|
--- |
|
license: apache-2.0 |
|
datasets: |
|
- HuggingFaceTB/cosmopedia |
|
- EleutherAI/proof-pile-2 |
|
- bigcode/the-stack-dedup |
|
- math-ai/AutoMathText |
|
language: |
|
- en |
|
metrics: |
|
- accuracy |
|
- code_eval |
|
--- |
|
|
|
|
|
# Mistral-Pro-8B Model Card |
|
|
|
## Model Description |
|
Mistral-Pro is a progressive version of the original [Mistral](https://huggingface.co/mistralai/Mistral-7B-v0.1) model, enhanced by the addition of Transformer blocks. It specializes in integrating both general language understanding and domain-specific knowledge, particularly in programming and mathematics. |
|
|
|
## Development and Training |
|
Developed by Tencent's ARC Lab, Mistral-Pro is an 8 billion parameter model. It's an expansion of Mistral-7B, further trained on code and math corpora. |
|
|
|
## Intended Use |
|
This model is designed for a wide range of NLP tasks, with a focus on programming, mathematics, and general language tasks. It suits scenarios requiring integration of natural and programming languages. |
|
|
|
## Performance |
|
Mistral_Pro_8B_v0.1 showcases superior performance on a range of benchmarks. It enhances the code and math performance of Mistral. Furthermore, it matches the performance of the recently dominant model, [Gemma](https://huggingface.co/google/gemma-7b). |
|
|
|
### Overall Performance on Languages, math and code tasks |
|
|
|
| Model | ARC | Hellaswag | MMLU | TruthfulQA | Winogrande | GSM8K | HumanEval | |
|
| :-: | :-: | :-: | :-: | :-: | :-: | :-: | :-: | |
|
| Gemma-7B | 61.9 | 82.2 | 64.6 | 44.8 | 79.0 | 50.9 | 32.3 | |
|
| Mistral-7B | 60.8 | 83.3 | 62.7 | 42.6 | 78.0 | 39.2 | 28.7 | |
|
| Mistral_Pro_8B_v0.1 | 63.2 | 82.6 | 60.6 | 48.3 | 78.9 | 50.6 | 32.9 | |
|
|
|
|
|
## Limitations |
|
While Mistral-Pro addresses some limitations of previous models in the series, it may still encounter challenges specific to highly specialized domains or tasks. |
|
|
|
## Ethical Considerations |
|
Users should be aware of potential biases in the model and use it responsibly, considering its impact on various applications. |
