metadata
base_model: BAAI/bge-small-en-v1.5
datasets: []
language: []
library_name: sentence-transformers
metrics:
- cosine_accuracy@1
- cosine_accuracy@5
- cosine_accuracy@10
- cosine_precision@1
- cosine_precision@5
- cosine_precision@10
- cosine_recall@1
- cosine_recall@5
- cosine_recall@10
- cosine_ndcg@5
- cosine_ndcg@10
- cosine_ndcg@100
- cosine_mrr@5
- cosine_mrr@10
- cosine_mrr@100
- cosine_map@100
- dot_accuracy@1
- dot_accuracy@5
- dot_accuracy@10
- dot_precision@1
- dot_precision@5
- dot_precision@10
- dot_recall@1
- dot_recall@5
- dot_recall@10
- dot_ndcg@5
- dot_ndcg@10
- dot_ndcg@100
- dot_mrr@5
- dot_mrr@10
- dot_mrr@100
- dot_map@100
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- feature-extraction
- generated_from_trainer
- dataset_size:900
- loss:GISTEmbedLoss
widget:
- source_sentence: How does the Equity Grant contribute to the creditworthiness of FPOs?
sentences:
- >-
' Date……………………………… ……………………………… Signature of Branch Manager with
branch seal Name…………………………………… … Designation ……………………………………
……………………………… ……………………………… Signature of Authorized Person in zonal
office Name………………………………… Designation …………………………………… 5. Promoter's
request letter List of Enclosures 1. Recommendation 9. List of
shareholders addressed to the Bank Manager on original letter head of
FPO confirmed by promoter and bank with amount of CGC sought on
Bank's Original letterhead with date and dispatch number duly signed by
the Branch Manager on each page. 2. Sanction letter of 6.
Implementation Schedule 10. Affidavit of promoters that confirmed by
the bank. they have not availed CGC from any other institution for
sanctioned Credit Facility. sanctioning authority addressed to
recommending branch. 3. Bank's approved 7. Up-to-date statement of
account of 11. Field inspection report of Term loan and Cash Credit
(if Sanctioned). Bank official as on recent date. Appraisal/Process
note bearing signature of sanctioning authority. 4. Potential Impact
on 8. a).Equity Certificate, C.A/CS * Pin Code at Column No. 1. a),
certificate/RCS certificate 2. b), 2. c), 4. a) and 9. a) is Mandatory
b). FORM-2, FORM-5 and FORM-23 filed with ROC for Company/RCS. small
farmer producers 1. Social Impact, 2. Environmental Impact 3.'
- >-
'i. Shareholder List and Share Capital contribution by each Member
verified and certified by a Chartered Accountant (CA) prior to
submission (Format attached, Annexure I- Enclosure-I). ii. Resolution of
FPO Board/Governing Council to seek Equity Grant for Members (Format
attached, Annexure I- Enclosure-II). iii. Consent of Shareholders,
stating name of shareholder, gender, number of shares held, face value
of shares, land holding, and signature, signifying consent for
Implementing Agency to directly transfer the Equity Grant sanctioned to
the FPC on their behalf, to FPC Bank account, against the consideration
of additional shares of equivalent value to be issued to them by FPC and
on exit- transfer of the shares as per rules (Format attached, Annexure
I-Enclosure-III). iv. Audited Financials of FPO for a minimum 1
year/for all years of existence of the FPO if formed less than three
years prior to application/ for the last 3 years for FPO in existence
for 3 years or more, verified and certified by a Chartered Accountant
(CA) prior to submission. v. Photocopy of FPO Bank Account Statement for
last six months authenticated by Branch Manager. vi. Business plan and
budget for next 18 months. vii. Names, photographs, and identity proof
(one from among ration card, Aadhaar card, election identification card,
and passport of Representatives/ Directors authorized by the Board for
executing and signing all documents under the Scheme. viii. Each page of
Application Form and accompanying documents should be signed by a
minimum of two Board Member Authorised Representatives of FPO;'
- >-
'11.1 Producer members' own equity supplemented by a matching Equity
Grant from Government, which is required to strengthen financial base
of FPOs and help them to get credit from financial institutions for
their projects and working capital requirements for business
development. Equity Grant shall be in the form of matching grant upto
Rs. 2,000 per farmer member of FPO subject to maximum limit of Rs. 15.00
lakh fixed per FPO. This Equity Grant is not in the form of government
participation in equity, but only as a matching grant to the FPOs as
farmer members' equity. Therefore, Rs.1,500 crore with DAC&FW is
proposed in the scheme to cover all the 10,000 FPOs, if maximum
permissible equity is contributed to all 10,000 FPOs. 11.2 **Objectives
of Equity Grant:** The objectives of Equity Grant are to (i) enhance
viability and sustainability of FPOs; (ii) increase credit worthiness of
FPOs; and (iii) enhance shareholding of members to increase their
ownership and participation in their FPO. 11.3 **Eligibility Criteria
for FPOs:** An FPO fulfilling following criteria shall be eligible to
apply for Equity Grant under the Scheme- (i) It shall be a legal
entity as per para 2 of this guidelines. (ii) It has raised equity from
its Members as laid down in its Articles of Association/ Bye laws, as
the case may be. (iii) The number of its Individual Shareholders is in
accordance with the terms hereto read together with the Scheme. (iv)
Minimum 50% of its shareholders are small, marginal and landless tenant
farmers as defined by the Agriculture Census carried out periodically by
the Ministry of Agriculture, GoI. Women farmers' participation as its
shareholders is to be preferred. (v) Maximum shareholding by any one
member shall not be more than 10% of total equity of the FPO.'
