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Babsie/CapybaraHermes-2.5-Mistral-7B
CapybaraHermes-2.5-Mistral-7B is a machine learning model from Babsie. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for trl. The card lists the license as apache-2.0.
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Downloads · 30 days
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From the Hugging Face model README
This model is the launching partner of the capybara-dpo dataset build with ⚗️ distilabel. It's a preference tuned OpenHermes-2.5-Mistral-7B.
CapybaraHermes has been preference tuned with LoRA and TRL for 3 epochs using argilla's dpo mix 7k.
To test the impact on multi-turn performance we have used MTBench. We also include the Nous Benchmark results and Mistral-7B-Instruct-v0.2 for reference as it's a strong 7B model on MTBench:
| Model | AGIEval | GPT4All | TruthfulQA | Bigbench | MTBench First Turn | MTBench Second Turn | Nous avg. | MTBench avg. |
|---|---|---|---|---|---|---|---|---|
| argilla/CapybaraHermes-2.5-Mistral-7B | 43.8 | 73.35 | 57.07 | 42.44 | 8.24375 | 7.5625 | 54.16 | 7.903125 |
| teknium/OpenHermes-2.5-Mistral-7B | 42.75 | 72.99 | 52.99 | 40.94 | 8.25 | 7.2875 | 52.42 | 7.76875 |
| Mistral-7B-Instruct-v0.2 | 38.5 | 71.64 | 66.82 | 42.29 | 7.8375 | 7.1 | 54.81 | 7.46875 |
The most interesting aspect in the context of the capybara-dpo dataset is the increased performance in MTBench Second Turn scores.
For the merge lovers, we also preference tuned Beagle14-7B with a mix of capybara-dpo and distilabel orca pairs using the same recipe as NeuralBeagle (see YALL - Yet Another LLM Leaderboard for reference):
| Model | AGIEval | GPT4All | TruthfulQA | Bigbench | Average |
|---|---|---|---|---|---|
| DistilabelBeagle14-7B | 45.29 | 76.92 | 71.66 | 48.78 | 60.66 |
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 68.14 |
| AI2 Reasoning Challenge (25-Shot) | 65.78 |
| HellaSwag (10-Shot) | 85.45 |
| MMLU (5-Shot) | 63.13 |
| TruthfulQA (0-shot) | 56.91 |
| Winogrande (5-shot) | 78.30 |
| GSM8k (5-shot) | 59.29 |