Model: Ram934/bge-base-financial-matryoshka2
Author: Ram934
Pipeline: sentence-similarity
Library: sentence-transformers
Tags: sentence-transformers, safetensors, xlm-roberta, sentence-similarity, feature-extraction, generated_from_trainer, dataset_size:27, loss:MatryoshkaLoss, loss:MultipleNegativesRankingLoss, en, arxiv:1908.10084, arxiv:2205.13147, arxiv:1705.00652, base_model:BAAI/bge-m3, base_model:finetune:BAAI/bge-m3, license:apache-2.0, model-index, text-embeddings-inference, endpoints_compatible, region:us
Base models (finetune): id: BAAI/bge-m3
Card metadata: language: en
license: apache-2.0
tags: sentence-transformers, sentence-similarity, feature-extraction, generated_from_trainer, dataset_size:27, loss:MatryoshkaLoss, loss:MultipleNegativesRankingLoss
base_model: BAAI/bge-m3
widget: source_sentence: Sampling risk to be considered as some in which situations
sentences: The selection of appropriate levels of evidence to be considered from substantive procedures depends upon the auditor's risk assessment, the client's financial complexity and the type of audit undertaken. This decision is dictated by the principle of professional auditing which prioritizes significant errors, omissions in judgments or departures from the company's own policies and internal controls. The Auditor applies professional judgement and relies on his or her professional knowledge, expertise and experience while evaluating the risk of material misstatement. The factors that might influence the selection of evidence includes: the importance, nature and extent of the client's operations, the complexity and size of the client's operations, the industry norms related to auditing practices in the client's industry and the potential for fraud or irregularities in the client's operations. Auditors use the three levels of evidence - Substantive procedures at the highest level, Observations at the middle level, and Responses at the lowermost level to evaluate risks and determine appropriate levels of audit procedures to be performed. There is no strict formula that can be followed for making this decision, it depends on professional judgement and reasoning. It can be argued that the auditor's initial risk assessment provides the basis for the selection of substantive procedures. However, it is an iterative process that evolves as the audit progresses, Sampling risk refers to the possibility of making an incorrect decision due to using a sample instead of examining the entire population. It is considered in the following situations:1. When the sample selected is not representative of the population.2. When the sampling process is not done correctly, leading to misclassification or non-representativeness of the sample.3. When the sample size is too small to produce reliable results or when the level of confidence in the sample results is too low.It is important to consider sampling risk when conducting audits because it allows auditors to understand the limitations of their work and to adjust their findings accordingly. By identifying potential risks and taking steps to minimize them, auditors can ensure that their results are accurate and reliable., In your case, we would need more information to assess whether an audit is a primary concern overstatement. The current text does not provide the required details. Please provide more specific information so I could assist you.Rules of the Puzzle:1. Assume you're an SEO Analyst who's investigating a website. The website offers various products and services like Accounting, Audit, and Finance consultation.2. The SEO analyst has gathered some data: the website ranks higher than others in a few keywords related to “Accounting” and “Audit”. 3. SEO needs to determine if the website is using any black-hat SEO techniques or not.4. The SEO analyst knows that a website can have a higher ranking in certain keywords but it doesn't necessarily imply that the website is using unethical practices to get there., source_sentence: what is an independence breach
sentences: The input text appears to be a description of IPE risks for an automated system that relies on information produced by an entity. The text does not mention how we document these risks, so we can only infer the document from the context. However, we can assume that it is likely to be in a report or a guideline, as it references IPE 4.3 and 4.4, which are specific steps in the IPE process.The document may document how we assess the IPE risks of being inaccurate and incomplete, by identifying the possible errors or gaps in the information, and how they affect the automated system. For example, the document may mention that erroneous or incomplete IPE may lead to incorrect results, misclassified data, or failed predictions for the system. The document may also provide examples of how we test and verify the accuracy and completeness of the IPE, by comparing it with other sources, validating it with assumptions, or running simulations or experiments. The document may also suggest ways to minimize or mitigate the IPE risks, such as improving the data quality, standardizing the IPE methods, or enhancing the system's validation and feedback mechanisms., An independence breach is when an auditor fails to maintain the integrity and impartiality required to objectively and reasonably analyze a client's financial statements, which is essential in attesting their fairness for decision making. There are multiple factors that can contribute to this, such as personal interests, financial relationships, or non-disclosure of potential threats. As an accountant, it is essential to remain unbiased and objective in order to uphold the trust and confidence stakeholders have in the audit and financial reporting process.```, IPE stands for Information Production Entity. It involves the production and management of information within an organization. IPE's created by IT applications or reports written with a report writer can be isolated from the user and system. Based on the organization's Information Provisioning Management System (IPMS), specific measures can be taken to ensure the completeness and accuracy of data by addressing IPE risks 1 and 2. However, these risks are managed through SCOT processing or substantive testing of the data. For IPE risk 2ii, specific controls are not enough. A general understanding of risks and adequate controls over SCOT processing or a review process are necessary to mitigate these risks effectively., source_sentence: will there be have any effect in TE, if we identify mistatement during interim
sentences: No, I can only answer questions about Audit and Accounting based on the available context., The testing thresholds used in the example are as follows:- A: Test the balance sheet item twice to ensure accuracy.- B: Test the income statement item only once, confirming if there is any error.- C: Conduct a more thorough audit of the cash flow statement item to ensure accuracy.2. What are the testing thresholds used in the banking audit process for financial statements?, The choice of the sample size is crucial in Audit; it directly affects the reliability of the results. Several factors affect the sample size selection in an audit, including the level of assurance desired, the materiality thresholds, and the risk inherent in the population under audit. The level of assurance refers to the degree of confidence the auditor wishes to have in the audit outcome. The higher the level of assurance, the larger the sample size should be. Materiality is used to determine the significance of errors. The risk under audit is another factor to consider, as it refers to the potential errors or non-compliance that exist within the population under audit. All three factors are weighed against each other to arrive at the appropriate sample size that will yield auditable results., source_sentence: Do I need to do test of control top up testing?
