Model: melghorab/snowflake-arctic-embed-l0-fineTuned
Author: melghorab
Pipeline: sentence-similarity
Library: sentence-transformers
Tags: sentence-transformers, safetensors, bert, sentence-similarity, feature-extraction, generated_from_trainer, dataset_size:24, loss:MatryoshkaLoss, loss:MultipleNegativesRankingLoss, arxiv:1908.10084, arxiv:2205.13147, arxiv:1705.00652, base_model:Snowflake/snowflake-arctic-embed-l, base_model:finetune:Snowflake/snowflake-arctic-embed-l, model-index, text-embeddings-inference, endpoints_compatible, region:us
Base models (finetune): id: Snowflake/snowflake-arctic-embed-l
Card metadata: tags: sentence-transformers, sentence-similarity, feature-extraction, generated_from_trainer, dataset_size:24, loss:MatryoshkaLoss, loss:MultipleNegativesRankingLoss
base_model: Snowflake/snowflake-arctic-embed-l
widget: source_sentence: What methods from the `statistics` module are used to calculate metrics from the input list of grades?
sentences: - Use in Script: It is employed to generate random grades for students within the specified range of 50 to 100.



**Functions**



**1. generate_student_grades(num_students)**



- Purpose: This function generates a list of random integers representing student grades.  

- Parameters:  

  - `num_students` (int): Specifies the number of student grades to generate.  

- Return Value:, - Parameters:  

  - `grades` (list of int): A list containing the student grades for which statistics are to be calculated.  

- Return Value:  

  - Returns a dictionary containing the following statistical metrics:  

    - `average`: The mean of the grades in the list.  

    - `median`: The median value of the grades.  

    - `highest`: The maximum grade.  

    - `lowest`: The minimum grade.  

- Mechanism:, - Mechanism:  

  - The function utilizes methods from the `statistics` module to calculate the average, median, highest, and lowest values from the input list of grades, then returns these metrics in a dictionary format.



**3. main()**



- Purpose: This is the main execution function of the script.  

- Mechanism:  

  - The function orchestrates the program flow by executing the following steps:  

    1. Calls `generate_student_grades(10)` to create a list of 10 random student grades., source_sentence: What is the purpose of the `generate_student_grades` function?
sentences: - Use in Script: It is employed to generate random grades for students within the specified range of 50 to 100.



**Functions**



**1. generate_student_grades(num_students)**



- Purpose: This function generates a list of random integers representing student grades.  

- Parameters:  

  - `num_students` (int): Specifies the number of student grades to generate.  

- Return Value:, - Returns a list of integers, each randomly selected between 50 and 100, representing the students' grades.  

- Mechanism:  

  - The function utilizes the `random.randint(50, 100)` method to generate random grades and appends them to a list, which is returned after all grades are generated.



**2. calculate_grade_stats(grades)**



- Purpose: This function computes various statistical metrics for a list of grades provided as input.  

- Parameters:, 2. Passes the generated grades to `calculate_grade_stats` to compute statistical metrics.  

    3. Outputs the generated grades and the calculated statistics to the console in a readable format.  

- Execution:  

  - The `main` function is invoked if the script is run directly, following standard Python script execution practices.



**Execution Mechanism**, source_sentence: How does the 'random' module contribute to the functionality of the Python script?
sentences: **Python Script for Generating and Analyzing Student Grades**



**Imports**



The following libraries are utilized in this Python script:



- statistics:   

  - Purpose: This module provides functions to calculate mathematical statistics of numeric data.  

  - Use in Script: It is used to compute statistical metrics such as the mean and median of the student grades generated.



- random:  

  - Purpose: This module implements pseudo-random number generators for various distributions., 2. Passes the generated grades to `calculate_grade_stats` to compute statistical metrics.  

    3. Outputs the generated grades and the calculated statistics to the console in a readable format.  

- Execution:  

  - The `main` function is invoked if the script is run directly, following standard Python script execution practices.



**Execution Mechanism**, - Returns a list of integers, each randomly selected between 50 and 100, representing the students' grades.  

- Mechanism:  

  - The function utilizes the `random.randint(50, 100)` method to generate random grades and appends them to a list, which is returned after all grades are generated.



**2. calculate_grade_stats(grades)**



- Purpose: This function computes various statistical metrics for a list of grades provided as input.  

