xlm-roberta-base-finetuned-panx-en Open-source Tagging Classification Model

Xlm Roberta Base Finetuned Panx En

Developed by andreaschandra

A tag classification model fine-tuned on the xtreme dataset based on xlm-roberta-base

Open Source License:MIT #Multilingual Tag Classification #Entity Recognition Optimization #Cross-lingual Transfer Learning

Downloads 19

Release Time : 7/12/2022

Model Overview

This model is a fine-tuned version of the XLM-RoBERTa base model on the PAN-X.en dataset, primarily used for token classification tasks. It achieved an F1 score of 0.6774 on the evaluation set.

Model Features

Cross-lingual Pretraining

Based on the XLM-RoBERTa architecture, with cross-lingual understanding capabilities

Task-Specific Fine-Tuning

Fine-tuned specifically for token classification tasks on the PAN-X.en dataset

Moderate Performance

Achieved an F1 score of 0.6774 on the evaluation set

Model Capabilities

Token Classification

Natural Language Processing

Sequence Labeling

Use Cases

Natural Language Processing

Named Entity Recognition

Can be used to identify named entities in text

F1 score 0.6774

Part-of-Speech Tagging

Can be used to tag the part-of-speech of words in text

Training Loss	Epoch	Step	Validation Loss	F1
1.0236	1.0	50	0.5462	0.5109
0.5047	2.0	100	0.4387	0.6370
0.3716	3.0	150	0.3932	0.6774

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Xlm Roberta Base Finetuned Panx En

Model Overview

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