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  • John Snow Labs
  • Apr 11, 2022

German Financial Bert Word Embeddings (Annual Financial Statements)

  • bert
  • embeddings
  • de
  • open_source

Description

Pretrained Financial Bert Word Embeddings model, trained on German Financial Statements. Uploaded to Hugging Face, adapted and imported into Spark NLP. german-financial-statements-bert is a German Financial model orginally trained upon 100,000 natural language annual financial statements.

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How to use

documentAssembler = DocumentAssembler() \
.setInputCol("text") \
.setOutputCol("document")

tokenizer = Tokenizer() \
.setInputCols("document") \
.setOutputCol("token")

embeddings = BertEmbeddings.pretrained("bert_embeddings_german_financial_statements_bert","de") \
.setInputCols(["document", "token"]) \
.setOutputCol("embeddings")

pipeline = Pipeline(stages=[documentAssembler, tokenizer, embeddings])

data = spark.createDataFrame([["Ich liebe Funken NLP"]]).toDF("text")

result = pipeline.fit(data).transform(data)

val documentAssembler = new DocumentAssembler() 
.setInputCol("text") 
.setOutputCol("document")

val tokenizer = new Tokenizer() 
.setInputCols(Array("document"))
.setOutputCol("token")

val embeddings = BertEmbeddings.pretrained("bert_embeddings_german_financial_statements_bert","de") 
.setInputCols(Array("document", "token")) 
.setOutputCol("embeddings")

val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, embeddings))

val data = Seq("Ich liebe Funken NLP").toDF("text")

val result = pipeline.fit(data).transform(data)

import nlu
nlu.load("de.embed.german_financial_statements_bert").predict("""Ich liebe Funken NLP""")

Model Information

Model Name: bert_embeddings_german_financial_statements_bert
Compatibility: Spark NLP 3.4.2+
License: Open Source
Edition: Official
Input Labels: [sentence, token]
Output Labels: [bert]
Language: de
Size: 409.8 MB
Case sensitive: true

References

  • https://huggingface.co/fabianrausch/german-financial-statements-bert