初始化项目，由ModelHub XC社区提供模型
Model: uukuguy/speechless-code-mistral-7b-v1.0 Source: Original Platform
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README.md
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README.md
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---
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language:
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- en
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library_name: transformers
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pipeline_tag: text-generation
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datasets:
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- jondurbin/airoboros-2.2
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- Open-Orca/OpenOrca
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- garage-bAInd/Open-Platypus
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- WizardLM/WizardLM_evol_instruct_V2_196k
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- TokenBender/python_eval_instruct_51k
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tags:
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- code
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license: apache-2.0
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model-index:
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- name: SpeechlessCoder
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results:
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- task:
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type: text-generation
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dataset:
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type: openai_humaneval
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name: HumanEval
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metrics:
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- name: pass@1
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type: pass@1
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value: 51.21951219512195
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verified: false
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---
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<p><h1> speechless-code-mistral-7b-v1.0 </h1></p>
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* [AWQ model(s) for GPU inference.](https://huggingface.co/TheBloke/speechless-code-mistral-7B-v1.0-AWQ)
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* [GPTQ models for GPU inference, with multiple quantisation parameter options.](https://huggingface.co/TheBloke/speechless-code-mistral-7B-v1.0-GPTQ)
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* [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)
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Code: https://github.com/uukuguy/speechless
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Use the following dataset to fine-tune mistralai/Mistral-7B-v0.1 in order to improve the model's reasoning and planning abilities.
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Total 201,981 samples.
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- jondurbin/airoboros-2.2: Filter categories related to coding, reasoning and planning. 23,462 samples.
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- Open-Orca/OpenOrca: Filter the 'cot' category in 1M GPT4 dataset. 74,440 samples.
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- garage-bAInd/Open-Platypus: 100%, 24,926 samples.
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- WizardLM/WizardLM_evol_instruct_V2_196k: Coding coversation part. 30,185 samples
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- TokenBender/python_eval_instruct_51k: “python” in output .40,309 samples
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- Spider: 8,659 samples
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## How to Prompt the Model
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This model accepts the Alpaca instruction format.
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For example:
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```
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You are an intelligent programming assistant.
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### Instruction:
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Implement a linked list in C++
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### Response:
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```
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## HumanEval
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| Metric | Value |
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| --- | --- |
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| humaneval-python | 51.21951219512195|
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## Big Code Evaluation
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| | Humaneval | Java | Javascript | CPP | Php | Rust | Swift | R | Lua | D | Racket | Julia |
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| ------ | ------ | ------ | ------ | ------ | ------ | ------ | ------ | ------ | ------ | ------ | ------ | ------ |
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| 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 |
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| 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 |
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[Big Code Models Leaderboard](https://huggingface.co/spaces/bigcode/bigcode-models-leaderboard)
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CodeLlama-34B-Python: 53.29
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CodeLlama-34B-Instruct: 50.79
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CodeLlama-13B-Instruct: 50.6
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CodeLlama-34B: 45.11
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CodeLlama-13B-Python: 42.89
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CodeLlama-13B: 35.07
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## lm-evaluation-harness
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```json
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{'ARC (acc_norm)': 0.6109215017064846,
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'HellaSwag (acc_norm)': 0.8358892650866361,
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'MMLU (acc)': 0.6325456394049195,
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'TruthfulQA (mc2)': 0.4746745250371087,
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'Winoground (acc)': 0.7829518547750592,
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'GSM8K (acc)': 0.467778620166793,
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'DROP (f1)': 0.49585675335570545,
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'Open LLM Score': 0.61437428571428571}
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```
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[Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
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| Metric | Value |
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| --- | --- |
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| ARC |60.58 |
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| HellaSwag |83.47 |
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| MMLU | 62.98 |
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| TruthfulQA | 47.9 |
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| Winoground | 78.69 |
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| GSM8K | 19.18 |
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| Average | 58.85 |
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## Parameters
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| | |
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|------ | ------ |
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| lr | 2e-4 |
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| lr_scheduler_type | cosine |
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| weight_decay | 0.0 |
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| optim | paged_adamw_8bit |
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| flash_attention | True |
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| rerope | False |
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| max_new_tokens | 4096 |
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| num_train_epochs | 2 |
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| bits | 4 |
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| lora_r | 64 |
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| lora_alpha | 16 |
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| lora_dropout | 0.05 |
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| double_quant | True |
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| quant_type | nf4 |
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| dataset_format | airoboros |
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| mini_batch_size | 2 |
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| grandient_accumulation_steps | 32 |
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| bf16 | True |
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A40-48G x 2
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| | |
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|------ | ------ |
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| epoch | 2.0 |
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| etrain_loss | 0.5 |
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| etrain_runtime | 1 day, 10:25:26.77 |
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| etrain_samples_per_second | 3.194 |
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| etrain_steps_per_second | 0.025 |
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| eeval_loss | 0.5146 |
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| eeval_runtime | 0:00:25.04 |
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| eeval_samples_per_second | 7.985 |
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| eeval_steps_per_second | |
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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_uukuguy__speechless-code-mistral-7b-v1.0)
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| Metric | Value |
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|-----------------------|---------------------------|
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| Avg. | 53.47 |
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| ARC (25-shot) | 60.58 |
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| HellaSwag (10-shot) | 83.75 |
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| MMLU (5-shot) | 62.98 |
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| TruthfulQA (0-shot) | 47.9 |
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| Winogrande (5-shot) | 78.69 |
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| GSM8K (5-shot) | 19.18 |
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| DROP (3-shot) | 21.19 |
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