Advanced usage & custom training
Let's create our own logic for a more customized training.
✏️ Preparing a dataset
The dataset will vary based on the task you work on. Let's work on sequence classification!
Our dataset will be composed of sentences and their associated classes. For example if you wanted to identify the subject of a conversation, you could create a dataset such as:
input class
The team scored a goal in the last seconds sports
The debate was heated between the 2 parties politics
I've never tasted croissants so delicious ! food
The objective of our trained model will be to correctly identify the class associated to new sentences.
🔎 Finding a dataset
If you don't have the right dataset, you can always explore the Datasets Hub. The "topic classification" category contains many datasets suitable for prototyping this model.
We select "Yahoo! Answers Topic Classification" and visualize it with the Datasets viewer.
Let's create our own logic for a more customized training.
✏️ Preparing a dataset
The dataset will vary based on the task you work on. Let's work on sequence classification!
Our dataset will be composed of sentences and their associated classes. For example if you wanted to identify the subject of a conversation, you could create a dataset such as:
input class
The team scored a goal in the last seconds sports
The debate was heated between the 2 parties politics
I've never tasted croissants so delicious ! food
The objective of our trained model will be to correctly identify the class associated to new sentences.
🔎 Finding a dataset
If you don't have the right dataset, you can always explore the Datasets Hub. The "topic classification" category contains many datasets suitable for prototyping this model.
We select "Yahoo! Answers Topic Classification" and visualize it with the Datasets viewer.