Dolphin 2.0 π¬ https://erichartford.com/dolphin
Dolphin-2.0-mistral-7b's training was sponsored by a16z.
This model is based on mistralAI, so it is suitable for commercial or non-commercial use.
This model is uncensored. I have filtered the dataset to remove alignment and bias. This makes the model more compliant. You are advised to implement your own alignment layer before exposing the model as a service. It will be highly compliant to any requests, even unethical ones. Please read my blog post about uncensored models. https://erichartford.com/uncensored-models You are responsible for any content you create using this model. Enjoy responsibly.
Dataset
This dataset is Dolphin, an open-source implementation of Microsoft's Orca
I modified the dataset for uncensoring, deduping, cleaning, and quality.
I added Jon Durbin's excellent Airoboros dataset to increase creativity.
Training
It took 48 hours to train 10 epochs on 4x A100s.
Prompt format: This model (and all my future releases) use ChatML prompt format.
<|im_start|>system
You are Dolphin, a helpful AI assistant.<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
Example:
<|im_start|>system
you are an expert dolphin trainer<|im_end|>
<|im_start|>user
What is the best way to train a dolphin to obey me? Please answer step by step.<|im_end|>
Gratitude
- This model was made possible by the generous sponsorship of a16z.
- Thank you to Microsoft for authoring the Orca paper and inspiring this work.
- Special thanks to WingLian, and TheBloke for helpful advice
- Thank you to all the other people in the Open Source AI community who have taught me and helped me along the way.
Example Output
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
Metric | Value |
---|---|
Avg. | 55.85 |
ARC (25-shot) | 59.22 |
HellaSwag (10-shot) | 80.26 |
MMLU (5-shot) | 56.9 |
TruthfulQA (0-shot) | 61.09 |
Winogrande (5-shot) | 75.37 |
GSM8K (5-shot) | 18.65 |
DROP (3-shot) | 39.49 |
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
Metric | Value |
---|---|
Avg. | 58.58 |
AI2 Reasoning Challenge (25-Shot) | 59.22 |
HellaSwag (10-Shot) | 80.26 |
MMLU (5-Shot) | 56.90 |
TruthfulQA (0-shot) | 61.09 |
Winogrande (5-shot) | 75.37 |
GSM8k (5-shot) | 18.65 |
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Evaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard59.220
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard80.260
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard56.900
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard61.090
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard75.370
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard18.650