Hugging Face model: trmteb/multilingual-e5-base_fine_tuned
Author: trmteb
Created: 2025-05-19 14:06:58
Last modified: 2025-05-19 14:07:28
Pipeline: sentence-similarity
Library: sentence-transformers
Likes: 0 | Downloads: 91
Tags: sentence-transformers, safetensors, xlm-roberta, sentence-similarity, feature-extraction, generated_from_trainer, dataset_size:1533351, loss:MultipleNegativesRankingLoss, loss:SoftmaxLoss, loss:CoSENTLoss, dataset:selmanbaysan/msmarco-tr_fine_tuning_dataset, dataset:selmanbaysan/fiqa-tr_fine_tuning_dataset, dataset:selmanbaysan/scifact-tr_fine_tuning_dataset, dataset:selmanbaysan/nfcorpus-tr_fine_tuning_dataset, dataset:selmanbaysan/multinli_tr_fine_tuning_dataset, dataset:selmanbaysan/snli_tr_fine_tuning_dataset, dataset:selmanbaysan/stsb-tr, dataset:selmanbaysan/wmt16_en_tr_fine_tuning_dataset, dataset:selmanbaysan/quora-tr_fine_tuning_dataset, dataset:selmanbaysan/xnli_tr_fine_tuning_dataset, arxiv:1908.10084, arxiv:1705.00652, base_model:selmanbaysan/multilingual-e5-base_contrastive_loss_training, base_model:finetune:selmanbaysan/multilingual-e5-base_contrastive_loss_training, model-index, text-embeddings-inference, endpoints_compatible, region:us
Base model relation: finetune
Base models: id: selmanbaysan/multilingual-e5-base_contrastive_loss_training
Card metadata:
tags: sentence-transformers, sentence-similarity, feature-extraction, generated_from_trainer, dataset_size:1533351, loss:MultipleNegativesRankingLoss, loss:SoftmaxLoss, loss:CoSENTLoss
base_model: selmanbaysan/multilingual-e5-base_contrastive_loss_training
datasets: selmanbaysan/msmarco-tr_fine_tuning_dataset, selmanbaysan/fiqa-tr_fine_tuning_dataset, selmanbaysan/scifact-tr_fine_tuning_dataset, selmanbaysan/nfcorpus-tr_fine_tuning_dataset, selmanbaysan/multinli_tr_fine_tuning_dataset, selmanbaysan/snli_tr_fine_tuning_dataset, selmanbaysan/stsb-tr, selmanbaysan/wmt16_en_tr_fine_tuning_dataset, selmanbaysan/quora-tr_fine_tuning_dataset, selmanbaysan/xnli_tr_fine_tuning_dataset
pipeline_tag: sentence-similarity
library_name: sentence-transformers
metrics: pearson_cosine, spearman_cosine, cosine_accuracy, cosine_accuracy_threshold, cosine_f1, cosine_f1_threshold, cosine_precision, cosine_recall, cosine_ap, cosine_mcc