Roberta Base Ca Finetuned Tecla
Text classification model fine-tuned on the MNLI task based on the Catalan RoBERTa model
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Release Time : 3/2/2022
Model Overview
This model is a fine-tuned version of BSC-TeMU's Catalan RoBERTa base model on the MNLI (Multi-Genre Natural Language Inference) task, primarily used for text classification tasks.
Model Features
Catalan optimization
Pre-trained model specifically optimized for Catalan text
MNLI task fine-tuning
Specially fine-tuned on multi-genre natural language inference tasks
Medium accuracy
Achieves 73.6% accuracy on the tecla evaluation set
Model Capabilities
Text classification
Natural language inference
Catalan text processing
Use Cases
Text analysis
Text classification
Classify Catalan text
Achieves 73.6% accuracy on the tecla dataset
Natural language inference
Determine the logical relationship between two texts
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