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Model: aari1995/germeo-7b-laser Source: Original Platform
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README.md
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---
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language:
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- de
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license: apache-2.0
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tags:
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- hermeo
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- laser
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datasets:
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- LeoLM/OpenSchnabeltier
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pipeline_tag: conversational
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model-index:
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- name: germeo-7b-laser
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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: 60.75
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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=aari1995/germeo-7b-laser
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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: 82.81
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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=aari1995/germeo-7b-laser
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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: 60.57
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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=aari1995/germeo-7b-laser
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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: 53.83
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=aari1995/germeo-7b-laser
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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: 75.61
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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=aari1995/germeo-7b-laser
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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: 43.37
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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=aari1995/germeo-7b-laser
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name: Open LLM Leaderboard
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---
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(Evaluation WIP)
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## Hermes + Leo + German Laser = Germeo
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## Germeo-7B-Laser
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A German-English understanding, but German-only speaking model merged from Hermeo-7B.
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### Model details
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**Merged from**: leo-mistral-hessianai-7b-chat and DPOpenHermes-7B-v2
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**Model type**: Causal decoder-only transformer language model
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**Languages**: German replies with English Understanding Capabilities
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**Laser-Data**: LeoLM/OpenSchnabeltier
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This is an early experiment on laser and its influence on language understanding. It generally improves the language understanding capabilities.
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The hypothesis is that it degrades the probability of English replies and increasing those of German replies. The models internal German capabilities are boosted.
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Will keep you updated..
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### Acknowledgements:
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I would like to thank everyone that participated in making this model and its training possible:
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To [@malteos](https://huggingface.co/malteos) for hermeo
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To [@cognitivecomputations](https://huggingface.co/cognitivecomputations) and Fernando Fernandes Neto for their implementation of LASER
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To [@LeoLM](https://huggingface.co/LeoLM) and Björn for the OpenSchnabeltier dataset.
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### Prompt format:
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```python
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streamer = TextStreamer(tokenizer, skip_prompt=True, skip_special_tokens=True)
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# Convert prompt to tokens
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prompt_template = """<|im_start|>system
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Du bist ein hilfreicher Assistent.<|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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prompt = "Schreibe eine Stellenanzeige für Data Scientist bei AXA!"
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final_prompt = prompt_template.format(prompt=prompt)
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```
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#### Limit the model to output reply-only:
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To solve this, you need to implement a custom stopping criteria:
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```python
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from transformers import StoppingCriteria
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class GermeoStoppingCriteria(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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# Get the generated text as a string
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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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# Check if the target sequence appears in the generated text
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if self.target_sequence in generated_text:
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return True # Stop generation
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return False # Continue generation
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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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```
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This then expects your input prompt (formatted as given into the model), and a stopping criteria, in this case the im_end token. Simply add it to the generation:
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```python
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generation_output = model.generate(
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tokens,
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streamer=streamer,
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max_new_tokens=1012,
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stopping_criteria=GermeoStoppingCriteria("<|im_end|>", prompt_template.format(prompt=prompt))
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)
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```
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### German benchmarks
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| **German tasks:** | **MMLU-DE** | **Hellaswag-DE** | **ARC-DE** |**Average** |
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|-------------------------------|-------------|---------------|--------------|--------------|
