'cancel_order': 22, - 'check_payment_methods': 23, - 'check_cancellation_fee': 24, - 'newsletter_subscription': 25, - 'complaint': 26 ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 2690, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False} - training_precision: float32 ### Training results | Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch | |:----------:|:--------------:|:---------------:|:-------------------:|:-----:| | 0.2113 | 0.9544 | 0.0056 | 0.9995 | 0 | | 0.0084 | 0.9987 | 0.0019 | 0.9995 | 1 | ### Framework versions - Transformers 4.35.2 - TensorFlow 2.15.0 - Datasets 2.16.0 - Tokenizers 0.15.0