Hugging Face model: sparse-encoder/example-splade-distilbert-base-uncased-quora-duplicates
Author: sparse-encoder
Created: 2025-05-26 15:38:19
Last modified: 2025-05-26 15:38:33
Pipeline: feature-extraction
Library: sentence-transformers
Likes: 0 | Downloads: 81
Tags: sentence-transformers, safetensors, distilbert, sparse-encoder, sparse, splade, generated_from_trainer, dataset_size:99000, loss:SpladeLoss, loss:SparseMultipleNegativesRankingLoss, loss:FlopsLoss, feature-extraction, en, dataset:sentence-transformers/quora-duplicates, arxiv:1908.10084, arxiv:2205.04733, arxiv:1705.00652, arxiv:2004.05665, base_model:distilbert/distilbert-base-uncased, base_model:finetune:distilbert/distilbert-base-uncased, license:apache-2.0, model-index, co2_eq_emissions, text-embeddings-inference, endpoints_compatible, region:us
Base model relation: finetune
Base models: id: distilbert/distilbert-base-uncased
Card metadata:
language: en
license: apache-2.0
tags: sentence-transformers, sparse-encoder, sparse, splade, generated_from_trainer, dataset_size:99000, loss:SpladeLoss, loss:SparseMultipleNegativesRankingLoss, loss:FlopsLoss
base_model: distilbert/distilbert-base-uncased
datasets: sentence-transformers/quora-duplicates
pipeline_tag: feature-extraction
library_name: sentence-transformers
metrics: cosine_accuracy, cosine_accuracy_threshold, cosine_f1, cosine_f1_threshold, cosine_precision, cosine_recall, cosine_ap, cosine_mcc, dot_accuracy, dot_accuracy_threshold, dot_f1, dot_f1_threshold, dot_precision, dot_recall, dot_ap, dot_mcc, euclidean_accuracy, euclidean_accuracy_threshold, euclidean_f1, euclidean_f1_threshold, euclidean_precision, euclidean_recall, euclidean_ap, euclidean_mcc, manhattan_accuracy, manhattan_accuracy_threshold, manhattan_f1, manhattan_f1_threshold, manhattan_precision, manhattan_recall, manhattan_ap, manhattan_mcc, max_accuracy, max_accuracy_threshold, max_f1, max_f1_threshold, max_precision, max_recall, max_ap, max_mcc, active_dims, sparsity_ratio, dot_accuracy@1, dot_accuracy@3, dot_accuracy@5, dot_accuracy@10, dot_precision@1, dot_precision@3, dot_precision@5, dot_precision@10, dot_recall@1, dot_recall@3, dot_recall@5, dot_recall@10, dot_ndcg@10, dot_mrr@10, dot_map@100, query_active_dims, query_sparsity_ratio, corpus_active_dims, corpus_sparsity_ratio
co2_eq_emissions: emissions: 1.4164940270091377
energy_consumed: 0.02527693261851813
source: codecarbon
training_type: fine-tuning
on_cloud: no
cpu_model: AMD Ryzen 9 6900HX with Radeon Graphics
ram_total_size: 30.6114501953125
hours_used: 0.222
hardware_used: 1 x NVIDIA GeForce RTX 3070 Ti Laptop GPU