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| **Models / Few-shots:** | _(5 shots)_ | _(10 shots)_ | _(24 shots)_ | |
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| _7B parameters_ | | | | |
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| llama-2-7b | 0.400 | 0.513 | 0.381 | 0.431 |
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| leo-hessianai-7b | 0.400 | 0.609 | 0.429 | 0.479 |
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| bloom-6b4-clp-german | 0.274 | 0.550 | 0.351 | 0.392 |
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| mistral-7b | **0.524** | 0.588 | 0.473 | 0.528 |
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| leo-mistral-hessianai-7b | 0.481 | 0.663 | 0.485 | 0.543 |
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| leo-mistral-hessianai-7b-chat | 0.458 | 0.617 | 0.465 | 0.513 |
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| DPOpenHermes-7B-v2 | 0.517 | 0.603 | 0.515 | 0.545 |
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| hermeo-7b | 0.511 | **0.668** | **0.528** | **0.569** |
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| **germeo-7b-laser (this model)**| ? | ? | ? | ? |
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| _13B parameters_ | | | | |
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| llama-2-13b | 0.469 | 0.581 | 0.468 | 0.506 |
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| leo-hessianai-13b | **0.486** | **0.658** | **0.509** | **0.551** |
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| _70B parameters_ | | | | |
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| llama-2-70b | 0.597 | 0.674 | 0.561 | 0.611 |
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| leo-hessianai-70b | **0.653** | **0.721** | **0.600** | **0.658** |
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Even though the model does not generate English text without being explicitly asked, performance on English Benchmarks is still up:
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### English benchmarks
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| **English tasks:** | **MMLU** | **Hellaswag** | **ARC** | **Average** |
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|------------------------------------|-------------|---------------|--------------|-------------|
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| **Models / Few-shots:** | _(5 shots)_ | _(10 shots)_ | _(24 shots)_ | |
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| llama-2-7b | 0.466 | 0.786 | 0.530 | 0.594 |
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| leolm-hessianai-7b | 0.423 | 0.759 | 0.522 | 0.568 |
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| bloom-6b4-clp-german | 0.264 | 0.525 | 0.328 | 0.372 |
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| mistral-7b | **0.635** | **0.832** | 0.607 | **0.691** |
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| leolm-mistral-hessianai-7b | 0.550 | 0.777 | 0.518 | 0.615 |
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| hermeo-7b | 0.601 | 0.821 | **0.620** | 0.681 |
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| germeo-7b-laser (this model) | 0.601 | 0.828 | 0.608 | 0.679 |
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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_aari1995__germeo-7b-laser)
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| Metric |Value|
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|---------------------------------|----:|
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|Avg. |62.82|
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|AI2 Reasoning Challenge (25-Shot)|60.75|
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|HellaSwag (10-Shot) |82.81|
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|MMLU (5-Shot) |60.57|
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|TruthfulQA (0-shot) |53.83|
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|Winogrande (5-shot) |75.61|
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|GSM8k (5-shot) |43.37|
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config.json
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{
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"_name_or_path": "malteos/hermeo-7b",
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"architectures": [
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"MistralForCausalLM"
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],
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"attention_dropout": 0.0,
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"bos_token_id": 1,
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"eos_token_id": 2,
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"hidden_act": "silu",
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"hidden_size": 4096,
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"initializer_range": 0.02,
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"intermediate_size": 14336,
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"max_position_embeddings": 32768,
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"model_type": "mistral",
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"num_attention_heads": 32,
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"num_hidden_layers": 32,
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"num_key_value_heads": 8,
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"rms_norm_eps": 1e-05,
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"rope_theta": 10000.0,
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"sliding_window": 4096,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.36.2",
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"use_cache": true,
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"vocab_size": 32002
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}
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||||
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||||
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||||
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||||
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|
||||
"model.norm.weight": "model-00003-of-00003.safetensors"
|
||||
}
|
||||
}
|
||||
23
special_tokens_map.json
Normal file
23
special_tokens_map.json
Normal file
@@ -0,0 +1,23 @@
|
||||
{
|
||||
"bos_token": {
|
||||
"content": "<s>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"eos_token": {
|
||||
"content": "</s>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"unk_token": {
|
||||
"content": "<unk>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
91122
tokenizer.json
Normal file
91122
tokenizer.json
Normal file
File diff suppressed because it is too large
Load Diff
BIN
tokenizer.model
(Stored with Git LFS)
Normal file
BIN
tokenizer.model
(Stored with Git LFS)
Normal file
Binary file not shown.
43
tokenizer_config.json
Normal file
43
tokenizer_config.json
Normal file
@@ -0,0 +1,43 @@
|
||||
{
|
||||
"add_bos_token": true,
|
||||
"add_eos_token": false,
|
||||
"added_tokens_decoder": {
|
||||
"0": {
|
||||
"content": "<unk>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"1": {
|
||||
"content": "<s>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"2": {
|
||||
"content": "</s>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
}
|
||||
},
|
||||
"additional_special_tokens": [],
|
||||
"bos_token": "<s>",
|
||||
"chat_template": "{% for message in messages %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}",
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "</s>",
|
||||
"legacy": true,
|
||||
"model_max_length": 1000000000000000019884624838656,
|
||||
"pad_token": null,
|
||||
"sp_model_kwargs": {},
|
||||
"spaces_between_special_tokens": false,
|
||||
"tokenizer_class": "LlamaTokenizer",
|
||||
"unk_token": "<unk>",
|
||||
"use_default_system_prompt": false
|
||||
}
|
||||
Reference in New Issue
Block a user