- source_sentence: What is the purpose of the National Crop Insurance Portal?
sentences:
- >-
'i. Shareholder List and Share Capital contribution by each Member
verified and certified by a Chartered Accountant (CA) prior to
submission (Format attached, Annexure I- Enclosure-I). ii. Resolution of
FPO Board/Governing Council to seek Equity Grant for Members (Format
attached, Annexure I- Enclosure-II). iii. Consent of Shareholders,
stating name of shareholder, gender, number of shares held, face value
of shares, land holding, and signature, signifying consent for
Implementing Agency to directly transfer the Equity Grant sanctioned to
the FPC on their behalf, to FPC Bank account, against the consideration
of additional shares of equivalent value to be issued to them by FPC and
on exit- transfer of the shares as per rules (Format attached, Annexure
I-Enclosure-III). iv. Audited Financials of FPO for a minimum 1
year/for all years of existence of the FPO if formed less than three
years prior to application/ for the last 3 years for FPO in existence
for 3 years or more, verified and certified by a Chartered Accountant
(CA) prior to submission. v. Photocopy of FPO Bank Account Statement for
last six months authenticated by Branch Manager. vi. Business plan and
budget for next 18 months. vii. Names, photographs, and identity proof
(one from among ration card, Aadhaar card, election identification card,
and passport of Representatives/ Directors authorized by the Board for
executing and signing all documents under the Scheme. viii. Each page of
Application Form and accompanying documents should be signed by a
minimum of two Board Member Authorised Representatives of FPO;'
- >-
'i. \'Credit Facility\' means any fund based credit facility extended
by an Eligible Lending Institution (ELI) to an Eligible Borrower
without any Collateral Security or Third Party Guarantee ; ii.
\'Credit Guarantee Fund\' means the Credit Guarantee Fund for FPOs
created with NABARD and NCDC respectively under the Scheme with
matching grant from DAC&FW for the purpose of extending guarantee to the
eligible lending institution(s) against their collateral free lending
to eligible FPOs; iii. \'Eligible Lending Institution (ELI)\' means a
Scheduled Commercial Bank for the time being included in the second
Schedule to the Reserve Bank of India Act, 1934, Regional Rural Banks,
Co-operative Banks, Cooperative Credit Society, NEDFI, or any other
institution (s) as may be decided by the NABARD and/or NCDC, as the case
may be, in consultation with Government of India from time to time.
NABARD and NCDC can also finance, if they so desire with the approval of
DAC&FW/N-PMFSC. NBFCs and such other financing institutions with
required net worth and track record may also serve as Eligible Lending
Institutions (ELIs), for lending to FPOs with a moderate spread between
their cost of capital and lending rate. However, Standard Financial
Sector Rating Agency should have rated NBFC **to be AAA** to be
considered as ELI; iv. \'Guarantee Cover\' means maximum cover
available per eligible FPO borrower; v. \'Guarantee Fee\' means the
onetime fee at a specified rate of the eligible credit facility
sanctioned by the ELI, payable by the ELI to NABARD or NCDC, as the case
may be; and vi.'
- >-
' 2.7 Secured credential/login, preferably linked with Aadhaar
Number and mobile OTP based, for all Stakeholders viz, Central
Government, State Governments, Banks, empanelled Insurance Companies
and their designated field functionaries will be provided on the Portal
to enable them to enter/upload/download the requisite information.
