speechless-code-mistral-7b-v1.0

* [AWQ model(s) for GPU inference.](https://huggingface.co/TheBloke/speechless-code-mistral-7B-v1.0-AWQ) * [GPTQ models for GPU inference, with multiple quantisation parameter options.](https://huggingface.co/TheBloke/speechless-code-mistral-7B-v1.0-GPTQ) * [2, 3, 4, 5, 6 and 8-bit GGUF models for CPU+GPU inference](https://huggingface.co/TheBloke/speechless-code-mistral-7B-v1.0-GGUF) Code: https://github.com/uukuguy/speechless Use the following dataset to fine-tune mistralai/Mistral-7B-v0.1 in order to improve the model's reasoning and planning abilities. Total 201,981 samples. - jondurbin/airoboros-2.2: Filter categories related to coding, reasoning and planning. 23,462 samples. - Open-Orca/OpenOrca: Filter the 'cot' category in 1M GPT4 dataset. 74,440 samples. - garage-bAInd/Open-Platypus: 100%, 24,926 samples. - WizardLM/WizardLM_evol_instruct_V2_196k: Coding coversation part. 30,185 samples - TokenBender/python_eval_instruct_51k: “python” in output .40,309 samples - Spider: 8,659 samples ## How to Prompt the Model This model accepts the Alpaca instruction format. For example: ``` You are an intelligent programming assistant. ### Instruction: Implement a linked list in C++ ### Response: ``` ## HumanEval | Metric | Value | | --- | --- | | humaneval-python | 51.21951219512195| ## Big Code Evaluation | | Humaneval | Java | Javascript | CPP | Php | Rust | Swift | R | Lua | D | Racket | Julia | | ------ | ------ | ------ | ------ | ------ | ------ | ------ | ------ | ------ | ------ | ------ | ------ | ------ | | pass@1 | 0.4260 | 0.3165 | 0.4241 | 0.3467 | 0.3548 | 0.2454 | 0.0000 | 0.1735 | 0.2942 | 0.1087 | 0.0000 | 0.3081 | | pass@10 | 0.5784 | 0.4506 | 0.5891 | 0.4845 | 0.4997 | 0.3858 | 0.0000 | 0.2516 | 0.4126 | 0.2018 | 0.0000 | 0.4427 | [Big Code Models Leaderboard](https://huggingface.co/spaces/bigcode/bigcode-models-leaderboard) CodeLlama-34B-Python: 53.29 CodeLlama-34B-Instruct: 50.79 CodeLlama-13B-Instruct: 50.6 CodeLlama-34B: 45.11 CodeLlama-13B-Python: 42.89 CodeLlama-13B: 35.07 ## lm-evaluation-harness ```json {'ARC (acc_norm)': 0.6109215017064846, 'HellaSwag (acc_norm)': 0.8358892650866361, 'MMLU (acc)': 0.6325456394049195, 'TruthfulQA (mc2)': 0.4746745250371087, 'Winoground (acc)': 0.7829518547750592, 'GSM8K (acc)': 0.467778620166793, 'DROP (f1)': 0.49585675335570545, 'Open LLM Score': 0.61437428571428571} ``` [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) | Metric | Value | | --- | --- | | ARC |60.58 | | HellaSwag |83.47 | | MMLU | 62.98 | | TruthfulQA | 47.9 | | Winoground | 78.69 | | GSM8K | 19.18 | | Average | 58.85 | ## Parameters | | | |------ | ------ | | lr | 2e-4 | | lr_scheduler_type | cosine | | weight_decay | 0.0 | | optim | paged_adamw_8bit | | flash_attention | True | | rerope | False | | max_new_tokens | 4096 | | num_train_epochs | 2 | | bits | 4 | | lora_r | 64 | | lora_alpha | 16 | | lora_dropout | 0.05 | | double_quant | True | | quant_type | nf4 | | dataset_format | airoboros | | mini_batch_size | 2 | | grandient_accumulation_steps | 32 | | bf16 | True | A40-48G x 2 | | | |------ | ------ | | epoch | 2.0 | | etrain_loss | 0.5 | | etrain_runtime | 1 day, 10:25:26.77 | | etrain_samples_per_second | 3.194 | | etrain_steps_per_second | 0.025 | | eeval_loss | 0.5146 | | eeval_runtime | 0:00:25.04 | | eeval_samples_per_second | 7.985 | | eeval_steps_per_second | | # [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_uukuguy__speechless-code-mistral-7b-v1.0) | Metric | Value | |-----------------------|---------------------------| | Avg. | 53.47 | | ARC (25-shot) | 60.58 | | HellaSwag (10-shot) | 83.75 | | MMLU (5-shot) | 62.98 | | TruthfulQA (0-shot) | 47.9 | | Winogrande (5-shot) | 78.69 | | GSM8K (5-shot) | 19.18 | | DROP (3-shot) | 21.19 |