--- license: apache-2.0 library_name: peft tags: - code - instruct - mistral datasets: - cognitivecomputations/dolphin-coder base_model: mistralai/Mistral-7B-v0.1 model-index: - name: mistral_7b_HalfEpoch_DolphinCoder results: - task: type: text-generation name: Text Generation dataset: name: AI2 Reasoning Challenge (25-Shot) type: ai2_arc config: ARC-Challenge split: test args: num_few_shot: 25 metrics: - type: acc_norm value: 61.77 name: normalized accuracy source: url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=qblocks/mistral_7b_HalfEpoch_DolphinCoder name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: HellaSwag (10-Shot) type: hellaswag split: validation args: num_few_shot: 10 metrics: - type: acc_norm value: 82.26 name: normalized accuracy source: url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=qblocks/mistral_7b_HalfEpoch_DolphinCoder name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MMLU (5-Shot) type: cais/mmlu config: all split: test args: num_few_shot: 5 metrics: - type: acc value: 61.75 name: accuracy source: url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=qblocks/mistral_7b_HalfEpoch_DolphinCoder name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: TruthfulQA (0-shot) type: truthful_qa config: multiple_choice split: validation args: num_few_shot: 0 metrics: - type: mc2 value: 45.46 source: url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=qblocks/mistral_7b_HalfEpoch_DolphinCoder name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: Winogrande (5-shot) type: winogrande config: winogrande_xl split: validation args: num_few_shot: 5 metrics: - type: acc value: 75.53 name: accuracy source: url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=qblocks/mistral_7b_HalfEpoch_DolphinCoder name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: GSM8k (5-shot) type: gsm8k config: main split: test args: num_few_shot: 5 metrics: - type: acc value: 29.64 name: accuracy source: url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=qblocks/mistral_7b_HalfEpoch_DolphinCoder name: Open LLM Leaderboard --- ### Finetuning Overview: **Model Used:** mistralai/Mistral-7B-v0.1 **Dataset:** cognitivecomputations/dolphin-coder #### Dataset Insights: [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. #### Finetuning Details: With the utilization of [MonsterAPI](https://monsterapi.ai)'s [no-code LLM finetuner](https://monsterapi.ai/finetuning), this finetuning: - Was achieved with great cost-effectiveness. - Completed in a total duration of 7hrs 36min for 0.5 epochs using an A6000 48GB GPU. - Costed `$15.2` for the entire run #### Hyperparameters & Additional Details: - **Epochs:** 0.5 - **Cost for full run:** $15.2 - **Model Path:** mistralai/Mistral-7B-v0.1 - **Learning Rate:** 0.0002 - **Data Split:** 100% train - **Gradient Accumulation Steps:** 128 - **lora r:** 32 - **lora alpha:** 64 ![image/png](https://cdn-uploads.huggingface.co/production/uploads/6313732454e6e5d9f0f797cd/0O1VKp3SJNfrhTd5earci.png) --- license: apache-2.0 # [Open LLM Leaderboard Evaluation Results](https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard) Detailed results can be found [here](https://huggingface.co./datasets/open-llm-leaderboard/details_qblocks__mistral_7b_HalfEpoch_DolphinCoder) | Metric |Value| |---------------------------------|----:| |Avg. |59.40| |AI2 Reasoning Challenge (25-Shot)|61.77| |HellaSwag (10-Shot) |82.26| |MMLU (5-Shot) |61.75| |TruthfulQA (0-shot) |45.46| |Winogrande (5-shot) |75.53| |GSM8k (5-shot) |29.64|