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# 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

{"license": "mit", "tags": ["generated_from_keras_callback"], "base_model": "microsoft/deberta-base", "model-index": [{"name": "INTENT", "results": []}]}
transformers tf deberta text-classification generated_from_keras_callback base_model:microsoft/deberta-base license:mit autotrain_compatible endpoints_compatible region:us