Model: dinho1597/bge-small-qa-telecom-ft
Author: dinho1597
Pipeline: sentence-similarity
Library: sentence-transformers
Tags: sentence-transformers, safetensors, bert, sentence-similarity, feature-extraction, generated_from_trainer, dataset_size:6552, loss:MultipleNegativesRankingLoss, dataset:dinho1597/Telecom-QA-MultipleChoice, arxiv:1908.10084, arxiv:1705.00652, base_model:BAAI/bge-small-en-v1.5, base_model:finetune:BAAI/bge-small-en-v1.5, model-index, text-embeddings-inference, endpoints_compatible, region:us
Base models (finetune): id: BAAI/bge-small-en-v1.5
Card metadata: tags: sentence-transformers, sentence-similarity, feature-extraction, generated_from_trainer, dataset_size:6552, loss:MultipleNegativesRankingLoss
base_model: BAAI/bge-small-en-v1.5
widget: source_sentence: What property is denoted as the M→M property in the queueing network literature?
sentences: The LOFAR system introduces two additional levels in the beam hierarchy: the compound (tile) beam and the station beam., The desired pseudonoise sequence in a CDMA system has the characteristics that the fraction of 0's and 1's is almost half-and-half over the period, and the shifted versions of the pseudonoise sequence are nearly orthogonal to each other. If the shift of the pseudonoise sequence is randomized, it becomes a random process., The M→M property in the queueing network literature denotes the independence of individual queues in the long term., source_sentence: Which type of channel condition has better path loss exponent (PLE) in terms of AA (air to air) and AG (air to ground) propagation channels?
sentences: The goal of the Fixed Access Information API is to provide access network related information for the multitude of fixed access technologies., Error mitigation is a technique to reduce the impact of errors in near-term quantum systems without requiring full fault-tolerant quantum codes., From the document, it is mentioned that the AA channel has better conditions than the AG channel in terms of path loss exponent (PLE)., source_sentence: What is the goal of a functionality extraction attack?
sentences: Deep learning can automatically extract high-level features from data, reducing the need for manual feature engineering., The goal of a functionality extraction attack is to create knock-off models that mimic the behavior of an existing machine learning model., The main advantage of using wind turbine towers for communication is that they already have a reliable power grid connection., source_sentence: What is MTU?
sentences: The worst-case complexity of average consensus is exponential in the number of nodes, but it can be reduced to linear if an upper bound on the total number of nodes is known., In a normally clad fiber, at long wavelengths, the MFD is large compared to the core diameter and the electric field extends far into the cladding region., MTU (Maximum Transmission Unit) represents the largest size of a data packet that can be sent over a network without fragmentation., source_sentence: What should the AP or PCP do if it is not decentralized AP or PCP clustering capable or a decentralized AP or PCP cluster is not present?
sentences: When a Data, Management or Extension frame is received, a STA inserts it in an appropriate cache., If the AP or PCP is not decentralized AP or PCP clustering capable or a decentralized AP or PCP cluster is not present, it should set its Cluster Member Role to 0 (not currently participating in a cluster) and remain unclustered., Analog beamforming based on slowly-varying second order statistics of the CSI reduces the dimension of the effective instantaneous CSI for digital beamforming within each coherent fading block, which helps to relieve the signaling overhead.
datasets: dinho1597/Telecom-QA-MultipleChoice
pipeline_tag: sentence-similarity
library_name: sentence-transformers
metrics: cosine_accuracy@1, cosine_accuracy@3, cosine_accuracy@5, cosine_accuracy@10, cosine_precision@1, cosine_recall@1, cosine_ndcg@10, cosine_mrr@10, cosine_map@100
model-index: name: SentenceTransformer based on BAAI/bge-small-en-v1.5
results: task: type: information-retrieval
name: Information Retrieval
dataset: name: telecom ir eval
type: telecom-ir-eval
metrics: type: cosine_accuracy@1
value: 0.965675057208238
name: Cosine Accuracy@1
verified: no, type: cosine_accuracy@3
value: 0.992372234935164
name: Cosine Accuracy@3
verified: no, type: cosine_accuracy@5
value: 0.9931350114416476
name: Cosine Accuracy@5
verified: no, type: cosine_accuracy@10
value: 0.9938977879481312
name: Cosine Accuracy@10
verified: no, type: cosine_precision@1
value: 0.965675057208238
name: Cosine Precision@1
verified: no, type: cosine_recall@1
value: 0.965675057208238
name: Cosine Recall@1
verified: no, type: cosine_ndcg@10
value: 0.9824027787882591
name: Cosine Ndcg@10
verified: no, type: cosine_mrr@10
value: 0.9784334023464457
name: Cosine Mrr@10
verified: no, type: cosine_map@100
value: 0.9786169716375667
name: Cosine Map@100
verified: no
Likes: 1 | All-time downloads: 8
Created: 2025-01-15 22:53:35