---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: Intent-Classification-Bert-Base-Cased
  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-Classification-Bert-Base-Cased

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an [Intent-Classification-Commands](https://huggingface.co/datasets/dipesh/Intent-Classification-Commands) dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.6110
- Train Sparse Categorical Accuracy: 0.9836
- Validation Loss: 0.4073
- Validation Sparse Categorical Accuracy: 0.9583
- Epoch: 3

## Model description

Base model:  'bert-base-cased' can be used for intent classification. It trained on the [Intent-Classification-Commands](https://huggingface.co/datasets/dipesh/Intent-Classification-Commands) dataset. With the following classes-

```
{
  "0": "asking date",
  "1": "asking time",
  "2": "asking weather",
  "3": "check internet speed",
  "4": "click photo",
  "5": "covid cases",
  "6": "download youtube video",
  "7": "goodbye",
  "8": "greet",
  "9": "open website",
  "10": "play games",
  "11": "play on youtube",
  "12": "send email",
  "13": "send whatsapp message",
  "14": "take screenshot",
  "15": "tell me about",
  "16": "tell me joke",
  "17": "tell me news"
}
```

## Intended uses & limitations

Intent Classifications for Chatbot or Virtual Assistant.
Only supports the English language. It can't work in outside classes. But you can fine-tune it for your own use.

## Training and evaluation data

Dataset Used: [Intent-Classification-Commands](https://huggingface.co/datasets/dipesh/Intent-Classification-Commands)

## Training procedure

https://colab.research.google.com/drive/1KHg14glvhdV_ziOcY0pHm66PBYoBZMS0?usp=sharing

### Training hyperparameters


The following hyperparameters were used during training:
- optimizer: {'name': 'Adam', 'learning_rate': 5e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
- training_precision: float32

### Training results

![1.jpg](1.jpg)

![2.jpg](2.jpg)

### Framework versions

- Transformers 4.19.2
- TensorFlow 2.8.0
- Datasets 2.2.2
- Tokenizers 0.12.1


## Connect me on-

* Subscribe to me on: https://youtube.com/techportofficial

* DM me on (for quick response): https://instagram.com/dipesh_pal17