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---
language:
- en
license: llama2
library_name: transformers
tags:
- llama-2
- code
datasets:
- jondurbin/airoboros-2.2
- Open-Orca/OpenOrca
- garage-bAInd/Open-Platypus
- WizardLM/WizardLM_evol_instruct_V2_196k
- TokenBender/python_eval_instruct_51k
pipeline_tag: text-generation
model-index:
- name: SpeechlessCoder
  results:
  - task:
      type: text-generation
    dataset:
      name: HumanEval
      type: openai_humaneval
    metrics:
    - type: pass@1
      value: 52.439
      name: pass@1
      verified: false
  - 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: 41.13
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=speechlessai/speechless-coding-7b-16k-tora
      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: 64.48
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=speechlessai/speechless-coding-7b-16k-tora
      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: 38.86
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=speechlessai/speechless-coding-7b-16k-tora
      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: 44.95
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=speechlessai/speechless-coding-7b-16k-tora
      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: 63.85
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=speechlessai/speechless-coding-7b-16k-tora
      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: 17.06
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=speechlessai/speechless-coding-7b-16k-tora
      name: Open LLM Leaderboard
---

<p><h1> speechless-coding-7b-16k-tora  </h1></p>

Use the following dataset to fine-tune llm_agents/tora-code-7b-v1.0 in order to improve the model's reasoning and planning abilities.

context window length: 16,384
prompt_type = "alpaca"
max_tokens > 128 && < 16384
>
Total 177,333 samples 316 MB
- jondurbin/airoboros-2.2: Filter categories related to coding, reasoning and planning. 21,923 samples.
- Open-Orca/OpenOrca: Filter the 'cot' category in 1M GPT4 dataset. 62,973 samples.
- garage-bAInd/Open-Platypus: 100%, 22,760 samples.
- WizardLM/WizardLM_evol_instruct_V2_196k: Coding coversation part. 30,081 samples
- TokenBender/python_eval_instruct_51k: “python” in output .39,596 samples


50 samples/T=0.2/MaxTokens=512/Top_P=0.95

Code: https://github.com/uukuguy/speechless

## HumanEval

| Metric | Value |
| --- | --- |
| humaneval-python | 52.44 |

[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

## MultiPL-E

                                                | Metric | Value |
                                                | --- | --- |
                                                | python | 55.96 |
                                                | java | 37.84 |
                                                | javascript | 46.93 |
                                                | cpp | 37.48 |
                                                | rust | 29.01 |
                                                | go | 28.99 |
                                                |  sh | 12.11 |
                                                | julia | 31.47 |
                                                | typescript | 47.80 |

## LMEval

                                                [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
                                                | Metric | Value |
                                                | --- | --- |
                                                | ARC | |
                                                | HellaSwag | |
                                                | MMLU | |
                                                | TruthfulQA |  |
                                                | Average |  |

## Parameters

                                                | | |
                                                |------ | ------ |
                                                | lr | 2e-4 |
                                                | lr_scheduler_type | cosine |
                                                | weight_decay | 0.0 |
                                                | optim | paged_adamw_8bit |
                                                | flash_attention | True |
                                                | rerope | False |
                                                | max_new_tokens | 16384 |
                                                | num_train_epochs | 2 |
                                                | bits | 4 |
                                                | lora_r | 64 |
                                                | lora_alpha | 256 |
                                                | lora_dropout | 0.05 |
                                                | double_quant | True |
                                                | quant_type | nf4 |
                                                | dataset_format | sharegpt |
                                                | mini_batch_size | 2 |
                                                | grandient_accumulation_steps | 32 |
                                                | bf16 | True |

                                                A100-40G x 4


# [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_speechlessai__speechless-coding-7b-16k-tora)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |45.05|
|AI2 Reasoning Challenge (25-Shot)|41.13|
|HellaSwag (10-Shot)              |64.48|
|MMLU (5-Shot)                    |38.86|
|TruthfulQA (0-shot)              |44.95|
|Winogrande (5-shot)              |63.85|
|GSM8k (5-shot)                   |17.06|