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[data] qwen3 fixes (#8109)

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@@ -50,7 +50,9 @@ Currently we support datasets in **alpaca** and **sharegpt** format.
* [Example dataset](alpaca_en_demo.json)
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.
In supervised fine-tuning, the `instruction` column will be concatenated with the `input` column and used as the user prompt, then the user prompt would be `instruction\ninput`. The `output` column represents the model response.
For reasoning models, if the dataset contains chain-of-thought (CoT), the CoT needs to be placed in the model responses, such as `<think>cot</think>output`.
The `system` column will be used as the system prompt if specified.
@@ -59,13 +61,13 @@ The `history` column is a list consisting of string tuples representing prompt-r
```json
[
{
"instruction": "human instruction (required)",
"input": "human input (optional)",
"instruction": "user instruction (required)",
"input": "user input (optional)",
"output": "model response (required)",
"system": "system prompt (optional)",
"history": [
["human instruction in the first round (optional)", "model response in the first round (optional)"],
["human instruction in the second round (optional)", "model response in the second round (optional)"]
["user instruction in the first round (optional)", "model response in the first round (optional)"],
["user instruction in the second round (optional)", "model response in the second round (optional)"]
]
}
]
@@ -86,6 +88,9 @@ Regarding the above dataset, the *dataset description* in `dataset_info.json` sh
}
```
> [!TIP]
> If the model has reasoning capabilities but the dataset does not contain chain-of-thought (CoT), LLaMA-Factory will automatically add empty CoT to the data. When `enable_thinking` is `True`, the empty CoT will be added to the model responses and loss computation will be considered; otherwise, it will be added to the user prompts and loss computation will be ignored. Please keep the `enable_thinking` parameter consistent during training and inference.
### Pre-training Dataset
- [Example dataset](c4_demo.jsonl)
@@ -119,8 +124,8 @@ It requires a better response in `chosen` column and a worse response in `reject
```json
[
{
"instruction": "human instruction (required)",
"input": "human input (optional)",
"instruction": "user instruction (required)",
"input": "user input (optional)",
"chosen": "chosen answer (required)",
"rejected": "rejected answer (required)"
}
@@ -174,7 +179,7 @@ Note that the human and observation should appear in odd positions, while gpt an
"conversations": [
{
"from": "human",
"value": "human instruction"
"value": "user instruction"
},
{
"from": "function_call",
@@ -225,7 +230,7 @@ Preference datasets in sharegpt format also require a better message in `chosen`
"conversations": [
{
"from": "human",
"value": "human instruction"
"value": "user instruction"
},
{
"from": "gpt",
@@ -233,7 +238,7 @@ Preference datasets in sharegpt format also require a better message in `chosen`
},
{
"from": "human",
"value": "human instruction"
"value": "user instruction"
}
],
"chosen": {
@@ -275,7 +280,7 @@ KTO datasets require a extra `kto_tag` column containing the boolean human feedb
"conversations": [
{
"from": "human",
"value": "human instruction"
"value": "user instruction"
},
{
"from": "gpt",
@@ -314,7 +319,7 @@ The number of images should be identical to the `<image>` tokens in the conversa
"conversations": [
{
"from": "human",
"value": "<image>human instruction"
"value": "<image>user instruction"
},
{
"from": "gpt",
@@ -355,7 +360,7 @@ The number of videos should be identical to the `<video>` tokens in the conversa
"conversations": [
{
"from": "human",
"value": "<video>human instruction"
"value": "<video>user instruction"
},
{
"from": "gpt",
@@ -396,7 +401,7 @@ The number of audios should be identical to the `<audio>` tokens in the conversa
"conversations": [
{
"from": "human",
"value": "<audio>human instruction"
"value": "<audio>user instruction"
},
{
"from": "gpt",
@@ -437,7 +442,7 @@ The openai format is simply a special case of the sharegpt format, where the fir
},
{
"role": "user",
"content": "human instruction"
"content": "user instruction"
},
{
"role": "assistant",