README.md

---
language:
- de
license: apache-2.0
tags:
- hermeo
- laser
datasets:
- LeoLM/OpenSchnabeltier
pipeline_tag: conversational
model-index:
- name: germeo-7b-laser
  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: 60.75
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=aari1995/germeo-7b-laser
      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: 82.81
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=aari1995/germeo-7b-laser
      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: 60.57
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=aari1995/germeo-7b-laser
      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: 53.83
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=aari1995/germeo-7b-laser
      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: 75.61
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=aari1995/germeo-7b-laser
      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: 43.37
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=aari1995/germeo-7b-laser
      name: Open LLM Leaderboard
---

(Evaluation WIP)

## Hermes + Leo + German Laser = Germeo

## Germeo-7B-Laser
A German-English understanding, but German-only speaking model merged from Hermeo-7B.

### Model details

**Merged from**: leo-mistral-hessianai-7b-chat and DPOpenHermes-7B-v2

**Model type**: Causal decoder-only transformer language model

**Languages**: German replies with English Understanding Capabilities

**Laser-Data**: LeoLM/OpenSchnabeltier


This is an early experiment on laser and its influence on language understanding. It generally improves the language understanding capabilities.
The hypothesis is that it degrades the probability of English replies and increasing those of German replies. The models internal German capabilities are boosted. 

Will keep you updated..

### Acknowledgements:

I would like to thank everyone that participated in making this model and its training possible:
To [@malteos](https://huggingface.co/malteos) for hermeo
To [@cognitivecomputations](https://huggingface.co/cognitivecomputations) and Fernando Fernandes Neto for their implementation of LASER
To [@LeoLM](https://huggingface.co/LeoLM) and Björn for the OpenSchnabeltier dataset.


### Prompt format:

```python
streamer = TextStreamer(tokenizer, skip_prompt=True, skip_special_tokens=True)
# Convert prompt to tokens
prompt_template = """<|im_start|>system
Du bist ein hilfreicher Assistent.<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant"""

prompt = "Schreibe eine Stellenanzeige für Data Scientist bei AXA!"

final_prompt = prompt_template.format(prompt=prompt)
```

### German benchmarks

| **German tasks:**             | **MMLU-DE**    | **Hellaswag-DE** | **ARC-DE**      |**Average**      |
|-------------------------------|-------------|---------------|--------------|--------------|
| **Models / Few-shots:**       | _(5 shots)_ | _(10 shots)_  | _(24 shots)_ | |
| _7B parameters_      |  | |  | |
| llama-2-7b                    | 0.400       | 0.513         | 0.381        | 0.431  |
| leo-hessianai-7b              | 0.400       | 0.609         | 0.429        | 0.479 |
| bloom-6b4-clp-german          | 0.274       | 0.550         | 0.351        | 0.392 |
| mistral-7b                    | **0.524**       | 0.588         | 0.473        | 0.528 |
| leo-mistral-hessianai-7b      | 0.481       | 0.663         | 0.485        | 0.543 |
| leo-mistral-hessianai-7b-chat | 0.458       | 0.617         | 0.465        | 0.513 |
| DPOpenHermes-7B-v2            | 0.517         | 0.603         | 0.515        | 0.545 |
| hermeo-7b                     | 0.511       | **0.668**         | **0.528**        | **0.569** |
| **germeo-7b-laser (this model)**| ?       | ?        | ?      | ? |
| _13B parameters_      |  | |  | |
| llama-2-13b                    | 0.469       | 0.581        | 0.468        | 0.506 |
| leo-hessianai-13b              | **0.486**       | **0.658**         | **0.509**       | **0.551** |
| _70B parameters_      |  | |  | |
| llama-2-70b                    | 0.597       | 0.674       | 0.561       | 0.611 |
| leo-hessianai-70b              | **0.653**       | **0.721**         | **0.600**       | **0.658** |


Even though the model does not generate English text without being explicitly asked, performance on English Benchmarks is still up:

### English benchmarks

| **English tasks:**                 | **MMLU**    | **Hellaswag** | **ARC**      | **Average** |
|------------------------------------|-------------|---------------|--------------|-------------|
| **Models / Few-shots:**            | _(5 shots)_ | _(10 shots)_  | _(24 shots)_ |             |
| llama-2-7b                         |       0.466 |         0.786 |        0.530 |       0.594 |
| leolm-hessianai-7b                 |       0.423 |         0.759 |        0.522 |       0.568 |
| bloom-6b4-clp-german               |       0.264 |         0.525 |        0.328 |       0.372 |
| mistral-7b                         |   **0.635** |     **0.832** |        0.607 |   **0.691** |
| leolm-mistral-hessianai-7b         |       0.550 |         0.777 |        0.518 |       0.615 |
| hermeo-7b                          |       0.601 |         0.821 |    **0.620** |       0.681 |
| germeo-7b-laser (this model)       |       0.601 |         0.828 |        0.608 |       0.679 |
# [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_aari1995__germeo-7b-laser)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |62.82|
|AI2 Reasoning Challenge (25-Shot)|60.75|
|HellaSwag (10-Shot)              |82.81|
|MMLU (5-Shot)                    |60.57|
|TruthfulQA (0-shot)              |53.83|
|Winogrande (5-shot)              |75.61|
|GSM8k (5-shot)                   |43.37|