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--- |
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language: |
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- en |
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license: mit |
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model-index: |
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- name: MoMo-72B-LoRA-V1.4 |
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results: |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: AI2 Reasoning Challenge (25-Shot) |
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type: ai2_arc |
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config: ARC-Challenge |
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split: test |
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args: |
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num_few_shot: 25 |
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metrics: |
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- type: acc_norm |
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value: 69.2 |
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name: normalized accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=moreh/MoMo-72B-LoRA-V1.4 |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: HellaSwag (10-Shot) |
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type: hellaswag |
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split: validation |
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args: |
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num_few_shot: 10 |
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metrics: |
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- type: acc_norm |
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value: 85.07 |
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name: normalized accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=moreh/MoMo-72B-LoRA-V1.4 |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: MMLU (5-Shot) |
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type: cais/mmlu |
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config: all |
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split: test |
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args: |
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num_few_shot: 5 |
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metrics: |
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- type: acc |
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value: 77.12 |
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name: accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=moreh/MoMo-72B-LoRA-V1.4 |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: TruthfulQA (0-shot) |
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type: truthful_qa |
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config: multiple_choice |
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split: validation |
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args: |
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num_few_shot: 0 |
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metrics: |
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- type: mc2 |
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value: 62.66 |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=moreh/MoMo-72B-LoRA-V1.4 |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: Winogrande (5-shot) |
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type: winogrande |
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config: winogrande_xl |
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split: validation |
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args: |
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num_few_shot: 5 |
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metrics: |
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- type: acc |
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value: 83.74 |
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name: accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=moreh/MoMo-72B-LoRA-V1.4 |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: GSM8k (5-shot) |
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type: gsm8k |
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config: main |
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split: test |
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args: |
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num_few_shot: 5 |
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metrics: |
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- type: acc |
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value: 70.2 |
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name: accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=moreh/MoMo-72B-LoRA-V1.4 |
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name: Open LLM Leaderboard |
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--- |
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# **Introduction** |
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MoMo-72B is trained via Supervised Fine-Tuning (SFT) using [LoRA](https://arxiv.org/abs/2106.09685), with the QWEN-72B model as its base-model. |
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Note that we did not exploit any form of weight merge. |
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For leaderboard submission, the trained weight is realigned for compatibility with llama. |
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MoMo-72B is trained using **[Moreh](https://moreh.io/)**'s [MoAI platform](https://moreh.io/product), which simplifies the training of large-scale models, and AMD's MI250 GPU. |
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## Details |
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### Used Librarys |
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- torch |
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- peft |
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### Used Datasets |
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- Open-Orca/SlimOrca |
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- No other dataset was used |
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- No benchmark test set or the training set are used |
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- [data contamination check](https://github.com/swj0419/detect-pretrain-code-contamination) result |
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| Model | ARC | MMLU | TruthfulQA | GSM8K | |
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|------------------------------|-------|-------|-------|-------| |
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| **V1.4(result < 0.1, %)**| TBU |0.73 | 0.71 | TBU | |
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### Used Environments |
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- AMD MI250 & MoAI platform |
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- Please visit https://moreh.io/product for more information about MoAI platform |
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- Or, contact us directly [contact@moreh.io](mailto:contact@moreh.io) |
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## How to use |
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```python |
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# pip install transformers==4.35.2 |
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import torch |
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from transformers import AutoModelForCausalLM, AutoTokenizer |
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tokenizer = AutoTokenizer.from_pretrained("moreh/MoMo-72B-LoRA-V1.4") |
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model = AutoModelForCausalLM.from_pretrained( |
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"moreh/MoMo-72B-LoRA-V1.4" |
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) |
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``` |
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# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) |
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_moreh__MoMo-72B-LoRA-V1.4) |
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| Metric |Value| |
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|---------------------------------|----:| |
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|Avg. |74.67| |
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|AI2 Reasoning Challenge (25-Shot)|69.20| |
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|HellaSwag (10-Shot) |85.07| |
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|MMLU (5-Shot) |77.12| |
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|TruthfulQA (0-shot) |62.66| |
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|Winogrande (5-shot) |83.74| |
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|GSM8k (5-shot) |70.20| |
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