2.8 Insurance Companies shall not distribute/collect/allow any other
proforma/utility/web Portal etc for collecting details of insured
farmers separately. However they may provide all requisite support to
facilitate Bank Branches/PACS for uploading the farmer's details on the
Portal well within the prescribed cut-off dates. 2.9 Only farmers
whose data is uploaded on the National Crop Insurance Portal shall be
eligible for Insurance coverage and the premium subsidy from State
and Central Govt. will be released accordingly. 2.10 All data
pertaining to crop-wise, area-wise historical yield data, weather data,
sown area, coverage and claims data, calamity years and actual yield
shall be made available on the National Crop Insurance Portal for the
purpose of premium rating, claim calculation etc. 2.11
Banks/Financial Institutions/other intermediaries need to compulsorily
transfer the individual farmer's data electronically to the National
Crop Insurance Portal. Accordingly Banks/FIs may endeavour to
undertake CBS integration in a time bound manner for real time transfer
of information/data. 2.12 It is also proposed to develop an
integrated platform/portal for both PMFBY and Interest Subvention
Scheme. The data/information of both the Schemes shall be auto
synchronized to enable real time sharing of information and better
program monitoring. 2.13 Insurance Companies shall compulsorily use
technology/mobile applications for monitoring of crop health/Crop
Cutting Experiments (CCEs) in coordination with concerned States. States
shall also facilitate Insurance Companies with Satellite
Imagery/Usage of Drones by way of prior approval of agency from which
such data can be sourced. This is required for better monitoring and
ground- truthing.'
- source_sentence: What should the business plan of an FPO be based on?
sentences:
- >-
'First installment due on (date) : ii). Last Installment due on
(date) : 6. b). Cash Credit : Limit: Drawing Power:
Outstanding: Comments on Irregularity ( if any): Any adverse
comments on the unit by inspecting official in last inspection
report: 7. A. Cost of Project (as accepted by sanctioning
authority)(In Rs. Lakh) B. Means of Finance (as accepted by
sanctioning authority)(In Rs. Lakh) Give component wise details a.
Term loan of Bank: b. Promoter Equity c. Unsecured loan : d. Others
if any Total Total 8. A. Forward Linkages: B. Backward
Linkages with Small/Marginal farmers: 1 No. of members:
2 Details of Primary and Collateral Securities taken by the bank (if
any) 3 a. Primary Securities b. Collateral Securities 4
5 6 (Please enclose details separately) 9
NameoftheConsortium(ifany)associatedwithCreditFacilitywithcompleteaddress,contac
t details and email: 9 a) Address (*with pin-code) : 9 b) Contact
Details : 9 c) Email Address : Request of Branch head for Credit
Guarantee:- In view of the above information, we request Credit
Guarantee Cover against Credit Facility of Rs.....................(in
Rupees ) to FPO(copy of sanction letter along with appraisal/process
note of competent authority is enclosed for your perusal and record ).
Further we confirm that : 1. The KYC norms in respect of the Promoters
have been complied by us. 2. Techno-feasibility and economic viability
aspect of the project has been taken care of by the sanctioning
authority and the branch. 3. On quarterly basis, bank will apprise the
........................(Name of Implementing Agency)about progress of
unit, recovery of bank's dues and present status of account
to........................(Name of Implementing Agency) 4. We undertake
to abide by the Terms & Conditions of the Scheme.'
- >-
'19.1 It has been seen, during first two years of implementation of
PMFBY, there are various types of yield disputes, which unnecessarily
delays the claim settlement. Following figure shows the procedures to
be adopted in various cases. Figure. Procedures to be followed in
different yield dispute cases 19.2 Wherever the yield estimates
reported at IU level are abnormally low or high vis-à-vis the general
crop condition the Insurance Company in consultation with State Govt.
can make use of various products (e.g. Satellite based Vegetation Index,
Weather parameters, etc.) or other technologies (including statistical
test, crop models etc.) to confirm yield estimates. If Insurance Company
witnesses any anomaly/deficiency in the actual yield data(partial
/consolidated) received from the State Govt., the same shall be brought
into the notice of concerned State department within 7 days from date of
receipt of yield data with specific observations/remarks under
intimation to Govt. of India and anomaly, if any, may be resolved in
next 7 days by the State Level Coordination Committee (SLCC) headed by
Additional Chief Secretary/Principal Secretary/Secretary of the
concerned department. This committee shall be authorized to decide all
such cases and the decision in such cases shall be final. The SLCC may
refer the case to State Level Technical Advisory Committee (STAC) for
dispute resolution (Constitution of STAC is defined in Para 19.5). In
case the matter stands unresolved even after examination by STAC, it may
be escalated to TAC along with all relevant documents including minutes
of meetings/records of discussion and report of the STAC and SLCC.
