Text Classification
Joblib
sentence-transformers
scikit-learn
random-forest
linear_svm
logistic_regression
childes
bilingualism
Instructions to use nimuezorro/bilingual_children_speech_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use nimuezorro/bilingual_children_speech_classifier with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("nimuezorro/bilingual_children_speech_classifier") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
| model_name,accuracy,macro_f1,model_path,confusion_matrix_figure | |
| logistic_regression,0.42592592592592593,0.1806055392154655,/Users/nimuezorman/Desktop/UPPSALA/INFO_R/IR_5LN712/assignment_1/models/logistic_regression.joblib,/Users/nimuezorman/Desktop/UPPSALA/INFO_R/IR_5LN712/assignment_1/reports/figures/confusion_matrix_logistic_regression.png | |
| linear_svm,0.4074074074074074,0.15369802168259256,/Users/nimuezorman/Desktop/UPPSALA/INFO_R/IR_5LN712/assignment_1/models/linear_svm.joblib,/Users/nimuezorman/Desktop/UPPSALA/INFO_R/IR_5LN712/assignment_1/reports/figures/confusion_matrix_linear_svm.png | |
| random_forest,0.26851851851851855,0.10542136339237788,/Users/nimuezorman/Desktop/UPPSALA/INFO_R/IR_5LN712/assignment_1/models/random_forest.joblib,/Users/nimuezorman/Desktop/UPPSALA/INFO_R/IR_5LN712/assignment_1/reports/figures/confusion_matrix_random_forest.png | |