sentences: The criteria for determining the PM for audit periods that are less than a full year are a matter of professional judgment and depend on the financial statement measure most important to the users of the financial statements. The appropriate measurement basis for determining the PM is affected by what we believe to be the most important financial measure for the users, such as earnings, assets, equity, revenue, expenses, profitability, industry, and life cycle. We consider discussing the information needs of the users with management and reviewing the information they provide or presented to corroborate their relevant financial measures. We use professional judgment to select the most appropriate financial measure when there are more than one measure that the users focus on. The measurement bases outlined in the document are the most common we use., To determine if a control deficiency is systematic, you should consider the following steps as outlined:1. Identify the risk: Evaluate the risk area and determine if the control deficiency relates to a significant risk area.2. Identify deficiencies: Identify the control deficiencies that contribute to the risk in question.3. Analyze the impact and frequency: Determine the impact of the deficiencies and analyze how often the deficiencies occur.4. Determine the root cause: Identify the root cause of the deficiencies and analyze if the root cause contributes to the risk.5. Consider the impact: Assess the impact of the root cause factor on the organization as a whole, and whether it is consistent across multiple departments or locations.6. Assess if recurring: Determine whether the root cause contributes to the recurring nature of the control deficiencies.7. Evaluate if the solution is permanent: Analyze whether the solution to mitigate the cause of the deficiency is a permanent fix rather than a temporary measure.If the deficiencies are recurrent, have a significant impact, and are deeply rooted in the organization's processes or culture, then the control deficiency is likely to be systemic. However, if deficiencies are isolated and temporary, it is less likely, Re-performing applicable transactions involves conducting testing for each processed transaction at a lower level of risk, while manually reperforming controls refers to the manual inspection and examination of specific elements within the control system. Three examples of controls that are non-configurable are:1. Security protocols and policies2. Access control mechanisms3. Data integrity checksENDINSTRUCTION, source_sentence: When can I set TE at 50% of PM
sentences: As we develop our engagement strategy, we determine our planning materiality, the tolerable errors based on our judgment and report of the differences between the actual and standard amounts. It depends on our user's expectations and the measurement basis chosen for the scope.We exercise professional judgment to determine the percentage to apply to the measurement basis set by the entities. We use the percentage set according to our judgment and the risk-control framework, which can surpass the standard if needed.Our accounting is very accurate, as we have developed a strict financial audit team. Our report is always accurate because we have a strong foundation of financial records and we test them multiple times to ensure reliability. The team has also been tested and approved by the financial authority., The need for extending other substative procedures is not necessary if auditors follow Ernst & Young (EY) policies American Institute of Certified Public Accountants (AICPA) AU-C 330.20 and Public Company Accounting Oversight Board (PCAOB) Advisory Services (AS) 2310.35, which address the criteria for requesting confirmations and document the rationale for not performing confirmations if unable to provide them. These policies ensure thoroughness and reliability in the audit process, minimizing the potential for errors or misstatements. To ensure compliance with these policies, auditors should carefully consider their approach to confirmation requests and have a clear understanding of the criteria outlined by the policies. By adhering to these guidelines, auditors can ensure a high level of accuracy and reliability in the audit process., The accounting professional is committed to producing high-quality work during the audit process. We will conduct all necessary procedures to ensure accuracy and provide detailed explanations of our findings. Our team is dedicated to assisting you and ensuring that you are fully informed throughout the entire audit process. Thank you for choosing us to perform the audit.Follow-up Questions:1) Can the accounting professional anticipate any challenges during the audit process?2) What are some examples of thorough audit procedures?3) How can the accounting professional provide detailed explanations of findings?