Reference to TAC can be made thereafter only in conditions specified in
Para 19.7.1 However, data with anomalies which is not reported within 7
days will be treated as accepted to insurance company.'
- >-
' (vi) A farmer can be member in more than one FPO with different
produce clusters but he/she will be eligible only once(for any one FPO
that he/she is a member) for the matching equity grant up to his/her
share. (vii) In the Board of Directors (BoD) and Governing Body (GB),
as the case may be, there shall be adequate representation of women
farmer member(s) and there should be minimum one woman member. (viii)
It has a duly constituted Management Committee responsible for the
business of the FPO. (ix) It has a business plan and budget for next 18
months that is based on a sustainable, revenue model as may be
determined by the Implementing Agency.'
- source_sentence: How often does DAC&FW release advances to Implementing Agencies?
sentences:
- >-
'| Picking 1 | Picking
2 | Picking 4
|\n|-------------------------------------------------------|----------------|--------------|\n|
Total Yield Kg) |
| |\n| Picking
3 |
| |\n| Yield
(Kg) |
| |\n|
Crop | Experiment no.
| |\n|
Yield |
| |\n|
(Kg) |
| |\n|
Yield |
| |\n|
(Kg) |
| |\n|
Yield |
| |\n|
(Kg) |
| |\n|
P1 | P2 |
P3 |\n| Well Conducted CCEs in the Taluka with 4 pickings
| | |\n|
Cotton | E1 |
1 |\n| Cotton
| E2 | 1 |\n|
Cotton | E3 |
0.75 |\n| Cotton
| E4 | 0.8 |\n|
Cotton | E5 |
0.95 |\n|
| Average | 0.9 |\n|
6.373 | 2.128 |
1.282 |\n| (1
| | |\n|
st |
| |\n| +
2 |
| |\n|
nd |
| |\n|
+3 |
| |\n|
rd |
|
|\n|
| | |\n| Factor (Total
yield/ | |
|\n| Picking Yield)
| |
|\n|
| | |\n|
(1 |
| |\n|
st |
| |\n|
) | (1
| |\n|
st |
| |\n|
+ |
| |\n|
2 |
| |\n|
nd |
| |\n|
) | )
| |\n| CCEs with Less Pickings in any IU within that
Taluka | | |\n|
Cotton | E6 (only 1
| |\n|
st |
| |\n|
Picking) | 1
| |\n|
Cotton | E7 (1
| |\n|
st |
| |\n| and
2 |
| |\n|
nd |
| |\n|
Picking) | 1.2 |
1.75 |\n| Cotton
| E8 (1 | |\n|
st |
| |\n| ,
2 |
| |\n|
nd |
| |\n| &
3 |
| |\n|
rd |
| |\n|
Picking) | 1.1 |
1.85 |'
- >-
'8.2.1 DAC&FW will make the advance release to the Implementing
Agencies (IAs) on six monthly basis based on recommendation of
N-PMAFSC, Annual Action Plan (AAP) of IAs and the due utilization
certificate submitted to meet out the expenses for engaging NPMA, FPO
formation & incubation cost to CBBO and also meeting out the cost of FPO
management cost direct to concerned FPOs account on recommendation of
concerned CBBO and Equity Grant etc. for effective and timely
implementation of the programme. The Implementing Agencies will develop
the payment schedule based on their various stages and component of
payment involved. The Implementing Agencies will raise the demand to
DAC&FW for release of payment. The Implementing Agencies will submit
utilization certificate of last payment released as per GFR for
releasing the next payment to them. In case of training, NABARD and NCDC
will submit to N- PMAFSC the training schedule for a year with tentative
expenditure for training through specialised training institutes
organised through their respective nodal training Institute. DAC&FW will
make due payment to NABARD and NCDC for training through specialised
Institutions based on the demand raised by NABARD and NCDC respectively
and utilisation certificate will be submitted to DAC&FW by both as due.
