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Model: aloobun/Reyna-Mini-1.8B-v0.2 Source: Original Platform
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README.md
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---
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license: other
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library_name: transformers
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tags:
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- chatml
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- finetune
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- gpt4
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- synthetic data
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- custom_code
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- qwen2
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datasets:
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- Locutusque/Hercules-v3.0
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license_name: tongyi-qianwen-research
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license_link: https://huggingface.co/Qwen/Qwen1.5-1.8B-Chat/raw/main/LICENSE
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model-index:
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- name: Reyna-Mini-1.8B-v0.2
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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: 36.6
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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=aloobun/Reyna-Mini-1.8B-v0.2
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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: 60.19
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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=aloobun/Reyna-Mini-1.8B-v0.2
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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: 44.75
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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=aloobun/Reyna-Mini-1.8B-v0.2
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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: 41.24
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=aloobun/Reyna-Mini-1.8B-v0.2
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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: 61.56
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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=aloobun/Reyna-Mini-1.8B-v0.2
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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: 31.31
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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=aloobun/Reyna-Mini-1.8B-v0.2
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name: Open LLM Leaderboard
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---
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- Finetuned [Qwen/Qwen1.5-1.8B-Chat](https://huggingface.co/Qwen/Qwen1.5-1.8B-Chat), with SFT on Hercules v3 dataset.
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- This marks the third model in this series.
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- Format: ChatML -
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```
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<|im_start|>system
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{system}<|im_end|>
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<|im_start|>user
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{prompt}<|im_end|>
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<|im_start|>assistant
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```
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- Next step would be to do a DPO train on top.
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## Benchamrks:
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|Avg. | Arc | HellaSwag | MMLU | TruthfulQA | Winogrande | GSM8K |
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|---|---|---|---|---|---|---|
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|45.94 | 36.6 |60.19 | 44.75 | 41.24 | 61.56 | 31.31 |
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## Example:
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```
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from transformers import AutoModelForCausalLM, AutoTokenizer, TextStreamer, StoppingCriteria
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import torch
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class MyStoppingCriteria(StoppingCriteria):
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def __init__(self, target_sequence, prompt):
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self.target_sequence = target_sequence
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self.prompt=prompt
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def __call__(self, input_ids, scores, **kwargs):
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generated_text = tokenizer.decode(input_ids[0])
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generated_text = generated_text.replace(self.prompt,'')
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if self.target_sequence in generated_text:
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return True
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return False
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def __len__(self):
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return 1
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def __iter__(self):
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yield self
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modelpath="aloobun/Reyna-Mini-1.8B-v0.2"
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model = AutoModelForCausalLM.from_pretrained(
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modelpath,
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torch_dtype=torch.bfloat16,
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device_map="cuda",
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trust_remote_code=True,
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)
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tokenizer = AutoTokenizer.from_pretrained(
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modelpath,
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trust_remote_code=True,
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use_fast=False,
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)
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prompt = "<|im_start|>system\nYou are a helpful assistant.<|im_end|>\n<|im_start|>user\nIs there inherent order in nature or is it all chaos and chance?<|im_end|>\n<|im_start|>assistant\n"
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encoded_input = tokenizer(prompt, return_tensors='pt')
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input_ids=encoded_input['input_ids'].cuda()
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streamer = TextStreamer(tokenizer=tokenizer, skip_prompt=True)
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op = model.generate(
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input_ids,
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streamer=streamer,
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pad_token_id=tokenizer.eos_token_id,
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do_sample=True,
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temperature=0.6,
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top_p=0.8,
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max_new_tokens=512,
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stopping_criteria=MyStoppingCriteria("<|im_end|>", prompt)
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)
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```
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## Output:
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>Nature appears to be inherently organized, with patterns and structures that can be observed across different levels of organization. However, the exact mechanisms by which these patterns emerge and evolve remain largely unknown.
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>The universe seems to be governed by a series of laws and principles known as "laws of physics," such as Newton's laws of motion, electromagnetism, and thermodynamics. These laws govern how matter and energy interact with each other and how they behave over time.
