Description
XLM-RoBERTa Model with sequence classification/regression head on top (a linear layer on top of the pooled output) e.g. for multi-class document classification tasks.
xlm_roberta_base_sequence_classifier_ag_news is a fine-tuned XLM-RoBERTa model that is ready to be used for Sequence Classification tasks such as sentiment analysis or multi-class text classification and it achieves state-of-the-art performance.
We used TFXLMRobertaForSequenceClassification to train this model and used XlmRoBertaForSequenceClassification annotator in Spark NLP 🚀 for prediction at scale!
Predicted Entities
Business, Sci/Tech, Sports, World
How to use
document_assembler = DocumentAssembler() \
.setInputCol('text') \
.setOutputCol('document')
tokenizer = Tokenizer() \
.setInputCols(['document']) \
.setOutputCol('token')
sequenceClassifier = XlmRoBertaForSequenceClassification \
.pretrained('xlm_roberta_base_sequence_classifier_ag_news', 'en') \
.setInputCols(['token', 'document']) \
.setOutputCol('class') \
.setCaseSensitive(True) \
.setMaxSentenceLength(512)
pipeline = Pipeline(stages=[
document_assembler,
tokenizer,
sequenceClassifier
])
example = spark.createDataFrame([['Disney Comics was a comic book publishing company operated by The Walt Disney Company which ran from 1990 to 1993.']]).toDF("text")
result = pipeline.fit(example).transform(example)
val document_assembler = DocumentAssembler()
.setInputCol("text")
.setOutputCol("document")
val tokenizer = Tokenizer()
.setInputCols("document")
.setOutputCol("token")
val sequenceClassifier = XlmRoBertaForSequenceClassification.pretrained("xlm_roberta_base_sequence_classifier_ag_news", "en")
.setInputCols("document", "token")
.setOutputCol("class")
.setCaseSensitive(true)
.setMaxSentenceLength(512)
val pipeline = new Pipeline().setStages(Array(document_assembler, tokenizer, sequenceClassifier))
val example = Seq("Disney Comics was a comic book publishing company operated by The Walt Disney Company which ran from 1990 to 1993.").toDS.toDF("text")
val result = pipeline.fit(example).transform(example)
import nlu
nlu.load("en.classify.xlm_roberta.ag_news").predict("""Disney Comics was a comic book publishing company operated by The Walt Disney Company which ran from 1990 to 1993.""")
Model Information
| Model Name: | xlm_roberta_base_sequence_classifier_ag_news |
| Compatibility: | Spark NLP 3.4.0+ |
| License: | Open Source |
| Edition: | Official |
| Input Labels: | [token, document] |
| Output Labels: | [ner] |
| Language: | en |
| Size: | 871.0 MB |
| Case sensitive: | true |
| Max sentense length: | 512 |
Data Source
https://huggingface.co/datasets/ag_news
Benchmarking
{
"eval_loss": 0.2071533501148224,
"eval_accuracy": 0.9478947368421052,
"eval_f1": 0.9478947368421052,
"eval_precision": 0.9478947368421052,
"eval_recall": 0.9478947368421052,
"eval_runtime": 97.8727,
"eval_samples_per_second": 77.652,
"eval_steps_per_second": 4.853,
"epoch": 2.0
}