Further, as regards DAC&FW's share towards Credit Guarantee Fund (CGF)
to be maintained and managed by NABARD and NCDC, the DAC&FW will provide
its matching share to NABARD and NCDC, as the case may be, which in
turn will submit detailed status of utilization to DAC&FW before raising
the further demand for next installment of CGF.'
- >-
'7.5.1 Only those AWS/ARGs of IMD/State Govt. /private agencies should
be considered and notified which are as per standards defined by IMD/WMO
and are certified and approved by IMD/any agency to be notified by the
State/Central govt. These must be optimally operational and be able to
provide real time weather data. AWS/ARG of private agencies should
only be considered in absence of properly functioning AWS/ARGs of IMD/
State Govt. AWS /ARG data sourced for crop insurance should be
transferred on real time basis to National Portal. The detailed
guidelines for sharing of weather data on the Portal will be circulated
separately. 7.5.2 State govt can explore the possibility to create
dense AWS/ARG network on PPP Mode for which GOI will provide 50% of the
viability gap funding. 7.5.3 The following data sources may be used
for validation of on account claims and claims for prevented sowing:'
- source_sentence: >-
Who is considered as the nodal agency for engagement with the Ministry of
Agriculture and Farmers Welfare and Insurance Companies?
sentences:
- >-
'8.2.1 DAC&FW will make the advance release to the Implementing
Agencies (IAs) on six monthly basis based on recommendation of
N-PMAFSC, Annual Action Plan (AAP) of IAs and the due utilization
certificate submitted to meet out the expenses for engaging NPMA, FPO
formation & incubation cost to CBBO and also meeting out the cost of FPO
management cost direct to concerned FPOs account on recommendation of
concerned CBBO and Equity Grant etc. for effective and timely
implementation of the programme. The Implementing Agencies will develop
the payment schedule based on their various stages and component of
payment involved. The Implementing Agencies will raise the demand to
DAC&FW for release of payment. The Implementing Agencies will submit
utilization certificate of last payment released as per GFR for
releasing the next payment to them. In case of training, NABARD and NCDC
will submit to N- PMAFSC the training schedule for a year with tentative
expenditure for training through specialised training institutes
organised through their respective nodal training Institute. DAC&FW will
make due payment to NABARD and NCDC for training through specialised
Institutions based on the demand raised by NABARD and NCDC respectively
and utilisation certificate will be submitted to DAC&FW by both as due.
Further, as regards DAC&FW's share towards Credit Guarantee Fund (CGF)
to be maintained and managed by NABARD and NCDC, the DAC&FW will provide
its matching share to NABARD and NCDC, as the case may be, which in
turn will submit detailed status of utilization to DAC&FW before raising
the further demand for next installment of CGF.'
- >-
' 13.4 Laxmanrao Imandar National Academy for Co-operative
Research & Development (LINAC), Gurugram promoted by NCDC is
designated as Nodal Training Institution at central level for FPOs
registered under Co-operative Societies Act and promoted by NCDC. The
LINAC will work in partnership with other reputed national and regional
training institutions like NIAM, VAMNICOM, MANAGE, NIRD, NCCT, IRMA,
ASCI, State and Central Agriculture Universities, KVK, very reputed
National level Management and Skill Development
Institutions/Universities etc. The LINAC in consultation with NCDC and
DAC&FW will prepare a training module and training schedule for the
ensuing year, which will be got approved by N-PMAFSC. As regards
training expenses, in case of LINAC being nodal agency, the LINAC
through NCDC will claim the expenses from DAC&FW and will also submit
the utilization certificate through NCDC after the training programme is
over. 13.5 DAC&FW in due course may also identify and designate other
training institute(s) as additional Nodal Training Institute at central
level, which will undertake training and skill development partnering
with other national and regional level institutes. 13.6 The central
Nodal Training Institutes will ensure that training programme be held
preferably in same State/UT wherein FPO trainees located are proposed to
participate to reduce the burden on transportation(TA/DA) cost. While
formulating the training schedule, Nodal Training Institutes will ensure
that BoDs, CEOs/Managers and other stakeholders etc. are trained twice
in a year. Nodal Training Institutes will have to make boarding and
lodging arrangements for the trainees and will also reimburse to and
fro journey tickets to the extent of sleeper class train tickets and/or
ordinary bus fare. Nodal Training Institutions will also evolve
methodology to monitor and track the performance of trainees and their
FPO organization to ensure effectiveness of training being provided.'
