README.md

---
datasets:
- Anthropic/hh-rlhf
- ehartford/dolphin
- conceptofmind/t0_submix_original
- conceptofmind/niv2_submix_original
language:
- en
pipeline_tag: text-generation
---
# Mac Llama 13B

## Model Description

`Mac Llama 13B` is a Experimental Llama2 13B model finetuned on an Orca style Dataset

## Usage

Mac Llama 13B should be used with this prompt format:
```
### System:
This is a system prompt, please behave and help the user.
### User:
Your prompt here
### Assistant
The output of Stable Beluga 13B
```

## Model Details

* **Model type**: Mac Llama 13B is an auto-regressive language model fine-tuned on Llama2 13B.
* **Language(s)**: English
* **Library**: [HuggingFace Transformers](https://github.com/huggingface/transformers)
* **Contact**: For questions and comments about the model, please email `[email protected]`


### Training Procedure

Models are learned via supervised fine-tuning on the aforementioned datasets, trained in mixed-precision (BF16), and optimized with AdamW. We outline the following hyperparameters:

| Dataset           | Batch Size | Learning Rate |Learning Rate Decay| Warm-up | Weight Decay | Betas       |
|-------------------|------------|---------------|-------------------|---------|--------------|-------------|
| Orca pt1 packed   | 256        | 3e-5          | Cosine to 3e-6    | 100     | 1e-6         | (0.9, 0.95) |

## Ethical Considerations and Limitations

This is a new technology that carries risks with use. Testing conducted to date has been in English, and has not covered, nor could it cover all scenarios. For these reasons, as with all LLMs, This models potential outputs cannot be predicted in advance, and the model may in some instances produce inaccurate, biased or other objectionable responses to user prompts. Therefore, before deploying any applications using this, developers should perform safety testing and tuning tailored to their specific applications of the model.