Model: ChrisLalk/German-Emotions
Author: ChrisLalk
Pipeline: text-classification
Library: transformers
Tags: transformers, safetensors, xlm-roberta, text-classification, medical, de, dataset:google-research-datasets/go_emotions, base_model:FacebookAI/xlm-roberta-base, base_model:finetune:FacebookAI/xlm-roberta-base, license:apache-2.0, endpoints_compatible, region:us
Base models (finetune): id: FacebookAI/xlm-roberta-base
Card metadata: license: apache-2.0
datasets: google-research-datasets/go_emotions
base_model: FacebookAI/xlm-roberta-base
language: de
metrics: f1_macro: 0.45, accuracy: 0.41, kappa: 0.42
pipeline_tag: text-classification
tags: medical
model_description: This model was fine-tuned on the German translation of the go_emotions dataset. It is designed to classify German text across 27 emotions (and a "neutral" category). The model is fine-tuned on the FacebookAI/xlm-roberta-base model.  It contains the following emotions: 'admiration', 'amusement', 'anger', 'annoyance', 'approval', 'caring', 'confusion', 'curiosity', 'desire', 'disappointment', 'disapproval', 'disgust', 'embarrassment', 'excitement', 'fear', 'gratitude', 'grief', 'joy', 'love', 'nervousness', 'optimism', 'pride', 'realization', 'relief', 'remorse', 'sadness', 'surprise', 'neutral'. 
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Created: 2024-07-15 09:13:45