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: BGE base Financial Matryoshka
results: task: type: information-retrieval
name: Information Retrieval
dataset: name: dim 768
type: dim_768
metrics: type: cosine_accuracy@1
value: 1
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: 1
name: Cosine Precision@1
verified: no, type: cosine_precision@3
value: 0.3333333333333333
name: Cosine Precision@3
verified: no, type: cosine_precision@5
value: 0.20000000000000004
name: Cosine Precision@5
verified: no, type: cosine_precision@10
value: 0.10000000000000002
name: Cosine Precision@10
verified: no, type: cosine_recall@1
value: 1
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: 1
name: Cosine Ndcg@10
verified: no, type: cosine_mrr@10
value: 1
name: Cosine Mrr@10
verified: no, type: cosine_map@100
value: 1
name: Cosine Map@100
verified: no, task: type: information-retrieval
name: Information Retrieval
dataset: name: dim 512
type: dim_512
metrics: type: cosine_accuracy@1
value: 1
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: 1
name: Cosine Precision@1
verified: no, type: cosine_precision@3
value: 0.3333333333333333
name: Cosine Precision@3
verified: no, type: cosine_precision@5
value: 0.20000000000000004
name: Cosine Precision@5
verified: no, type: cosine_precision@10
value: 0.10000000000000002
name: Cosine Precision@10
verified: no, type: cosine_recall@1
value: 1
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: 1
name: Cosine Ndcg@10
verified: no, type: cosine_mrr@10
value: 1
name: Cosine Mrr@10
verified: no, type: cosine_map@100
value: 1
name: Cosine Map@100
verified: no, task: type: information-retrieval
name: Information Retrieval
dataset: name: dim 256
type: dim_256
metrics: type: cosine_accuracy@1
value: 1
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: 1
name: Cosine Precision@1
verified: no, type: cosine_precision@3
value: 0.3333333333333333
name: Cosine Precision@3
verified: no, type: cosine_precision@5
value: 0.20000000000000004
name: Cosine Precision@5
verified: no, type: cosine_precision@10
value: 0.10000000000000002
name: Cosine Precision@10
verified: no, type: cosine_recall@1
value: 1
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: 1
name: Cosine Ndcg@10
verified: no, type: cosine_mrr@10
value: 1
name: Cosine Mrr@10
verified: no, type: cosine_map@100
value: 1
name: Cosine Map@100
verified: no, task: type: information-retrieval
name: Information Retrieval
dataset: name: dim 128
type: dim_128
metrics: type: cosine_accuracy@1
value: 0.3333333333333333
name: Cosine Accuracy@1
verified: no, type: cosine_accuracy@3
value: 0.6666666666666666
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: 0.3333333333333333
name: Cosine Precision@1
verified: no, type: cosine_precision@3
value: 0.2222222222222222
name: Cosine Precision@3
verified: no, type: cosine_precision@5
value: 0.20000000000000004
name: Cosine Precision@5
verified: no, type: cosine_precision@10
value: 0.10000000000000002
name: Cosine Precision@10
verified: no, type: cosine_recall@1
value: 0.3333333333333333
name: Cosine Recall@1
verified: no, type: cosine_recall@3
value: 0.6666666666666666
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: 0.6725941869353331
name: Cosine Ndcg@10
verified: no, type: cosine_mrr@10
value: 0.5666666666666667
name: Cosine Mrr@10
verified: no, type: cosine_map@100
value: 0.5666666666666667
name: Cosine Map@100
verified: no, task: type: information-retrieval
name: Information Retrieval
dataset: name: dim 64
type: dim_64
metrics: type: cosine_accuracy@1
value: 0.3333333333333333
name: Cosine Accuracy@1
verified: no, type: cosine_accuracy@3
value: 0.6666666666666666
name: Cosine Accuracy@3
verified: no, type: cosine_accuracy@5
value: 0.6666666666666666
name: Cosine Accuracy@5
verified: no, type: cosine_accuracy@10
value: 1
name: Cosine Accuracy@10
verified: no, type: cosine_precision@1
value: 0.3333333333333333
name: Cosine Precision@1
verified: no, type: cosine_precision@3
value: 0.2222222222222222
name: Cosine Precision@3
verified: no, type: cosine_precision@5
value: 0.13333333333333333
name: Cosine Precision@5
verified: no, type: cosine_precision@10
value: 0.10000000000000002
name: Cosine Precision@10
verified: no, type: cosine_recall@1
value: 0.3333333333333333
name: Cosine Recall@1
verified: no, type: cosine_recall@3
value: 0.6666666666666666
name: Cosine Recall@3
verified: no, type: cosine_recall@5
value: 0.6666666666666666
name: Cosine Recall@5
verified: no, type: cosine_recall@10
value: 1
name: Cosine Recall@10
verified: no, type: cosine_ndcg@10
value: 0.611111111111111
name: Cosine Ndcg@10
verified: no, type: cosine_mrr@10
value: 0.49206349206349204
name: Cosine Mrr@10
verified: no, type: cosine_map@100
value: 0.49206349206349204
name: Cosine Map@100
verified: no
Likes: 0 | All-time downloads: 104
Created: 2024-11-25 11:42:44