‼️Sentence Transformers v4.0 is out! You can now train and finetune reranker models with multi-GPU training, bf16 support, loss logging, callbacks & much more. I also prove that finetuning on your domain helps much more than you might think.
1️⃣ Reranker Training Refactor Reranker models can now be trained using an extensive trainer with a lot of powerful features: - MultiGPU Training (Data Parallelism (DP) and Distributed Data Parallelism (DDP)) - bf16 training support; loss logging - Evaluation datasets + evaluation loss - Improved callback support + an excellent Weights & Biases integration - Gradient checkpointing, gradient accumulation - Model card generation - Resuming from a training checkpoint without performance loss - Hyperparameter Optimization and much more!
Read my detailed blogpost to learn about the components that make up this new training approach: https://huggingface.co/blog/train-reranker Notably, the release is fully backwards compatible: all deprecations are soft, meaning that they still work but emit a warning informing you how to upgrade.
2️⃣ New Reranker Losses - 11 new losses: - 2 traditional losses: BinaryCrossEntropy and CrossEntropy - 2 distillation losses: MSE and MarginMSE - 2 in-batch negatives losses: MNRL (a.k.a. InfoNCE) and CMNRL - 5 learning to rank losses: Lambda, p-ListMLE, ListNet, RankNet, ListMLE
3️⃣ New Reranker Documentation - New Training Overview, Loss Overview, API Reference docs - 5 new, 1 refactored training examples docs pages - 13 new, 6 refactored training scripts - Migration guides (2.x -> 3.x, 3.x -> 4.x)
4️⃣ Blogpost Alongside the release, I've written a blogpost where I finetune ModernBERT on a generic question-answer dataset. My finetunes easily outperform all general-purpose reranker models, even models 4x as big. Finetuning on your domain is definitely worth it: https://huggingface.co/blog/train-reranker
At this very moment, as shown in the screenshot, mii-llm/maestrale-chat-v0.4-beta is ranked 8th right between ChatGPT-4.5 and ChatGPT-4o.
It's likely that for several months, the best Italian speaking LLM has been an open source 7B model created by open source contributors and hardly anyone knew it.
At this very moment, as shown in the screenshot, mii-llm/maestrale-chat-v0.4-beta is ranked 8th right between ChatGPT-4.5 and ChatGPT-4o.
It's likely that for several months, the best Italian speaking LLM has been an open source 7B model created by open source contributors and hardly anyone knew it.
@ mii-llm with @efederici@mferraretto@FinancialSupport and @DeepMount00 we just released #Propaganda a framework designed to evaluate and train LLMs on political opinions and bias. We aim to analyze both open-source and closed-source LLMs to understand the political positions and biases expressed in their outputs. Moreover we provide a set of recipes to enforce political positions into the models by creating ad hoc curated datasets and by applying fine tuning techniques. By releasing our work in the open, we hope to foster contributions: https://github.com/mii-llm/propaganda
This framework offers opportunities for expansion in various directions and could become the standard reference for evaluating LLMs on political topics, particularly those that influence public opinion.
@ mii-llm with @efederici@mferraretto@FinancialSupport and @DeepMount00 we just released #Propaganda a framework designed to evaluate and train LLMs on political opinions and bias. We aim to analyze both open-source and closed-source LLMs to understand the political positions and biases expressed in their outputs. Moreover we provide a set of recipes to enforce political positions into the models by creating ad hoc curated datasets and by applying fine tuning techniques. By releasing our work in the open, we hope to foster contributions: https://github.com/mii-llm/propaganda
This framework offers opportunities for expansion in various directions and could become the standard reference for evaluating LLMs on political topics, particularly those that influence public opinion.