- Parameters:, source_sentence: What is the purpose of the `grades` parameter in the context provided?
sentences: **Python Script for Generating and Analyzing Student Grades**



**Imports**



The following libraries are utilized in this Python script:



- statistics:   

  - Purpose: This module provides functions to calculate mathematical statistics of numeric data.  

  - Use in Script: It is used to compute statistical metrics such as the mean and median of the student grades generated.



- random:  

  - Purpose: This module implements pseudo-random number generators for various distributions., - Returns a list of integers, each randomly selected between 50 and 100, representing the students' grades.  

- Mechanism:  

  - The function utilizes the `random.randint(50, 100)` method to generate random grades and appends them to a list, which is returned after all grades are generated.



**2. calculate_grade_stats(grades)**



- Purpose: This function computes various statistical metrics for a list of grades provided as input.  

- Parameters:, - Parameters:  

  - `grades` (list of int): A list containing the student grades for which statistics are to be calculated.  

- Return Value:  

  - Returns a dictionary containing the following statistical metrics:  

    - `average`: The mean of the grades in the list.  

    - `median`: The median value of the grades.  

    - `highest`: The maximum grade.  

    - `lowest`: The minimum grade.  

- Mechanism:, source_sentence: Which statistical metric indicates the maximum grade among the student grades?
sentences: - Parameters:  

  - `grades` (list of int): A list containing the student grades for which statistics are to be calculated.  

- Return Value:  

  - Returns a dictionary containing the following statistical metrics:  

    - `average`: The mean of the grades in the list.  

    - `median`: The median value of the grades.  

    - `highest`: The maximum grade.  

    - `lowest`: The minimum grade.  

- Mechanism:, - Mechanism:  

  - The function utilizes methods from the `statistics` module to calculate the average, median, highest, and lowest values from the input list of grades, then returns these metrics in a dictionary format.



**3. main()**



- Purpose: This is the main execution function of the script.  

- Mechanism:  

  - The function orchestrates the program flow by executing the following steps:  

    1. Calls `generate_student_grades(10)` to create a list of 10 random student grades., - Returns a list of integers, each randomly selected between 50 and 100, representing the students' grades.  

- Mechanism:  

  - The function utilizes the `random.randint(50, 100)` method to generate random grades and appends them to a list, which is returned after all grades are generated.



**2. calculate_grade_stats(grades)**



- Purpose: This function computes various statistical metrics for a list of grades provided as input.  

- Parameters:
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_precision@3, cosine_precision@5, cosine_precision@10, cosine_recall@1, cosine_recall@3, cosine_recall@5, cosine_recall@10, cosine_ndcg@10, cosine_mrr@10, cosine_map@100
model-index: name: SentenceTransformer based on Snowflake/snowflake-arctic-embed-l
results: task: type: information-retrieval
name: Information Retrieval
dataset: name: Unknown
type: unknown
metrics: type: cosine_accuracy@1
value: 0.75
name: Cosine Accuracy@1
verified: no, type: cosine_accuracy@3
value: 1
name: Cosine Accuracy@3
verified: no, type: cosine_accuracy@5
value: 1
name: Cosine Accuracy@5
verified: no, type: cosine_accuracy@10
value: 1
name: Cosine Accuracy@10
verified: no, type: cosine_precision@1
value: 0.75
name: Cosine Precision@1
verified: no, type: cosine_precision@3
value: 0.3333333333333333
name: Cosine Precision@3
verified: no, type: cosine_precision@5
value: 0.2
name: Cosine Precision@5
verified: no, type: cosine_precision@10
value: 0.1
name: Cosine Precision@10
verified: no, type: cosine_recall@1
value: 0.75
name: Cosine Recall@1
verified: no, type: cosine_recall@3
value: 1
name: Cosine Recall@3
verified: no, type: cosine_recall@5
value: 1
name: Cosine Recall@5
verified: no, type: cosine_recall@10
value: 1
name: Cosine Recall@10
verified: no, type: cosine_ndcg@10
value: 0.9077324383928644
name: Cosine Ndcg@10
verified: no, type: cosine_mrr@10
value: 0.875
name: Cosine Mrr@10
verified: no, type: cosine_map@100
value: 0.875
name: Cosine Map@100
verified: no
Likes: 0 | All-time downloads: 11
Created: 2025-03-06 19:48:35