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---
license: mit
datasets:
- lavita/ChatDoctor-HealthCareMagic-100k
model-index:
- name: doctorLLM10k
results:
- 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: 54.95
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=vikash06/doctorLLM10k
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: 79.94
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=vikash06/doctorLLM10k
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: 44.4
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=vikash06/doctorLLM10k
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: 44.76
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=vikash06/doctorLLM10k
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: 70.01
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=vikash06/doctorLLM10k
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: 10.16
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=vikash06/doctorLLM10k
name: Open LLM Leaderboard
---
Sample Input on Postman API:
![image/png](https://cdn-uploads.huggingface.co/production/uploads/63a7d07154f1d0225b0b9d1c/1A5BfWI5QOQHa7g8ueGIS.png)
Number of epochs: 10
Number of Data points: 10000
# Creative Writing: Write a question or instruction that requires a creative medical response from a doctor.
The instruction should be reasonable to ask of a person with general medical knowledge and should not require searching.
In this task, your prompt should give very specific instructions to follow.
Constraints, instructions, guidelines, or requirements all work, and the more of them the better.
Reference dataset: https://github.com/Kent0n-Li/ChatDoctor
# [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_vikash06__doctorLLM10k)
| Metric |Value|
|---------------------------------|----:|
|Avg. |50.70|
|AI2 Reasoning Challenge (25-Shot)|54.95|
|HellaSwag (10-Shot) |79.94|
|MMLU (5-Shot) |44.40|
|TruthfulQA (0-shot) |44.76|
|Winogrande (5-shot) |70.01|
|GSM8k (5-shot) |10.16|
|