- >-
'8.1 CSCs under Ministry of Electronics and Information Technology
(MeITY) have been engaged to enrol non-loanee farmers. The Insurance
Companies are required to enter into a separate agreement with CSC
and pay service charges as fixed by DAC&FW, GOI per farmer per village
per season. No other agreement or payment is required to be made for
this purpose. Nodal agency for engagement with Ministry of
Agriculture and Farmers Welfare and Insurance Companies will be CSC-SPV,
a company established under MeITY for carrying out e-governance
initiatives of GoI. 8.2 No charges/fee shall be borne or paid by the
farmers being enrolled through CSCs i.e. CSC-SPV and CSC-VLE 8.3
As per IRDA circular, no separate qualification/certification will be
required for the VLEs of CSCs to facilitate enrolment of non-loanee
farmers. 8.4 All empanelled Insurance Companies will compulsorily be
required to enter into an agreement with CSC for enrolment of
non-loanee farmers and for provision of other defined services to
farmers. 8.5 Other designated intermediaries may be linked with the
Portal in due course. 8.6 Empanelled Insurance Companies have to
necessarily register on the portal and submit list and details of
agents/intermediaries engaged for enrolment of non-loanee farmers in the
beginning of each season within 10 days of award of work in the
State. Further all agents/intermediaries have to work strictly as
per the provisions of the Scheme and IRDA regulations'
model-index:
- name: SentenceTransformer based on BAAI/bge-small-en-v1.5
results:
- task:
type: information-retrieval
name: Information Retrieval
dataset:
name: val evaluator
type: val_evaluator
metrics:
- type: cosine_accuracy@1
value: 0.51
name: Cosine Accuracy@1
- type: cosine_accuracy@5
value: 0.9
name: Cosine Accuracy@5
- type: cosine_accuracy@10
value: 0.96
name: Cosine Accuracy@10
- type: cosine_precision@1
value: 0.51
name: Cosine Precision@1
- type: cosine_precision@5
value: 0.17999999999999997
name: Cosine Precision@5
- type: cosine_precision@10
value: 0.096
name: Cosine Precision@10
- type: cosine_recall@1
value: 0.51
name: Cosine Recall@1
- type: cosine_recall@5
value: 0.9
name: Cosine Recall@5
- type: cosine_recall@10
value: 0.96
name: Cosine Recall@10
- type: cosine_ndcg@5
value: 0.7319026681359824
name: Cosine Ndcg@5
- type: cosine_ndcg@10
value: 0.7503025597337694
name: Cosine Ndcg@10
- type: cosine_ndcg@100
value: 0.7590365063330959
name: Cosine Ndcg@100
- type: cosine_mrr@5
value: 0.6745
name: Cosine Mrr@5
- type: cosine_mrr@10
value: 0.6815000000000002
name: Cosine Mrr@10
- type: cosine_mrr@100
value: 0.6834441946057421
name: Cosine Mrr@100
- type: cosine_map@100
value: 0.6834441946057419
name: Cosine Map@100
- type: dot_accuracy@1
value: 0.51
name: Dot Accuracy@1
- type: dot_accuracy@5
value: 0.9
name: Dot Accuracy@5
- type: dot_accuracy@10
value: 0.96
name: Dot Accuracy@10
- type: dot_precision@1
value: 0.51
name: Dot Precision@1
- type: dot_precision@5
value: 0.17999999999999997
name: Dot Precision@5
- type: dot_precision@10
value: 0.096
name: Dot Precision@10
- type: dot_recall@1
value: 0.51
name: Dot Recall@1
- type: dot_recall@5
value: 0.9
name: Dot Recall@5
- type: dot_recall@10
value: 0.96
name: Dot Recall@10
- type: dot_ndcg@5
value: 0.7319026681359824
name: Dot Ndcg@5
- type: dot_ndcg@10
value: 0.7503025597337692
name: Dot Ndcg@10
- type: dot_ndcg@100
value: 0.7590365063330959
name: Dot Ndcg@100
- type: dot_mrr@5
value: 0.6745
name: Dot Mrr@5
- type: dot_mrr@10
value: 0.6815000000000002
name: Dot Mrr@10
- type: dot_mrr@100
value: 0.6834441946057421
name: Dot Mrr@100
- type: dot_map@100
value: 0.6834441946057419
name: Dot Map@100
SentenceTransformer based on BAAI/bge-small-en-v1.5
This is a sentence-transformers model finetuned from BAAI/bge-small-en-v1.5. It maps sentences & paragraphs to a 384-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more.
