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--- |
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license: mit |
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base_model: microsoft/deberta-base |
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tags: |
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- generated_from_keras_callback |
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model-index: |
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- name: INTENT |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information Keras had access to. You should |
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probably proofread and complete it, then remove this comment. --> |
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# INTENT |
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This is intent classification for customer order service, |
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Features such as placing, Tracking and managment of orders, |
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Handles payment issues such as making and refund of payment |
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Options for delivery , address for shipping and also account management like password change, update account and delete account |
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Options for contacting human agent |
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You can also sends complaints here |
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model is a fine-tuned version of [microsoft/deberta-base](https://huggingface.co/microsoft/deberta-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Train Loss: 0.0084 |
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- Train Accuracy: 0.9987 |
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- Validation Loss: 0.0019 |
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- Validation Accuracy: 0.9995 |
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- Epoch: 1 |
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## Model description |
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Enter intent , you will get the label number depicting the intent |
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'get_refund': 0, |
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'change_order': 1, |
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'contact_customer_service': 2, |
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'recover_password': 3, |
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'create_account': 4, |
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'check_invoices': 5, |
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'payment_issue': 6, |
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'place_order': 7, |
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'delete_account': 8, |
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'set_up_shipping_address': 9, |
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'delivery_options': 10, |
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'track_order': 11, |
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'change_shipping_address': 12, |
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'track_refund': 13, |
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'check_refund_policy': 14, |
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'review': 15, |
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'contact_human_agent': 16, |
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'delivery_period': 17, |
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'edit_account': 18, |
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'registration_problems': 19, |
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'get_invoice': 20, |
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'switch_account': 21, |
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'cancel_order': 22, |
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'check_payment_methods': 23, |
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'check_cancellation_fee': 24, |
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'newsletter_subscription': 25, |
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'complaint': 26 |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- 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} |
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- training_precision: float32 |
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### Training results |
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| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch | |
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|:----------:|:--------------:|:---------------:|:-------------------:|:-----:| |
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| 0.2113 | 0.9544 | 0.0056 | 0.9995 | 0 | |
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| 0.0084 | 0.9987 | 0.0019 | 0.9995 | 1 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- TensorFlow 2.15.0 |
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- Datasets 2.16.0 |
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- Tokenizers 0.15.0 |
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