Adding Evaluation Results
#1
by
leaderboard-pr-bot
- opened
README.md
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---
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license: apache-2.0
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pipeline_tag: text-generation
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tags:
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- finetuned
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---
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# deepseek-coder-6.7b-chat-and-function-calling
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It was created by starting with the deepseek-coder-6.7b and training it on the open assistant dataset then training yhat on function calling. We have attached the wandb report in pdf form to view the training run at a glance.
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# Referrals
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Run Pod - This is who I use to train th emodels on huggingface. If you use it we both get free crdits. - <a href="https://runpod.io?ref=kilq83n1" target="_blank" style="color: #3498db; text-decoration: none; font-weight: bold;">Visit Runpod's Website!</a>
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Paypal - If you want to leave a tip, it is appecaheted. - <a href="https://paypal.me/OpenSourceTraining" target="_blank" style="color: #3498db; text-decoration: none; font-weight: bold;">Visit My Paypal!</a>
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---
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license: apache-2.0
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tags:
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- finetuned
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pipeline_tag: text-generation
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model-index:
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- name: deepseek-coder-6.7b-chat-and-function-calling
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results:
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: AI2 Reasoning Challenge (25-Shot)
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type: ai2_arc
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config: ARC-Challenge
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split: test
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args:
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num_few_shot: 25
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metrics:
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- type: acc_norm
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value: 36.09
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name: normalized accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=AIGym/deepseek-coder-6.7b-chat-and-function-calling
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: HellaSwag (10-Shot)
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type: hellaswag
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split: validation
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args:
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num_few_shot: 10
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metrics:
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- type: acc_norm
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value: 53.8
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name: normalized accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=AIGym/deepseek-coder-6.7b-chat-and-function-calling
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: MMLU (5-Shot)
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type: cais/mmlu
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config: all
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split: test
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 38.29
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name: accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=AIGym/deepseek-coder-6.7b-chat-and-function-calling
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: TruthfulQA (0-shot)
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type: truthful_qa
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config: multiple_choice
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split: validation
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args:
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num_few_shot: 0
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metrics:
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- type: mc2
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value: 42.83
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=AIGym/deepseek-coder-6.7b-chat-and-function-calling
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: Winogrande (5-shot)
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type: winogrande
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config: winogrande_xl
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split: validation
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 57.22
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name: accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=AIGym/deepseek-coder-6.7b-chat-and-function-calling
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: GSM8k (5-shot)
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type: gsm8k
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config: main
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split: test
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 17.21
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name: accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=AIGym/deepseek-coder-6.7b-chat-and-function-calling
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name: Open LLM Leaderboard
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---
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110 |
# deepseek-coder-6.7b-chat-and-function-calling
|
111 |
It was created by starting with the deepseek-coder-6.7b and training it on the open assistant dataset then training yhat on function calling. We have attached the wandb report in pdf form to view the training run at a glance.
|
|
|
119 |
# Referrals
|
120 |
Run Pod - This is who I use to train th emodels on huggingface. If you use it we both get free crdits. - <a href="https://runpod.io?ref=kilq83n1" target="_blank" style="color: #3498db; text-decoration: none; font-weight: bold;">Visit Runpod's Website!</a>
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+
Paypal - If you want to leave a tip, it is appecaheted. - <a href="https://paypal.me/OpenSourceTraining" target="_blank" style="color: #3498db; text-decoration: none; font-weight: bold;">Visit My Paypal!</a>
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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_AIGym__deepseek-coder-6.7b-chat-and-function-calling)
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| Metric |Value|
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|---------------------------------|----:|
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|Avg. |40.91|
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|AI2 Reasoning Challenge (25-Shot)|36.09|
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|HellaSwag (10-Shot) |53.80|
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|MMLU (5-Shot) |38.29|
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|TruthfulQA (0-shot) |42.83|
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|Winogrande (5-shot) |57.22|
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|GSM8k (5-shot) |17.21|
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