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>Despite our understanding of these laws, we still struggle to comprehend the underlying mechanisms that allow for the emergence of complex patterns and structures. This is because the universe operates on a scale that is too small for us to observe directly, and therefore we cannot fully understand its internal workings.
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>In summary, while there may be some level of order and structure within the universe, the precise mechanisms governing this order remain largely unknown.<|im_end|>
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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_aloobun__Reyna-Mini-1.8B-v0.2)
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| Metric |Value|
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|---------------------------------|----:|
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|Avg. |45.94|
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|AI2 Reasoning Challenge (25-Shot)|36.60|
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|HellaSwag (10-Shot) |60.19|
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|MMLU (5-Shot) |44.75|
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|TruthfulQA (0-shot) |41.24|
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|Winogrande (5-shot) |61.56|
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|GSM8k (5-shot) |31.31|
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config.json
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{
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"_name_or_path": "Qwen/Qwen1.5-1.8B-Chat",
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"architectures": [
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"Qwen2ForCausalLM"
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],
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"attention_dropout": 0.0,
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"bos_token_id": 151643,
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"eos_token_id": 151645,
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"hidden_act": "silu",
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"hidden_size": 2048,
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"initializer_range": 0.02,
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"intermediate_size": 5504,
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"max_position_embeddings": 32768,
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"max_window_layers": 21,
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"model_type": "qwen2",
|
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"num_attention_heads": 16,
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"num_hidden_layers": 24,
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"num_key_value_heads": 16,
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"rms_norm_eps": 1e-06,
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"rope_theta": 1000000.0,
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"sliding_window": 32768,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.37.0",
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"use_cache": true,
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"use_sliding_window": false,
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"vocab_size": 151936
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}
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"top_p": 0.8,
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|
||||
"model.norm.weight": "model-00002-of-00002.safetensors"
|
||||
}
|
||||
}
|
||||
20
special_tokens_map.json
Normal file
20
special_tokens_map.json
Normal file
@@ -0,0 +1,20 @@
|
||||
{
|
||||
"additional_special_tokens": [
|
||||
"<|im_start|>",
|
||||
"<|im_end|>"
|
||||
],
|
||||
"eos_token": {
|
||||
"content": "<|im_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"pad_token": {
|
||||
"content": "<|endoftext|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
303125
tokenizer.json
Normal file
303125
tokenizer.json
Normal file
File diff suppressed because it is too large
Load Diff
43
tokenizer_config.json
Normal file
43
tokenizer_config.json
Normal file
@@ -0,0 +1,43 @@
|
||||
{
|
||||
"add_prefix_space": false,
|
||||
"added_tokens_decoder": {
|
||||
"151643": {
|
||||
"content": "<|endoftext|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151644": {
|
||||
"content": "<|im_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151645": {
|
||||
"content": "<|im_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
}
|
||||
},
|
||||
"additional_special_tokens": [
|
||||
"<|im_start|>",
|
||||
"<|im_end|>"
|
||||
],
|
||||
"bos_token": null,
|
||||
"chat_template": "{% for message in messages %}{% if loop.first and messages[0]['role'] != 'system' %}{{ '<|im_start|>system\nYou are a helpful assistant<|im_end|>\n' }}{% endif %}{{'<|im_start|>' + message['role'] + '\n' + message['content']}}{% if (loop.last and add_generation_prompt) or not loop.last %}{{ '<|im_end|>' + '\n'}}{% endif %}{% endfor %}{% if add_generation_prompt and messages[-1]['role'] != 'assistant' %}{{ '<|im_start|>assistant\n' }}{% endif %}",
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "<|im_end|>",
|
||||
"errors": "replace",
|
||||
"model_max_length": 32768,
|
||||
"pad_token": "<|endoftext|>",
|
||||
"split_special_tokens": false,
|
||||
"tokenizer_class": "Qwen2Tokenizer",
|
||||
"unk_token": null
|
||||
}
|
||||
1
vocab.json
Normal file
1
vocab.json
Normal file
File diff suppressed because one or more lines are too long
Reference in New Issue
Block a user