> ## Documentation Index
> Fetch the complete documentation index at: https://kumo.ai/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# train_start_offset

#### `train_start_offset: <integer>` (Optional)

## Description

Defines the numerical offset from the most recent entry to use to generate training data labels. Unless a custom time unit is specified in the aggregation, this value is in `days`. This can be used to make sure the query only generates labels on data from the last `train_start_offset` days. Regardless of this value, all data is used as an input to the model, but this value can help limit what labels are generated.

* `train_start_offset`must be > ` 0`.

### Supported Task Types

* Temporal

### Example 1

For example, you may want to only use training examples for customers that churned in the last year, but those customers may have 10 years of data that we will use for training the model.

<CodeGroup>
  ```Text Field theme={null}
  train_start_offset: <integer>
  train_start_offset: 10 # Only train on data from the last 10 days
  train_start_offset: 365 # Only train on data from the last year
  ```
</CodeGroup>

This only applies to temporal queries (queries that include a temporal aggregation such as `SUM(TRANSACTIONS.AMOUNT, 0, 2, days)`) The unit of this step is the same as the unit in the aggregation.

### Example 2

For example, for the query

<CodeGroup>
  ```yaml Field theme={null}
  PREDICT SUM(transactions.price, 0, 30, days)
  FOR EACH customers.customer_id
  ```
</CodeGroup>

The value of `train_start_offset` will be in `days`. For example, if set to `10`, the training table will only include entries from the last 10 days.

### Default Values

| run\_mode | Default Value |
| --------- | ------------- |
| FAST      | 0             |
| NORMAL    | 0             |
| BEST      | 0             |