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If you are using a custom dataset, please add your **dataset description** to `dataset_info.json` according to the following format. We also provide several examples in the next section.
The `dataset_info.json` contains all available datasets. If you are using a custom dataset, please make sure to add a *dataset description* in `dataset_info.json` and specify `dataset: dataset_name` before training to use it.
Currently we support datasets in **alpaca** and **sharegpt** format.
```json
"dataset_name": {
"hf_hub_url": "the name of the dataset repository on the Hugging Face hub. (if specified, ignore script_url and file_name)",
"ms_hub_url": "the name of the dataset repository on the ModelScope hub. (if specified, ignore script_url and file_name)",
"ms_hub_url": "the name of the dataset repository on the Model Scope hub. (if specified, ignore script_url and file_name)",
"script_url": "the name of the directory containing a dataset loading script. (if specified, ignore file_name)",
"file_name": "the name of the dataset file in this directory. (required if above are not specified)",
"file_sha1": "the SHA-1 hash value of the dataset file. (optional, does not affect training)",
"file_name": "the name of the dataset folder or dataset file in this directory. (required if above are not specified)",
"formatting": "the format of the dataset. (optional, default: alpaca, can be chosen from {alpaca, sharegpt})",
"ranking": "whether the dataset is a preference dataset or not. (default: False)",
"subset": "the name of the subset. (optional, default: None)",
"folder": "the name of the folder of the dataset repository on the Hugging Face hub. (optional, default: None)",
"ranking": "whether the dataset is a preference dataset or not. (default: false)",
"formatting": "the format of the dataset. (optional, default: alpaca, can be chosen from {alpaca, sharegpt})",
"columns (optional)": {
"prompt": "the column name in the dataset containing the prompts. (default: instruction)",
"query": "the column name in the dataset containing the queries. (default: input)",
@@ -36,11 +37,15 @@ If you are using a custom dataset, please add your **dataset description** to `d
}
```
After that, you can load the custom dataset by specifying `--dataset dataset_name`.
## Alpaca Format
----
### Supervised Fine-Tuning Dataset
Currently we support dataset in **alpaca** or **sharegpt** format, the dataset in alpaca format should follow the below format:
In supervised fine-tuning, the `instruction` column will be concatenated with the `input` column and used as the human prompt, then the human prompt would be `instruction\ninput`. The `output` column represents the model response.
The `system` column will be used as the system prompt if specified.
The `history` column is a list consisting string tuples representing prompt-response pairs in the history messages. Note that the responses in the history **will also be learned by the model** in supervised fine-tuning.
```json
[
@@ -57,7 +62,7 @@ Currently we support dataset in **alpaca** or **sharegpt** format, the dataset i
]
```
Regarding the above dataset, the description in `dataset_info.json` should be:
Regarding the above dataset, the *dataset description* in `dataset_info.json` should be:
```json
"dataset_name": {
@@ -72,11 +77,9 @@ Regarding the above dataset, the description in `dataset_info.json` should be:
}
```
The `query` column will be concatenated with the `prompt` column and used as the human prompt, then the human prompt would be `prompt\nquery`. The `response` column represents the model response.
### Pre-training Dataset
The `system` column will be used as the system prompt. The `history` column is a list consisting string tuples representing prompt-response pairs in the history. Note that the responses in the history **will also be used for training** in supervised fine-tuning.
For the **pre-training datasets**, only the `prompt` column will be used for training, for example:
In pre-training, only the `prompt` column will be used for model learning.
```json
[
@@ -85,7 +88,7 @@ For the **pre-training datasets**, only the `prompt` column will be used for tra
]
```
Regarding the above dataset, the description in `dataset_info.json` should be:
Regarding the above dataset, the *dataset description* in `dataset_info.json` should be:
```json
"dataset_name": {
@@ -96,20 +99,24 @@ Regarding the above dataset, the description in `dataset_info.json` should be:
}
```
For the **preference datasets**, the `response` column should be a string list whose length is 2, with the preferred answers appearing first, for example:
### Preference Dataset
Preference datasets are used for reward modeling, DPO training and ORPO training.
It requires a better response in `chosen` column and a worse response in `rejected` column.
