使用r-text的textEmbed生成嵌入值出现异常字符及NA值的原因排查

Hey there! Let's break down the two issues you're facing with your textEmbed output—those weird-looking characters and the NA values.

1. Understanding the Ġ, <s>, </s>, <pad> Characters #

First off, these aren't "异常字符" (abnormal characters) at all—they're standard outputs from the RoBERTa tokenizer:

• Ġ: RoBERTa uses this symbol to mark tokens that start with a space (it's how the model tracks word boundaries).
• <s>: Marks the start of a text sequence.
• </s>: Marks the end of a text sequence.
• <pad>: Used to pad shorter texts to match the maximum input length the model expects.

How to Clean Them Up #

If you want to remove these markers from your token list, you can use simple string manipulation to filter and clean the data. Here's a quick example using dplyr and stringr:

library(dplyr)
library(stringr)

# Extract your token data
token_data <- temp[["tokens"]][["texts"]][[1]]

# Clean the tokens
cleaned_tokens <- token_data %>%
  # Remove sequence markers like <s>, </s>, <pad>
  filter(!str_detect(token, "^<.*>$")) %>%
  # Strip the leading Ġ from tokens
  mutate(token = str_remove(token, "^Ġ"))

# View the cleaned result
View(cleaned_tokens)

2. Fixing the NA Values in Embeddings #

NA values typically come from a few common issues when working with large models like RoBERTa-large:

• Insufficient Memory: RoBERTa-large is a huge model (over 350 million parameters) and needs a lot of RAM to run smoothly. If your system doesn't have enough memory, parts of the embedding process might fail, leading to NAs. Try closing other resource-heavy programs, or test with a smaller model like roberta-base first to see if the issue goes away.
• Incomplete Model Download: Sometimes model files don't download fully on the first try. You can verify the model's details with:

  textModelInfo("roberta-large")
  

  If the output looks incomplete, try reloading the model or reinstalling the text package.
• Outdated Package Versions: Bugs in older versions of the text package or its dependencies (like transformers) could cause this issue. Update the package with:

  install.packages("text")
  

• Layer Parameter Validation: RoBERTa-large has exactly 24 layers, so layers=23:24 is valid—but double-check you aren't referencing layers that don't exist (e.g., if you accidentally used a model with fewer layers).

Quick Test to Isolate the Problem #

To narrow down the root cause, try running a minimal version of your code with a smaller model:

rm(list=ls())
Sys.setenv(LANG = "C.UTF-8", LC_ALL="C.UTF-8")
library(text)

# Test with roberta-base instead of large
temp_test <- textEmbed("I'm trying to do so good and I keep messing up my life. I hate it so much.", 
                       model="roberta-base", 
                       layers=11:12, 
                       dim_name = FALSE)

View(temp_test[["tokens"]][["texts"]][[1]])

If this works without NAs, the problem is likely tied to memory constraints or issues loading the large RoBERTa model.

内容的提问来源于stack exchange，提问作者AlexGu