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--- |
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license: apache-2.0 |
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library_name: peft |
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tags: |
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- code |
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- instruct |
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- mistral |
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datasets: |
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- cognitivecomputations/dolphin-coder |
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base_model: mistralai/Mistral-7B-v0.1 |
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model-index: |
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- name: mistral_7b_DolphinCoder |
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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: 59.73 |
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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=Zangs3011/mistral_7b_DolphinCoder |
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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: 81.64 |
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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=Zangs3011/mistral_7b_DolphinCoder |
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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: 59.87 |
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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=Zangs3011/mistral_7b_DolphinCoder |
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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: 43.95 |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Zangs3011/mistral_7b_DolphinCoder |
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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: 74.59 |
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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=Zangs3011/mistral_7b_DolphinCoder |
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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: 26.23 |
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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=Zangs3011/mistral_7b_DolphinCoder |
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name: Open LLM Leaderboard |
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--- |
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### Finetuning Overview: |
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**Model Used:** mistralai/Mistral-7B-v0.1 |
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**Dataset:** cognitivecomputations/dolphin-coder |
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#### Dataset Insights: |
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[Dolphin-Coder](https://huggingface.co/datasets/cognitivecomputations/dolphin-coder) dataset – a high-quality collection of 100,000+ coding questions and responses. It's perfect for supervised fine-tuning (SFT), and teaching language models to improve on coding-based tasks. |
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#### Finetuning Details: |
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With the utilization of [MonsterAPI](https://monsterapi.ai)'s [no-code LLM finetuner](https://monsterapi.ai/finetuning), this finetuning: |
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- Was achieved with great cost-effectiveness. |
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- Completed in a total duration of 15hr 36mins for 1 epochs using an A6000 48GB GPU. |
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- Costed `$31.51` for the entire 1 epoch. |
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#### Hyperparameters & Additional Details: |
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- **Epochs:** 1 |
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- **Cost Per Epoch:** $31.51 |
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- **Model Path:** mistralai/Mistral-7B-v0.1 |
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- **Learning Rate:** 0.0002 |
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- **Data Split:** 100% train |
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- **Gradient Accumulation Steps:** 128 |
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- **lora r:** 32 |
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- **lora alpha:** 64 |
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![Train Loss](https://cdn-uploads.huggingface.co/production/uploads/63ba46aa0a9866b28cb19a14/kUDqiPdErxwf8sU-lHwI1.png) |
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--- |
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license: apache-2.0 |
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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_Zangs3011__mistral_7b_DolphinCoder) |
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| Metric |Value| |
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|---------------------------------|----:| |
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|Avg. |57.67| |
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|AI2 Reasoning Challenge (25-Shot)|59.73| |
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|HellaSwag (10-Shot) |81.64| |
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|MMLU (5-Shot) |59.87| |
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|TruthfulQA (0-shot) |43.95| |
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|Winogrande (5-shot) |74.59| |
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|GSM8k (5-shot) |26.23| |
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