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---
license: mit
base_model: microsoft/phi-2
datasets:
- Open-Orca/SlimOrca-Dedup
- migtissera/Synthia-v1.3
- LDJnr/Verified-Camel
- LDJnr/Pure-Dove
- LDJnr/Capybara
- meta-math/MetaMathQA
- Intel/orca_dpo_pairs
- argilla/ultrafeedback-binarized-preferences-cleaned
---
# Phi-2 Orange
A two-step finetune of Phi-2, with a bit of zest.
There is an updated model at [rhysjones/phi-2-orange-v2](https://huggingface.co/rhysjones/phi-2-orange-v2) which has higher evals, if you wish to test.
# Training details
A first finetune using a collection of broad training data:
- [Open-Orca/SlimOrca-Dedup](https://huggingface.co/datasets/Open-Orca/SlimOrca-Dedup)
- [migtissera/Synthia-v1.3](https://huggingface.co/datasets/migtissera/Synthia-v1.3)
- [LDJnr/Verified-Camel](https://huggingface.co/datasets/LDJnr/Verified-Camel)
- [LDJnr/Pure-Dove](https://huggingface.co/datasets/LDJnr/Pure-Dove)
- [LDJnr/Capybara](https://huggingface.co/datasets/LDJnr/Capybara)
- [meta-math/MetaMathQA](https://huggingface.co/datasets/meta-math/MetaMathQA)
And then a DPO finetune using:
- [Intel/orca_dpo_pairs](https://huggingface.co/datasets/Intel/orca_dpo_pairs)
- [argilla/ultrafeedback-binarized-preferences-cleaned](https://huggingface.co/datasets/argilla/ultrafeedback-binarized-preferences-cleaned)
# Run within Ollama
If you're using [Ollama](https://ollama.ai), you can download and run using:
```
ollama run rhysjones/phi-2-orange
```
# Prompt Format
Phi-2 Orange uses ChatML as the prompt format, with or without the system instruction.
To prompt with a system instruction (use whatever system prompt you like):
```
<|im_start|>system
You are a helpful assistant for Python which outputs in Markdown format.<|im_end|>
<|im_start|>user
Write a function to calculate the Fibonacci sequence<|im_end|>
<|im_start|>assistant
```
You can also omit the system prompt if you wish:
```
<|im_start|>user
Why is the sky blue?<|im_end|>
<|im_start|>assistant
```
# Evaluations
Evaluations done using mlabonne's usefull [Colab notebook llm-autoeval](https://github.com/mlabonne/llm-autoeval).
Also check out the alternative leaderboard at [Yet_Another_LLM_Leaderboard](https://huggingface.co/spaces/mlabonne/Yet_Another_LLM_Leaderboard)
| Model |AGIEval|GPT4All|TruthfulQA|Bigbench|Average|
|----------------------------------------------------------------|------:|------:|---------:|-------:|------:|
|[phi-2-orange](https://huggingface.co/rhysjones/phi-2-orange)| **33.37**| 71.33| 49.87| **37.3**| **47.97**|
|[phi-2-dpo](https://huggingface.co/lxuechen/phi-2-dpo)| 30.39| **71.68**| **50.75**| 34.9| 46.93|
|[dolphin-2_6-phi-2](https://huggingface.co/cognitivecomputations/dolphin-2_6-phi-2)| 33.12| 69.85| 47.39| 37.2| 46.89|
|[phi-2](https://huggingface.co/microsoft/phi-2)| 27.98| 70.8| 44.43| 35.21| 44.61| |