Model Details
Model Description
- Model Type: Sentence Transformer
- Base model: BAAI/bge-small-en-v1.5
- Maximum Sequence Length: 512 tokens
- Output Dimensionality: 384 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': 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)
First install the Sentence Transformers library:
pip install -U sentence-transformers
Then you can load this model and run inference.
from sentence_transformers import SentenceTransformer
# Download from the 🤗 Hub
model = SentenceTransformer("SamagraDataGov/embedding_finetuned_test")
# Run inference
sentences = [
'Who is considered as the nodal agency for engagement with the Ministry of Agriculture and Farmers Welfare and Insurance Companies?',
"'8.1 CSCs under Ministry of Electronics and Information Technology (MeITY) have been engaged to enrol non-loanee farmers. The Insurance Companies are required to enter into a separate agreement with CSC and pay service charges as fixed by DAC&FW, GOI per farmer per village per season. No other agreement or payment is required to be made for this purpose. Nodal agency for engagement with Ministry of Agriculture and Farmers Welfare and Insurance Companies will be CSC-SPV, a company established under MeITY for carrying out e-governance initiatives of GoI. 8.2 No charges/fee shall be borne or paid by the farmers being enrolled through CSCs i.e. CSC-SPV and CSC-VLE 8.3 As per IRDA circular, no separate qualification/certification will be required for the VLEs of CSCs to facilitate enrolment of non-loanee farmers. 8.4 All empanelled Insurance Companies will compulsorily be required to enter into an agreement with CSC for enrolment of non-loanee farmers and for provision of other defined services to farmers. 8.5 Other designated intermediaries may be linked with the Portal in due course. 8.6 Empanelled Insurance Companies have to necessarily register on the portal and submit list and details of agents/intermediaries engaged for enrolment of non-loanee farmers in the beginning of each season within 10 days of award of work in the State. Further all agents/intermediaries have to work strictly as per the provisions of the Scheme and IRDA regulations'",
"' 13.4 Laxmanrao Imandar National Academy for Co-operative Research & Development (LINAC), Gurugram promoted by NCDC is designated as Nodal Training Institution at central level for FPOs registered under Co-operative Societies Act and promoted by NCDC. The LINAC will work in partnership with other reputed national and regional training institutions like NIAM, VAMNICOM, MANAGE, NIRD, NCCT, IRMA, ASCI, State and Central Agriculture Universities, KVK, very reputed National level Management and Skill Development Institutions/Universities etc. The LINAC in consultation with NCDC and DAC&FW will prepare a training module and training schedule for the ensuing year, which will be got approved by N-PMAFSC. As regards training expenses, in case of LINAC being nodal agency, the LINAC through NCDC will claim the expenses from DAC&FW and will also submit the utilization certificate through NCDC after the training programme is over. 13.5 DAC&FW in due course may also identify and designate other training institute(s) as additional Nodal Training Institute at central level, which will undertake training and skill development partnering with other national and regional level institutes. 13.6 The central Nodal Training Institutes will ensure that training programme be held preferably in same State/UT wherein FPO trainees located are proposed to participate to reduce the burden on transportation(TA/DA) cost. While formulating the training schedule, Nodal Training Institutes will ensure that BoDs, CEOs/Managers and other stakeholders etc. are trained twice in a year. Nodal Training Institutes will have to make boarding and lodging arrangements for the trainees and will also reimburse to and fro journey tickets to the extent of sleeper class train tickets and/or ordinary bus fare. Nodal Training Institutions will also evolve methodology to monitor and track the performance of trainees and their FPO organization to ensure effectiveness of training being provided.'",
