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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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- llama-2 |
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- code |
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license: llama2 |
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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: 50.0 |
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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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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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## HumanEval |
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| Metric | Value | |
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| --- | --- | |
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| humaneval-python | 50.0| |
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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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[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 |59.64 | |
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| HellaSwag |82.25 | |
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| MMLU | 61.33 | |
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| TruthfulQA | 48.45 | |
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| Average | 62.92 | |
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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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