初始化项目，由ModelHub XC社区提供模型
Model: mesolitica/Malaysian-Qwen2.5-3B-Instruct Source: Original Platform
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README.md
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---
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language:
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- ms
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- en
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- zh
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- ta
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---
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# Malaysian Qwen 2.5 3B Instruct
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Continue finetuning https://huggingface.co/Qwen/Qwen2.5-3B-Instruct on highly curated 1.5B tokens Malaysian instruction dataset.
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## Improvement
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1. Support respond in Mandarin, Tamil, Jawi, Manglish, Johor, Kedah, Kelantan, Pahang, Perak, Sabah, Sarawak, Selangor, Negeri Sembilan and Terengganu.
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2. Able to code in Mandarin, Tamil, Jawi, Manglish, Johor, Kedah, Kelantan, Pahang, Perak, Sabah, Sarawak, Selangor, Negeri Sembilan and Terengganu.
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3. Multi-turn Malaysian context such as related to Malaysian Legislation, politics, religions and languages.
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## Training session
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Finetune on [mesolitica/Malaysian-SFT](https://huggingface.co/datasets/mesolitica/Malaysian-SFT) to make the model understand Malaysian context.
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## How we train
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1. LoRA on `["q_proj", "k_proj", "v_proj", "o_proj", "gate_proj", "up_proj", "down_proj", "embed_tokens", "lm_head"]`.
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2. 128 Rank with alpha 256, or alpha of 2.0
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3. Multipacking 8192 context length with proper SDPA causal masking to prevent document contamination and also make sure proper position ids.
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4. Chunk CCE loss for LoRA.
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5. WanDB at https://wandb.ai/huseinzol05/lora-embedding-128-qwen2.5-3b-malaysian-8k?nw=nwuserhuseinzol05
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Source code at https://github.com/mesolitica/malaya/tree/master/session/qwen2.5
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## Benchmark
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### MalayMMLU
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#### Probability next tokens
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Based on 0-shot official MalayMMLU First token accuracy,
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```
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Model Accuracy shot by_letter category
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0 Malaysian-Qwen2.5-3B-Instruct 65.124847 0shot True STEM
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1 Malaysian-Qwen2.5-3B-Instruct 65.903308 0shot True Language
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2 Malaysian-Qwen2.5-3B-Instruct 58.514021 0shot True Social science
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3 Malaysian-Qwen2.5-3B-Instruct 59.678580 0shot True Others
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4 Malaysian-Qwen2.5-3B-Instruct 63.526735 0shot True Humanities
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{'Social science': 6918, 'Language': 6288, 'Humanities': 4395, 'Others': 4169, 'STEM': 2443}
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Model : Malaysian-Qwen2.5-3B-Instruct
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Metric : first
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Shot : 0shot
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average accuracy 62.21038285218684
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accuracy for STEM 65.12484650020467
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accuracy for Language 65.9033078880407
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accuracy for Social science 58.51402139346632
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accuracy for Others 59.67857999520268
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accuracy for Humanities 63.52673492605233
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```
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While the original model,
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```
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Model Accuracy shot by_letter category
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0 Qwen2.5-3B-Instruct 55.218993 0shot True STEM
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1 Qwen2.5-3B-Instruct 60.464377 0shot True Language
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2 Qwen2.5-3B-Instruct 49.479618 0shot True Social science
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3 Qwen2.5-3B-Instruct 50.755577 0shot True Others
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4 Qwen2.5-3B-Instruct 57.542662 0shot True Humanities
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{'Social science': 6918, 'Language': 6288, 'Humanities': 4395, 'Others': 4169, 'STEM': 2443}
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Model : Qwen2.5-3B-Instruct
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Metric : first
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Shot : 0shot
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average accuracy 54.59463924338166
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accuracy for STEM 55.218993041342614
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accuracy for Language 60.464376590330794
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accuracy for Social science 49.479618386816995
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accuracy for Others 50.75557687694891
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accuracy for Humanities 57.54266211604096
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```
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#### First token match using vLLM
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Based on 0-shot exact first token match using vLLM Guided Decoding,LLM,
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```
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Model Accuracy shot category
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0 Malaysian-Qwen2.5-3B-Instruct 55.505526 0 STEM
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1 Malaysian-Qwen2.5-3B-Instruct 59.446565 0 Language
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2 Malaysian-Qwen2.5-3B-Instruct 53.093380 0 Social science
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3 Malaysian-Qwen2.5-3B-Instruct 52.866395 0 Others
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4 Malaysian-Qwen2.5-3B-Instruct 54.152446 0 Humanities
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Model : Malaysian-Qwen2.5-3B-Instruct
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Metric : full
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Shot : 0
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average accuracy 55.139800933382894
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accuracy for STEM 55.50552599263201
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accuracy for Language 59.44656488549618
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accuracy for Social science 53.09337958947673
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accuracy for Others 52.86639481890142
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accuracy for Humanities 54.152445961319685
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```
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While the original model,
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```
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Model Accuracy shot category
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0 Qwen2.5-3B-Instruct 51.125665 0 STEM
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1 Qwen2.5-3B-Instruct 57.649491 0 Language
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2 Qwen2.5-3B-Instruct 44.998554 0 Social science
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3 Qwen2.5-3B-Instruct 47.637323 0 Others
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4 Qwen2.5-3B-Instruct 54.357224 0 Humanities
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Model : Qwen2.5-3B-Instruct
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Metric : full
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Shot : 0
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average accuracy 51.05521827117664
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accuracy for STEM 51.12566516577978
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accuracy for Language 57.649491094147585
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accuracy for Social science 44.99855449551894
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accuracy for Others 47.637323099064524
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accuracy for Humanities 54.357224118316275
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```
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## Acknowledgement
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Special thanks to https://www.sns.com.my and Nvidia for 8x H100 node!
