---
license: apache-2.0
datasets:
- Mihaiii/OpenHermes-2.5-1k-longest-curated
metrics:
- accuracy
base_model: migtissera/Tess-10.7B-v1.5b
inference: false
model-index:
- name: Bucharest-0.2
  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: 64.59
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Mihaiii/Bucharest-0.2
      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: 84.87
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Mihaiii/Bucharest-0.2
      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: 66.03
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Mihaiii/Bucharest-0.2
      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: 45.3
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Mihaiii/Bucharest-0.2
      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: 83.27
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Mihaiii/Bucharest-0.2
      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: 56.79
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Mihaiii/Bucharest-0.2
      name: Open LLM Leaderboard
---

[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)

The Bucharest series is mostly an experiment. Use Pallas series instead.

An instruct based fine tune of [migtissera/Tess-10.7B-v1.5b](https://huggingface.co/migtissera/Tess-10.7B-v1.5b).

This model is trained on a private dataset + [Mihaiii/OpenHermes-2.5-1k-longest-curated](https://huggingface.co/datasets/Mihaiii/OpenHermes-2.5-1k-longest-curated), which is a subset of [HuggingFaceH4/OpenHermes-2.5-1k-longest](https://huggingface.co/datasets/HuggingFaceH4/OpenHermes-2.5-1k-longest), which is a subset of [teknium/OpenHermes-2.5](https://huggingface.co/datasets/teknium/OpenHermes-2.5).

# Prompt Format:

```
SYSTEM: <ANY SYSTEM CONTEXT>
USER: 
ASSISTANT:
```

GGUF:

[tsunemoto/Bucharest-0.2-GGUF](https://huggingface.co/tsunemoto/Bucharest-0.2-GGUF)
# [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_Mihaiii__Bucharest-0.2)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |66.81|
|AI2 Reasoning Challenge (25-Shot)|64.59|
|HellaSwag (10-Shot)              |84.87|
|MMLU (5-Shot)                    |66.03|
|TruthfulQA (0-shot)              |45.30|
|Winogrande (5-shot)              |83.27|
|GSM8k (5-shot)                   |56.79|