```json
[
{
"instruction": "human instruction",
"input": "human input",
"chosen": "chosen answer",
"rejected": "rejected answer"
"instruction": "human instruction (required)",
"input": "human input (optional)",
"chosen": "chosen answer (required)",
"rejected": "rejected answer (required)"
}
]
```
Regarding the above dataset, the description in `dataset_info.json` should be:
Regarding the above dataset, the *dataset description* in `dataset_info.json` should be:
```json
"dataset_name": {
@@ -124,14 +131,86 @@ Regarding the above dataset, the description in `dataset_info.json` should be:
}
```
----
### KTO Dataset
The dataset in **sharegpt** format should follow the below format:
KTO datasets require a extra `kto_tag` column containing the boolean human feedback.
```json
[
{
"instruction": "human instruction (required)",
"input": "human input (optional)",
"output": "model response (required)",
"kto_tag": "human feedback [true/false] (required)"
}
]
```
Regarding the above dataset, the *dataset description* in `dataset_info.json` should be:
```json
"dataset_name": {
"file_name": "data.json",
"columns": {
"prompt": "instruction",
"query": "input",
"response": "output",
"kto_tag": "kto_tag"
}
}
```
### Multimodal Dataset
Multimodal datasets require a `images` column containing the paths to the input image. Currently we only support one image.
```json
[
{
"instruction": "human instruction (required)",
"input": "human input (optional)",
"output": "model response (required)",
"images": [
"image path (required)"
]
}
]
```
Regarding the above dataset, the *dataset description* in `dataset_info.json` should be:
```json
"dataset_name": {
"file_name": "data.json",
"columns": {
"prompt": "instruction",
"query": "input",
"response": "output",
"images": "images"
}
}
```
## Sharegpt Format
### Supervised Fine-Tuning Dataset
Compared to the alpaca format, the sharegpt format allows the datasets have more **roles**, such as human, gpt, observation and function. They are presented in a list of objects in the `conversations` column.
Note that the human and observation should appear in odd positions, while gpt and function should appear in even positions.
```json
[
{
"conversations": [
{
"from": "human",
"value": "human instruction"
},
{
"from": "gpt",
"value": "model response"
},
{
"from": "human",
"value": "human instruction"
@@ -147,7 +226,7 @@ The dataset in **sharegpt** format should follow the below format:
]
```
Regarding the above dataset, the description in `dataset_info.json` should be:
Regarding the above dataset, the *dataset description* in `dataset_info.json` should be:
```json
"dataset_name": {
@@ -157,19 +236,61 @@ Regarding the above dataset, the description in `dataset_info.json` should be:
"messages": "conversations",
"system": "system",
"tools": "tools"
},
"tags": {
"role_tag": "from",
"content_tag": "value",
"user_tag": "human",
"assistant_tag": "gpt"
}
}
```
where the `messages` column should be a list following the `u/a/u/a/u/a` order.
### Preference Dataset
We also supports the dataset in the **openai** format:
Preference datasets in sharegpt format also require a better message in `chosen` column and a worse message in `rejected` column.
```json
[
{
"conversations": [
{
"from": "human",
"value": "human instruction"
},
{
"from": "gpt",
"value": "model response"
},
{
"from": "human",
"value": "human instruction"
}
],
"chosen": {
"from": "gpt",
"value": "chosen answer (required)"
},
"rejected": {
"from": "gpt",
"value": "rejected answer (required)"
}
}
]
```
Regarding the above dataset, the *dataset description* in `dataset_info.json` should be:
```json
"dataset_name": {
"file_name": "data.json",
"formatting": "sharegpt",
"ranking": true,
"columns": {
"messages": "conversations",
"chosen": "chosen",
"rejected": "rejected"
}
}
```
### OpenAI Format
The openai format is simply a special case of the sharegpt format, where the first message may be a system prompt.
```json
[
@@ -192,7 +313,7 @@ We also supports the dataset in the **openai** format:
]
```
Regarding the above dataset, the description in `dataset_info.json` should be:
Regarding the above dataset, the *dataset description* in `dataset_info.json` should be:
```json
"dataset_name": {
@@ -211,4 +332,6 @@ Regarding the above dataset, the description in `dataset_info.json` should be:
}
```
Pre-training datasets and preference datasets are **incompatible** with the sharegpt format yet.
The KTO datasets and multimodal datasets in sharegpt format are similar to the alpaca format.
Pre-training datasets are **incompatible** with the sharegpt format.