SentenceTransformer based on sentence-transformers/all-mpnet-base-v2

Model Details

Model Description

• Model Type: Sentence Transformer
• Base model: sentence-transformers/all-mpnet-base-v2
• Maximum Sequence Length: 384 tokens
• Output Dimensionality: 768 tokens
• 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': 384, 'do_lower_case': False}) with Transformer model: MPNetModel 
  (1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, '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)

Training Details

Training Dataset

Unnamed Dataset

• Size: 380 training samples
• Columns: Question and Answer
• Approximate statistics based on the first 1000 samples:

  	Question	Answer
  type	string	string
  details	min: 8 tokens mean: 14.96 tokens max: 23 tokens	min: 19 tokens mean: 95.53 tokens max: 118 tokens

• Samples:

  Question	Answer
  How do you interpret a line chart?	A line chart is interpreted by observing the plotted data points that are connected by a line, representing series of data over a certain period. The x-axis typically denotes time or categories, while the y-axis represents the quantity of what is being measured. An upward trend of the line indicates an increase and a downward trend indicates a decrease in the data's value. The steeper the line, the more rapid the increase or decrease. Multiple lines on the same graph can indicate comparisons between different datasets. Further,
  Can you define a heatmap in data visualization?	A heatmap in data visualization is a graphical representation of data where individual values contained in a matrix or data table are represented as colors. It provides an overview of the data and makes complex data sets understandable and visually appealing. Heatmaps are often used to visualize correlation matrices, geographical data, or the behavior of website visitors, among other aspects.
  What are radar charts, and what kind of data are they useful for displaying?	Radar charts, also known as spider or web charts, are graphical representations used in data analysis for displaying multivariate data in the form of two-dimensional charts. These charts are effectively used to visualize the performance or rating data, especially for comparing multiple entities based on different parameters. They can also highlight the contrast between targeted and achieved performance.[object Object][object Object]The values each variable takes are plotted on its individual axes that start from the center of the chart. All these axes are arranged radially, which gives the chart a

• 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: 16
• per_device_eval_batch_size: 16
• num_train_epochs: 1
• warmup_ratio: 0.1
• fp16: True
• batch_sampler: no_duplicates

All Hyperparameters

Framework Versions

• Python: 3.10.12
• Sentence Transformers: 3.0.0
• Transformers: 4.41.2
• PyTorch: 2.3.0+cu121
• Accelerate: 0.30.1
• Datasets: 2.19.2
• Tokenizers: 0.19.1

Citation

BibTeX

Sentence Transformers

MultipleNegativesRankingLoss