Hugging Face model: bobox/DeBERTa2-0.9B-ST-stsb
Author: bobox
Created: 2024-09-04 16:24:10
Last modified: 2024-09-04 16:27:10
Pipeline: sentence-similarity
Library: sentence-transformers
Likes: 0 | Downloads: 0
Tags: sentence-transformers, pytorch, deberta-v2, sentence-similarity, feature-extraction, generated_from_trainer, dataset_size:5749, loss:AnglELoss, en, dataset:sentence-transformers/stsb, arxiv:1908.10084, arxiv:2309.12871, base_model:BXresearch/DeBERTa2-0.9B-SentenceTransformer-v2, base_model:finetune:BXresearch/DeBERTa2-0.9B-SentenceTransformer-v2, model-index, text-embeddings-inference, endpoints_compatible, region:us
Base model relation: finetune
Base models: id: BXresearch/DeBERTa2-0.9B-SentenceTransformer-v2
Card metadata:
base_model: BXresearch/DeBERTa2-0.9B-ST-v2
datasets: sentence-transformers/stsb
language: en
library_name: sentence-transformers
metrics: pearson_cosine, spearman_cosine, pearson_manhattan, spearman_manhattan, pearson_euclidean, spearman_euclidean, pearson_dot, spearman_dot, pearson_max, spearman_max, cosine_accuracy, cosine_accuracy_threshold, cosine_f1, cosine_f1_threshold, cosine_precision, cosine_recall, cosine_ap, dot_accuracy, dot_accuracy_threshold, dot_f1, dot_f1_threshold, dot_precision, dot_recall, dot_ap, manhattan_accuracy, manhattan_accuracy_threshold, manhattan_f1, manhattan_f1_threshold, manhattan_precision, manhattan_recall, manhattan_ap, euclidean_accuracy, euclidean_accuracy_threshold, euclidean_f1, euclidean_f1_threshold, euclidean_precision, euclidean_recall, euclidean_ap, max_accuracy, max_accuracy_threshold, max_f1, max_f1_threshold, max_precision, max_recall, max_ap
pipeline_tag: sentence-similarity
tags: sentence-transformers, sentence-similarity, feature-extraction, generated_from_trainer, dataset_size:5749, loss:AnglELoss