SentenceTransformer based on BAAI/bge-small-en-v1.5

Model Details

Model Description

• Model Type: Sentence Transformer
• Base model: BAAI/bge-small-en-v1.5
• Maximum Sequence Length: 512 tokens
• Output Dimensionality: 384 dimensions
• Similarity Function: Cosine Similarity

Model Sources

• Documentation: Sentence Transformers Documentation
• Repository: Sentence Transformers on GitHub
• Hugging Face: Sentence Transformers on Hugging Face

Full Model Architecture

SentenceTransformer(
  (0): Transformer({'max_seq_length': 512, 'do_lower_case': True}) with Transformer model: BertModel 
  (1): Pooling({'word_embedding_dimension': 384, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
  (2): Normalize()
)

Usage

Direct Usage (Sentence Transformers)

Evaluation

Metrics

Logging

• Dataset: ir-eval
• Evaluated with [object Object].LoggingEvaluator

Training Details

Training Dataset

Unnamed Dataset

• Size: 98,112 training samples
• Columns: sentence_0 and sentence_1
• Approximate statistics based on the first 1000 samples:

  	sentence_0	sentence_1
  type	string	string
  details	min: 18 tokens mean: 55.27 tokens max: 512 tokens	min: 9 tokens mean: 317.52 tokens max: 512 tokens

• Samples:

  sentence_0	sentence_1
  Represent this question for retrieving relevant documents: Are elevated levels of pro-inflammatory oxylipins in older subjects normalized by flaxseed consumption?	Oxylipins, including eicosanoids, are highly bioactive molecules endogenously produced from polyunsaturated fatty acids. Oxylipins play a key role in chronic disease progression. It is possible, but unknown, if oxylipin concentrations change with the consumption of functional foods or differ with subject age. Therefore, in a parallel comparator trial, 20 healthy individuals were recruited into a younger (19-28years) or older (45-64years) age group (n=10/group). Participants ingested one muffin/day containing 30g of milled flaxseed (6g alpha-linolenic acid) for 4weeks. Plasma oxylipins were isolated through solid phase extraction, analyzed with HPLC-MS/MS targeted lipidomics, and quantified with the stable isotope dilution method. At baseline, the older group exhibited 13 oxylipins ≥2-fold the concentration of the younger group. Specifically, pro-inflammatory oxylipins 5-hydroxyeicosatetraenoic acid, 9,10,13-trihydroxyoctadecenoic acid, and 9,12,13-trihydroxyoctadecenoic acid were signi...
  Represent this question for retrieving relevant documents: Find the isometries of the metric $ds^2 = dx^2 + dy^2$ over the rectangle $R=[0,a] \times [0,b]$, subject to the additional condition that any isometry $f$ maps $(0,0)$ to $(x_0, y_0)$. Find $x_0$ and $y_0$ such that the isometry $f$ is given by $f(x,y) = (x_0 + x, y_0 - y)$.	An isometry is a transformation that preserves the distance between points. In this case, we are looking for transformations that preserve the metric $ds^2 = dx^2 + dy^2$. Let's consider the transformation $f(x,y) = (x_0 + x, y_0 - y)$ and find the conditions on $x_0$ and $y_0$ for it to be an isometry.[object Object][object Object]First, let's compute the differential of the transformation:[object Object][object Object]$$df = \begin{pmatrix} 1 & 0 \ 0 & -1 \end{pmatrix} \begin{pmatrix} dx \ dy \end{pmatrix} = \begin{pmatrix} dx \ -dy \end{pmatrix}$$[object Object][object Object]Now, let's compute the metric under this transformation:[object Object][object Object]$$ds'^2 = (dx')^2 + (dy')^2 = dx^2 + (-dy)^2 = dx^2 + dy^2$$[object Object][object Object]Since $ds'^2 = ds^2$, the transformation $f(x,y) = (x_0 + x, y_0 - y)$ is an isometry.[object Object][object Object]Now, let's find the conditions on $x_0$ and $y_0$ such that the isometry maps $(0,0)$ to $(x_0, y_0)$. Applying the transformation to $(0,0)$, we get:[object Object][object Object]$$f(0,0) = (x_0 + 0, y_0 - 0) = (x_0, y_0)$$[object Object][object Object]Since the transformation maps $(0,0)$ to $(x_0, y_0)$, there are no additional conditions...
  Represent this question for retrieving relevant documents: Do two di-leucine motifs regulate trafficking and function of mouse ASIC2a?	Acid-sensing ion channels (ASICs) are proton-gated cation channels that mediate acid-induced responses in neurons. ASICs are important for mechanosensation, learning and memory, fear, pain, and neuronal injury. ASIC2a is widely expressed in the nervous system and modulates ASIC channel trafficking and activity in both central and peripheral systems. Here, to better understand mechanisms regulating ASIC2a, we searched for potential protein motifs that regulate ASIC2a trafficking.

• Loss: MultipleNegativesRankingLoss with these parameters:
  json

  1{ 2 "scale": 20.0, 3 "similarity_fct": "cos_sim" 4}

Training Hyperparameters

Non-Default Hyperparameters

• eval_strategy: steps
• per_device_train_batch_size: 32
• per_device_eval_batch_size: 32
• num_train_epochs: 1
• batch_sampler: no_duplicates
• multi_dataset_batch_sampler: round_robin

All Hyperparameters

Training Logs

Framework Versions

• Python: 3.12.8
• Sentence Transformers: 3.4.1
• Transformers: 4.51.3
• PyTorch: 2.5.1+cu124
• Accelerate: 1.3.0
• Datasets: 3.2.0
• Tokenizers: 0.21.0

Citation

BibTeX

Sentence Transformers

MultipleNegativesRankingLoss