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

# MODEL TRAINING RECIPE SCHEMA DEFINITIONS

> Schema definitions for training models

## OVERVIEW

The following defines the configuration schema used for training models in Oumi.

The configuration includes:

* Model loading configuration
* Dataset configuration
* Training parameters
* Logging and evaluation settings
* Parameter-efficient fine-tuning (PEFT)

<Note>Fields marked with (\*) are **required**.</Note>

***

# SCHEMA STRUCTURE

```json theme={null}
{
  "model": {},
  "data": {},
  "training": {},
  "peft": {}
}
```

***

# MODEL \*

Defines the model and tokenizer configuration.

| Field              | Type    | Required | Description                                         |
| ------------------ | ------- | -------- | --------------------------------------------------- |
| modelName          | string  | ✓        | HuggingFace model name or path                      |
| tokenizerName      | string  |          | Tokenizer name (defaults to model name)             |
| tokenizerPadToken  | string  |          | Override pad token for tokenizer                    |
| modelMaxLength     | number  |          | Maximum sequence length                             |
| torchDtype         | string  |          | PyTorch dtype (e.g. `float16`, `bfloat16`)          |
| trustRemoteCode    | boolean |          | Allow execution of custom model repo code           |
| attnImplementation | string  |          | Attention implementation (e.g. `flash_attention_2`) |
| chatTemplate       | string  |          | Custom Jinja chat template                          |
| enableLigerKernel  | boolean |          | Enable Liger fused kernel optimizations             |

### CONSTRAINTS

| Field     | Constraint          |
| --------- | ------------------- |
| modelName | Minimum length: `1` |

### EXAMPLE

```json theme={null}
{
  "model": {
    "modelName": "meta-llama/Llama-3-8B",
    "tokenizerName": "meta-llama/Llama-3-8B",
    "torchDtype": "bfloat16",
    "modelMaxLength": 4096
  }
}
```

***

# DATA \*

Defines datasets used for training and evaluation.

| Field      | Type   | Required | Description                      |
| ---------- | ------ | -------- | -------------------------------- |
| train      | object | ✓        | Training dataset configuration   |
| validation | object |          | Validation dataset configuration |
| test       | object |          | Test dataset configuration       |

***

## TRAIN \*

Training dataset definition.

| Field    | Type      | Required | Description      |
| -------- | --------- | -------- | ---------------- |
| datasets | object\[] | ✓        | List of datasets |

### CONSTRAINTS

| Field    | Constraint         |
| -------- | ------------------ |
| datasets | Exactly **1 item** |

***

### DATASET OBJECT

| Field     | Type    | Required | Description        |
| --------- | ------- | -------- | ------------------ |
| datasetId | integer | ✓        | Dataset identifier |

### RANGE

| Field     | Range                 |
| --------- | --------------------- |
| datasetId | (0..9007199254740991] |

***

## VALIDATION

Validation dataset configuration.

| Field    | Type      | Description         |
| -------- | --------- | ------------------- |
| datasets | object\[] | Validation datasets |

***

## TEST

Test dataset configuration.

| Field    | Type      | Description   |
| -------- | --------- | ------------- |
| datasets | object\[] | Test datasets |

***

# TRAINING \*

Defines model training parameters.

| Field                       | Type    | Description                                          |
| --------------------------- | ------- | ---------------------------------------------------- |
| maxSteps                    | number  | Stop training after this many steps (-1 = unlimited) |
| numTrainEpochs              | integer | Number of full passes over the dataset               |
| learningRate                | number  | Peak learning rate                                   |
| lrSchedulerType             | enum    | Learning rate scheduler                              |
| warmupRatio                 | number  | Fraction of warmup steps                             |
| warmupSteps                 | number  | Warmup steps (overrides ratio)                       |
| optimizer                   | string  | Optimizer name                                       |
| weightDecay                 | number  | L2 regularization                                    |
| adamBeta1                   | number  | Adam optimizer beta1                                 |
| adamBeta2                   | number  | Adam optimizer beta2                                 |
| maxGradNorm                 | number  | Gradient clipping value                              |
| mixedPrecisionDtype         | enum    | Mixed precision training dtype                       |
| enableGradientCheckpointing | boolean | Reduce memory usage                                  |
| loggingSteps                | number  | Log every N steps                                    |
| evalStrategy                | enum    | Evaluation schedule                                  |
| evalSteps                   | number  | Eval interval                                        |
| saveSteps                   | number  | Checkpoint interval                                  |
| saveFinalModel              | boolean | Save model after training                            |
| trainerType                 | enum    | Training algorithm                                   |
| seed                        | number  | Random seed                                          |
| enableWandb                 | boolean | Enable Weights & Biases logging                      |
| enableTensorboard           | boolean | Enable TensorBoard logging                           |
| runName                     | string  | Display name for training run                        |

***

## PARAMETER CONSTRAINTS

| Field          | Range          |
| -------------- | -------------- |
| numTrainEpochs | 1–30           |
| learningRate   | 0.000001–0.001 |
| runName        | length 1–128   |
| optimizer      | length 1–128   |

***

## LRSCHEDULERTYPE

| Allowed Values         |
| ---------------------- |
| `linear`               |
| `cosine`               |
| `cosine_with_restarts` |
| `cosine_with_min_lr`   |
| `constant`             |

***

## MIXEDPRECISIONDTYPE

| Allowed Values |
| -------------- |
| `none`         |
| `fp16`         |
| `bf16`         |

***

## EVALSTRATEGY

| Allowed Values |
| -------------- |
| `no`           |
| `steps`        |
| `epoch`        |

***

## TRAINERTYPE

| Allowed Values |
| -------------- |
| `sft`          |
| `opd`          |

***

# ONPOLICYDISTILLATION

Optional configuration for **on-policy distillation**.

> Requires `trainerType = "opd"`.

***

# PEFT \*

Parameter-efficient fine-tuning configuration.

| Field      | Type    | Required | Description               |
| ---------- | ------- | -------- | ------------------------- |
| usePeft    | boolean | ✓        | Enable PEFT               |
| peftMethod | string  | ✓        | PEFT method (e.g. `lora`) |
| loraR      | num     |          |                           |