Adding Evaluation Results (#2)

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	---
	language:
	- tr
	- en
	license: apache-2.0
	datasets:
	- malhajar/meditron-tr
	model-index:
	- name: Mistral-7B-v0.2-meditron-turkish
	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: 59.56
	name: normalized accuracy
	source:
	url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=malhajar/Mistral-7B-v0.2-meditron-turkish
	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: 81.79
	name: normalized accuracy
	source:
	url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=malhajar/Mistral-7B-v0.2-meditron-turkish
	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: 60.35
	name: accuracy
	source:
	url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=malhajar/Mistral-7B-v0.2-meditron-turkish
	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: 66.19
	source:
	url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=malhajar/Mistral-7B-v0.2-meditron-turkish
	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: 76.24
	name: accuracy
	source:
	url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=malhajar/Mistral-7B-v0.2-meditron-turkish
	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: 35.94
	name: accuracy
	source:
	url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=malhajar/Mistral-7B-v0.2-meditron-turkish
	name: Open LLM Leaderboard
	---

	# Model Card for Model ID

	<!-- Provide a quick summary of what the model is/does. -->
	Mistral-7B-v0.2-meditron-turkish is a finetuned Mistral Model version using Freeze technique on Turkish Meditron dataset of [`malhajar/meditron-7b-tr`](https://huggingface.co/datasets/malhajar/meditron-tr) using SFT Training.
	This model can answer information about different excplicit ideas in medicine in Turkish and English

	### Model Description

	- Finetuned by: [`Mohamad Alhajar`](https://www.linkedin.com/in/muhammet-alhajar/)
	- Language(s) (NLP): Turkish,English
	- Finetuned from model: [`mistralai/Mistral-7B-Instruct-v0.2`](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2)

	### Prompt Template For Turkish Generation
	```
	### Kullancı:
	```
	### Prompt Template For English Generation
	```
	### User:
	```

	## How to Get Started with the Model

	Use the code sample provided in the original post to interact with the model.
	```python
	from transformers import AutoTokenizer,AutoModelForCausalLM

	model_id = "malhajar/Mistral-7B-v0.2-meditron-turkish"
	model = AutoModelForCausalLM.from_pretrained(model_name_or_path,
	device_map="auto",
	torch_dtype=torch.float16,
	revision="main")

	tokenizer = AutoTokenizer.from_pretrained(model_id)

	question: "Akciğer kanseri nedir?"
	# For generating a response
	prompt = '''
	### Kullancı:
	{question}
	'''
	input_ids = tokenizer(prompt, return_tensors="pt").input_ids
	output = model.generate(inputs=input_ids,max_new_tokens=512,pad_token_id=tokenizer.eos_token_id,top_k=50, do_sample=True,
	top_p=0.95)
	response = tokenizer.decode(output[0])

	print(response)
	```
	# [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_malhajar__Mistral-7B-v0.2-meditron-turkish)

	\| Metric \|Value\|
	\|---------------------------------\|----:\|
	\|Avg. \|63.34\|
	\|AI2 Reasoning Challenge (25-Shot)\|59.56\|
	\|HellaSwag (10-Shot) \|81.79\|
	\|MMLU (5-Shot) \|60.35\|
	\|TruthfulQA (0-shot) \|66.19\|
	\|Winogrande (5-shot) \|76.24\|
	\|GSM8k (5-shot) \|35.94\|