Mixtral significantly upsampled multilingual data during pretraining, which enhances its performance on multilingual benchmarks while ensuring high accuracy in English, outperforming Llama 2 70B.
In assessing long context capabilities, Mixtral achieved a 100% retrieval accuracy in the passkey retrieval task, demonstrating proficiency regardless of context length or passkey position.
Mixtral's performance was evaluated on bias benchmarks like BBQ and BOLD, which measure social biases in QA and language generation, aiming for possible corrections through fine-tuning.
The findings regarding Mixtral highlight its advantages in multilingual tasks and accuracy, alongside its systematic evaluation against well-established benchmarks to identify areas for improvement.
#multilingual-performance #ai-benchmarking #bias-mitigation #long-context-retrieval #sparse-mixture-of-experts
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