license: eupl-1.2
tags:
- assembly
- arm64
- amd64
- risc-v
- i386
Model Description
ASMTransformers is a project to train and use a machine learning model to compare assembly (ARM64, AMD64, RISC-V, i386) functions to a database of known functions, to aid in the process of reverse engineering.
Status
?
Relevant links
Version
TODO: calver of new release
Usage
TODO: do we refer to the inference file of our repo?
Intended use
The model has been trained and tested to be used for similarity search of assembly code. It has not been trained/tested on any other languages than ARM64, AMD64, RISC-V or I386, nor has it been tested on other downstream tasks.
Architecture description
TODO: get model architecture like on the model card of the previous model Don't forget to describe that during pretraining, the --mlm-prob parameter has been set to 0.4, in accordance to [paper](INSERT LINK) Parameters used: epochs=19, eval_steps=10000, batch_size=512, gradient_accumulation_steps=1, mlm_prob=0.4, bf16=True, tf32=True
add estimated time it has cost to train: pretraining: finetuning: 4 hours on 1 NVIDIA H200
Output
The model outputs embeddings that can be compared using cosine similarity
Data
TODO: how did we get the data?
Preprocessing
Several preprocessing steps have been taken, that differ slightly between architectures. TODO: update to same as architecture.md in repo
Performance
Performance was measured in two ways: Mean Reciprocal Rank (MRR) and Accuracy@1