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config.json
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|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151646": {
|
||||
"content": "<|object_ref_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151647": {
|
||||
"content": "<|object_ref_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151648": {
|
||||
"content": "<|box_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151649": {
|
||||
"content": "<|box_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151650": {
|
||||
"content": "<|quad_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151651": {
|
||||
"content": "<|quad_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151652": {
|
||||
"content": "<|vision_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151653": {
|
||||
"content": "<|vision_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151654": {
|
||||
"content": "<|vision_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151655": {
|
||||
"content": "<|image_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151656": {
|
||||
"content": "<|video_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151657": {
|
||||
"content": "<tool_call>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151658": {
|
||||
"content": "</tool_call>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151659": {
|
||||
"content": "<|fim_prefix|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151660": {
|
||||
"content": "<|fim_middle|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151661": {
|
||||
"content": "<|fim_suffix|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151662": {
|
||||
"content": "<|fim_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151663": {
|
||||
"content": "<|repo_name|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151664": {
|
||||
"content": "<|file_sep|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
}
|
||||
},
|
||||
"additional_special_tokens": [
|
||||
"<|im_start|>",
|
||||
"<|im_end|>",
|
||||
"<|object_ref_start|>",
|
||||
"<|object_ref_end|>",
|
||||
"<|box_start|>",
|
||||
"<|box_end|>",
|
||||
"<|quad_start|>",
|
||||
"<|quad_end|>",
|
||||
"<|vision_start|>",
|
||||
"<|vision_end|>",
|
||||
"<|vision_pad|>",
|
||||
"<|image_pad|>",
|
||||
"<|video_pad|>"
|
||||
],
|
||||
"bos_token": null,
|
||||
"chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0]['role'] == 'system' %}\n {{- messages[0]['content'] }}\n {%- else %}\n {{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}\n {%- endif %}\n {{- \"\\n\\n# Tools\\n\\nYou may call one or more functions to assist with the user query.\\n\\nYou are provided with function signatures within <tools></tools> XML tags:\\n<tools>\" }}\n {%- for tool in tools %}\n {{- \"\\n\" }}\n {{- tool | tojson }}\n {%- endfor %}\n {{- \"\\n</tools>\\n\\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\\n<tool_call>\\n{\\\"name\\\": <function-name>, \\\"arguments\\\": <args-json-object>}\\n</tool_call><|im_end|>\\n\" }}\n{%- else %}\n {%- if messages[0]['role'] == 'system' %}\n {{- '<|im_start|>system\\n' + messages[0]['content'] + '<|im_end|>\\n' }}\n {%- else %}\n {{- '<|im_start|>system\\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\\n' }}\n {%- endif %}\n{%- endif %}\n{%- for message in messages %}\n {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) or (message.role == \"assistant\" and not message.tool_calls) %}\n {{- '<|im_start|>' + message.role + '\\n' + message.content + '<|im_end|>' + '\\n' }}\n {%- elif message.role == \"assistant\" %}\n {{- '<|im_start|>' + message.role }}\n {%- if message.content %}\n {{- '\\n' + message.content }}\n {%- endif %}\n {%- for tool_call in message.tool_calls %}\n {%- if tool_call.function is defined %}\n {%- set tool_call = tool_call.function %}\n {%- endif %}\n {{- '\\n<tool_call>\\n{\"name\": \"' }}\n {{- tool_call.name }}\n {{- '\", \"arguments\": ' }}\n {{- tool_call.arguments | tojson }}\n {{- '}\\n</tool_call>' }}\n {%- endfor %}\n {{- '<|im_end|>\\n' }}\n {%- elif message.role == \"tool\" %}\n {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != \"tool\") %}\n {{- '<|im_start|>user' }}\n {%- endif %}\n {{- '\\n<tool_response>\\n' }}\n {{- message.content }}\n {{- '\\n</tool_response>' }}\n {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n {{- '<|im_end|>\\n' }}\n {%- endif %}\n {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n {{- '<|im_start|>assistant\\n' }}\n{%- endif %}\n",
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "<|im_end|>",
|
||||
"errors": "replace",
|
||||
"extra_special_tokens": {},
|
||||
"model_max_length": 131072,
|
||||
"pad_token": "<|endoftext|>",
|
||||
"split_special_tokens": false,
|
||||
"tokenizer_class": "Qwen2Tokenizer",
|
||||
"unk_token": null
|
||||
}
|
||||
1
vocab.json
Normal file
1
vocab.json
Normal file
File diff suppressed because one or more lines are too long
Reference in New Issue
Block a user