Can embedding size be considered a hyperparameter?

Aug 18, 2020 ... An embedding of the topological space X into Euclidean space Rn is just a map ϕ:X→Rn such that ϕ:X→ϕ(X) is a homeomorphism. An embedding refers to the reduction of high-dimensional data, such as unstructured text, to a representation with fewer dimensions, such as a vector. For other users embedding many documents, this batch size may be too small. # set the batch size to 42 embed_model = OpenAIEmbedding(embed_batch_size=42) ... They feature lower costs, higher multilingual performance, and new parameters to control the overall size. What are embeddings? OpenAI's text embeddings measure ... Mar 19, 2023 ... I was wondering if ml-common has (or will have) options to reduce the default size using techniques such as PCA, t-SNE (t-SNE-Java), LDA, Autoencoders etc. Model Choices Voyage currently provides the following text embedding models: Model Context Length (tokens) Embedding Dimension Description voyage-3-large ... Apr 8, 2024 ... What are embedding models? Embedding models are models that are trained specifically to generate vector embeddings ... Parameter Size. mxbai-embed ... Higher dimensions allow more nuanced representations but require more computational resources. For instance, word embeddings like Word2Vec often use 300 ... ... embed configuration. Here I could define the size as I like. In the new storymaps I don't have a place to do that. They even change the embedded code to ... Here are some test forms on fitting-net size tuning or embedding-net size tuning performed on several different systems.