README.md

---
language:
- en
license: apache-2.0
base_model: Locutusque/TinyMistral-248M
datasets:
- HuggingFaceH4/ultrachat_200k
- Felladrin/ChatML-ultrachat_200k
- Open-Orca/OpenOrca
- Felladrin/ChatML-OpenOrca
- hkust-nlp/deita-10k-v0
- Felladrin/ChatML-deita-10k-v0
- LDJnr/Capybara
- Felladrin/ChatML-Capybara
- databricks/databricks-dolly-15k
- Felladrin/ChatML-databricks-dolly-15k
- euclaise/reddit-instruct-curated
- Felladrin/ChatML-reddit-instruct-curated
- CohereForAI/aya_dataset
- Felladrin/ChatML-aya_dataset
pipeline_tag: text-generation
widget:
- messages:
  - role: system
    content: You are a highly knowledgeable and friendly assistant. Your goal is to
      understand and respond to user inquiries with clarity. Your interactions are
      always respectful, helpful, and focused on delivering the most accurate information
      to the user.
  - role: user
    content: Hey! Got a question for you!
  - role: assistant
    content: Sure! What's it?
  - role: user
    content: What are some potential applications for quantum computing?
- messages:
  - role: user
    content: Heya!
  - role: assistant
    content: Hi! How may I help you?
  - role: user
    content: I'm interested in developing a career in software engineering. What would
      you recommend me to do?
- messages:
  - role: user
    content: Morning!
  - role: assistant
    content: Good morning! How can I help you today?
  - role: user
    content: Could you give me some tips for becoming a healthier person?
- messages:
  - role: system
    content: You are a very creative assistant. User will give you a task, which you
      should complete with all your knowledge.
  - role: user
    content: Hello! Can you please elaborate a background story of an RPG game about
      wizards and dragons in a sci-fi world?
inference:
  parameters:
    max_new_tokens: 250
    penalty_alpha: 0.5
    top_k: 5
model-index:
- name: TinyMistral-248M-Chat-v2
  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: 23.29
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Felladrin/TinyMistral-248M-Chat-v2
      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: 27.39
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Felladrin/TinyMistral-248M-Chat-v2
      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: 23.52
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Felladrin/TinyMistral-248M-Chat-v2
      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: 41.32
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Felladrin/TinyMistral-248M-Chat-v2
      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: 49.01
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Felladrin/TinyMistral-248M-Chat-v2
      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: 0.0
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Felladrin/TinyMistral-248M-Chat-v2
      name: Open LLM Leaderboard
---

# Locutusque's TinyMistral-248M trained on chat datasets

- Base model: [Locutusque/TinyMistral-248M](https://huggingface.co/Locutusque/TinyMistral-248M) with two additional special tokens (`<|im_start|>` and `<|im_end|>`)
- Datasets:
  - [[ChatML](https://huggingface.co/datasets/Felladrin/ChatML-ultrachat_200k)] [HuggingFaceH4/ultrachat_200k](https://huggingface.co/datasets/HuggingFaceH4/ultrachat_200k)
  - [[ChatML](https://huggingface.co/datasets/Felladrin/ChatML-OpenOrca)] [Open-Orca/OpenOrca](https://huggingface.co/datasets/Open-Orca/OpenOrca)
  - [[ChatML](https://huggingface.co/datasets/Felladrin/ChatML-deita-10k-v0)] [hkust-nlp/deita-10k-v0](https://huggingface.co/datasets/hkust-nlp/deita-10k-v0)
  - [[ChatML](https://huggingface.co/datasets/Felladrin/ChatML-Capybara)] [LDJnr/Capybara](https://huggingface.co/datasets/LDJnr/Capybara)
  - [[ChatML](https://huggingface.co/datasets/Felladrin/ChatML-databricks-dolly-15k)] [databricks/databricks-dolly-15k](https://huggingface.co/datasets/databricks/databricks-dolly-15k)
  - [[ChatML](https://huggingface.co/datasets/Felladrin/ChatML-reddit-instruct-curated)] [euclaise/reddit-instruct-curated](https://huggingface.co/datasets/euclaise/reddit-instruct-curated)
  - [[ChatML](https://huggingface.co/datasets/Felladrin/ChatML-aya_dataset)] [CohereForAI/aya_dataset](https://huggingface.co/datasets/CohereForAI/aya_dataset)
- License: [Apache License 2.0](https://huggingface.co/Felladrin/TinyMistral-248M-Chat-v2/resolve/main/license.txt)
- Availability in other ML formats:
  - GGUF: [Felladrin/gguf-TinyMistral-248M-Chat-v2](https://huggingface.co/Felladrin/gguf-TinyMistral-248M-Chat-v2)
  - ONNX: [Felladrin/onnx-TinyMistral-248M-Chat-v2](https://huggingface.co/Felladrin/onnx-TinyMistral-248M-Chat-v2)

## Recommended Prompt Format

```
<|im_start|>system
{system_message}<|im_end|>
<|im_start|>user
{user_message}<|im_end|>
<|im_start|>assistant
```

## Recommended Inference Parameters

```yml
penalty_alpha: 0.5
top_k: 5
```

## Usage Example

```python
from transformers import pipeline

generate = pipeline("text-generation", "Felladrin/TinyMistral-248M-Chat-v2")

messages = [
    {
        "role": "system",
        "content": "You are a highly knowledgeable and friendly assistant. Your goal is to understand and respond to user inquiries with clarity. Your interactions are always respectful, helpful, and focused on delivering the most accurate information to the user.",
    },
    {
        "role": "user",
        "content": "Hey! Got a question for you!",
    },
    {
        "role": "assistant",
        "content": "Sure! What's it?",
    },
    {
        "role": "user",
        "content": "What are some potential applications for quantum computing?",
    },
]

prompt = generate.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)

output = generate(
    prompt,
    max_new_tokens=256,
    penalty_alpha=0.5,
    top_k=5,
)

print(output[0]["generated_text"])
```

## How it was trained

This model was trained with [SFTTrainer](https://huggingface.co/docs/trl/main/en/sft_trainer) using the following settings:

| Hyperparameter         | Value                                         |
| :--------------------- | :-------------------------------------------- |
| Learning rate          | 2e-5                                          |
| Total train batch size | 32                                            |
| Max. sequence length   | 2048                                          |
| Weight decay           | 0.01                                          |
| Warmup ratio           | 0.1                                           |
| NEFTune Noise Alpha    | 5                                             |
| Optimizer              | Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| Scheduler              | cosine                                        |
| Seed                   | 42                                            |

## [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_Felladrin__TinyMistral-248M-Chat-v2)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |27.42|
|AI2 Reasoning Challenge (25-Shot)|23.29|
|HellaSwag (10-Shot)              |27.39|
|MMLU (5-Shot)                    |23.52|
|TruthfulQA (0-shot)              |41.32|
|Winogrande (5-shot)              |49.01|
|GSM8k (5-shot)                   | 0.00|