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---
license: mit
base_model: microsoft/deberta-base
tags:
- generated_from_keras_callback
model-index:
- name: INTENT
results: []
---
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# INTENT
This is intent classification for enquiry of 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
|