README.md

---
license: apache-2.0
---
<h1>
<a alt="Ask2Democracy project" href="https://github.com/jorge-henao/ask2democracy">Ask2Democracy project</a>
</h1>
<hr>

## What's baizemocracy-lora-7B-cfqa-conv model?

This model is an open-source chat model fine-tuned with [LoRA](https://github.com/microsoft/LoRA) inspired by [Baize project](https://github.com/project-baize/baize-chatbot/tree/main/). It was trained with the Baize datasets and the ask2democracy-cfqa-salud-pension dataset, wich contains almost 4k instructions to answers questions based on a context relevant to citizen concerns and public debate in spanish.
Two major experiments models was performed during the Hackathon Somos NLP 2023: 
- A conversational style focused model
- A contex focused style model.
  
This model is focused in a more conversational way of asking questions. See Pre-proccessing dataset section.
There is other model variation more focused on augmented retrieval based on context [Baizemocracy-contextfocused](https://github.com/project-baize/baize-chatbot/tree/main/).

Testing is a work in progress, we decide to share both model variations with community in order to invovle more people experimenting what it works better and find other possible use cases.


- **Developed by:**
- 🇨🇴 [Jorge Henao](https://huggingface.co/jorge-henao)
- 🇨🇴 [David Torres ](https://github.com/datorresb)

## Training Parameters

- Base Model: [LLaMA-7B](https://arxiv.org/pdf/2302.13971.pdf)
- Training Epoch: 1
- Batch Size: 16
- Maximum Input Length: 512
- Learning Rate: 2e-4
- LoRA Rank: 8
- Updated Modules: All Linears

## Training Dataset

- [Ask2Democracy-cfqa-salud-pension](https://huggingface.co/datasets/hackathon-somos-nlp-2023/ask2democracy-cfqa-salud-pension) (3,806)
- [Standford Alpaca](https://github.com/tatsu-lab/stanford_alpaca) (51,942)
- [Quora Dialogs](https://github.com/project-baize/baize) (54,456):
- [StackOverflow Dialogs](https://github.com/project-baize/baize) (57,046)
- [Alpacaca chat Dialogs](https://github.com/project-baize/baize)
- [Medical chat Dialogs](https://github.com/project-baize/baize)

## About pre-processing

Ask2Democracy-cfqa-salud-pension dataset was pre-processed in a conversational style in two variations like this:
```python

def format_instruction_without_context(example):
  example["topic"] = example['input']
  input = "La conversación entre un humano y un asistente de IA."
  input += "\n[|Human|] "+example['input']
  input += "\n[|AI|] "+example["output"]
  if len(example["topics"])>0:
    topics = ", ".join(example["topics"])
    input += "\n[|Human|] "+"¿En cuáles tópicos clasificarías su respuesta?"
    input += "\n[|AI|] "+f"Aquí una lista de tópicos: {topics}."
    example["topic"] += f" ({topics})"
  example["input"] = input
  return example`

def format_instruction_with_context(example):
  example["topic"] = example['input']
  context = example['instruction'].replace("Given the context please answer the question. Context:","")
  context = ' '.join(context.strip().split())[1:-3]
  input = "La conversación entre un humano y un asistente de IA."
  input += "\n[|Human|] "+example['input']+f"\nPara responder la pregunta, usa el siguiente contexto:\n{context}"
  input += "\n[|AI|] "+example["output"]
  if len(example["topics"])>0:
    topics = ", ".join(example["topics"])
    input += "\n[|Human|] "+"¿En cuáles tópicos clasificarías su respuesta?"
    input += "\n[|AI|] "+f"Aquí una lista de tópicos: {topics}."
    example["topic"] += f" ({topics})"
  example["input"] = input
  return example

```




More details can be found in the Ask2Democracy [GitHub](https://github.com/jorge-henao/ask2democracy)