---
license: mit
datasets:
- iamplus/LLama2-SFT-Data
- iamplus/Open_Platypus_Orca
- iamplus/Orca
- iamplus/Conversational_Data
---


**Description :**

This model is trained on a mix of Orca data and Open Source + Closed Multi-turn Conversation data to create a better reasoning model which is capable of holding multi-turn conversations as well.

The Dataset split description, Prompt description as well as Training Parameters are given below.

**Prompt Description :** 

The prompt template for the first turn looks like this:
```
<s>[INST] <<SYS>>
{{ system_prompt }}
<</SYS>>

{{ user_message }} [/INST]
```

The prompt template for the multi-turn conversation looks like this:
```
<s>[INST] <<SYS>>
{{ system_prompt }}
<</SYS>>

{{ user_msg_1 }} [/INST] {{ model_answer_1 }} </s><s>[INST] {{ user_msg_2 }} [/INST]
```

This model follows the official Meta's chat model Prompt format. Please refer here : https://huggingface.co/blog/llama2#how-to-prompt-llama-2 on how to prompt the model for single/multi-turn conversations.

**Base model :** meta-llama/Llama-2-70b-hf

**Data :** 
1. 1M Orca dara (Gpt-4 Orca data - OpenOrca)
2. 1.7M chat data (includes OpenAssistant Chat data, Ultrachat, and many more open source Chat Datasets)
3. 30k OpenPlatypus data

**Training Params :**
```
Number of Epochs : 1
Batch Size : 64
Sequence Length : 4096
Learning Rate : 2e-5 (Cosine)
Weight Decay : 0.1
Gradient Clipping : 1.0
Gamma : 0.85
beta_1 : 0.9
beta_2 : 0.95
eps : 1e-5
Precision : bf16
Optimizer : Any Precision AdamW Optimizer
```