]
embeddings = model.encode(sentences)
print(embeddings.shape)
# [3, 384]
# Get the similarity scores for the embeddings
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [3, 3]
Evaluation
Metrics
Information Retrieval
- Dataset:
val_evaluator - Evaluated with
InformationRetrievalEvaluator
| Metric | Value |
|---|---|
| cosine_accuracy@1 | 0.51 |
| cosine_accuracy@5 | 0.9 |
| cosine_accuracy@10 | 0.96 |
| cosine_precision@1 | 0.51 |
| cosine_precision@5 | 0.18 |
| cosine_precision@10 | 0.096 |
| cosine_recall@1 | 0.51 |
| cosine_recall@5 | 0.9 |
| cosine_recall@10 | 0.96 |
| cosine_ndcg@5 | 0.7319 |
| cosine_ndcg@10 | 0.7503 |
| cosine_ndcg@100 | 0.759 |
| cosine_mrr@5 | 0.6745 |
| cosine_mrr@10 | 0.6815 |
| cosine_mrr@100 | 0.6834 |
| cosine_map@100 | 0.6834 |
| dot_accuracy@1 | 0.51 |
| dot_accuracy@5 | 0.9 |
| dot_accuracy@10 | 0.96 |
| dot_precision@1 | 0.51 |
| dot_precision@5 | 0.18 |
| dot_precision@10 | 0.096 |
| dot_recall@1 | 0.51 |
| dot_recall@5 | 0.9 |
| dot_recall@10 | 0.96 |
| dot_ndcg@5 | 0.7319 |
| dot_ndcg@10 | 0.7503 |
| dot_ndcg@100 | 0.759 |
| dot_mrr@5 | 0.6745 |
| dot_mrr@10 | 0.6815 |
| dot_mrr@100 | 0.6834 |
| dot_map@100 | 0.6834 |
Training Details
Training Hyperparameters
Non-Default Hyperparameters
eval_strategy: stepsper_device_train_batch_size: 32per_device_eval_batch_size: 32learning_rate: 1e-05weight_decay: 0.01num_train_epochs: 1.0warmup_ratio: 0.1load_best_model_at_end: True
All Hyperparameters
Click to expand
overwrite_output_dir: Falsedo_predict: Falseeval_strategy: stepsprediction_loss_only: Trueper_device_train_batch_size: 32per_device_eval_batch_size: 32per_gpu_train_batch_size: Noneper_gpu_eval_batch_size: Nonegradient_accumulation_steps: 1eval_accumulation_steps: Nonetorch_empty_cache_steps: Nonelearning_rate: 1e-05weight_decay: 0.01adam_beta1: 0.9adam_beta2: 0.999adam_epsilon: 1e-08max_grad_norm: 1.0num_train_epochs: 1.0max_steps: -1lr_scheduler_type: linearlr_scheduler_kwargs: {}warmup_ratio: 0.1warmup_steps: 0log_level: passivelog_level_replica: warninglog_on_each_node: Truelogging_nan_inf_filter: Truesave_safetensors: Truesave_on_each_node: Falsesave_only_model: Falserestore_callback_states_from_checkpoint: Falseno_cuda: Falseuse_cpu: Falseuse_mps_device: Falseseed: 42data_seed: Nonejit_mode_eval: Falseuse_ipex: Falsebf16: Falsefp16: Falsefp16_opt_level: O1half_precision_backend: autobf16_full_eval: Falsefp16_full_eval: Falsetf32: Nonelocal_rank: 0ddp_backend: Nonetpu_num_cores: Nonetpu_metrics_debug: Falsedebug: []dataloader_drop_last: Falsedataloader_num_workers: 0dataloader_prefetch_factor: Nonepast_index: -1disable_tqdm: Falseremove_unused_columns: Truelabel_names: Noneload_best_model_at_end: Trueignore_data_skip: Falsefsdp: []fsdp_min_num_params: 0fsdp_config: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}fsdp_transformer_layer_cls_to_wrap: Noneaccelerator_config: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None}deepspeed: Nonelabel_smoothing_factor: 0.0optim: adamw_torchoptim_args: Noneadafactor: Falsegroup_by_length: Falselength_column_name: lengthddp_find_unused_parameters: Noneddp_bucket_cap_mb: Noneddp_broadcast_buffers: Falsedataloader_pin_memory: Truedataloader_persistent_workers: Falseskip_memory_metrics: Trueuse_legacy_prediction_loop: Falsepush_to_hub: Falseresume_from_checkpoint: Nonehub_model_id: Nonehub_strategy: every_savehub_private_repo: Falsehub_always_push: Falsegradient_checkpointing: Falsegradient_checkpointing_kwargs: Noneinclude_inputs_for_metrics: Falseeval_do_concat_batches: Truefp16_backend: autopush_to_hub_model_id: Nonepush_to_hub_organization: Nonemp_parameters:auto_find_batch_size: Falsefull_determinism: Falsetorchdynamo: Noneray_scope: lastddp_timeout: 1800torch_compile: Falsetorch_compile_backend: Nonetorch_compile_mode: Nonedispatch_batches: Nonesplit_batches: Noneinclude_tokens_per_second: Falseinclude_num_input_tokens_seen: Falseneftune_noise_alpha: Noneoptim_target_modules: Nonebatch_eval_metrics: Falseeval_on_start: Falseeval_use_gather_object: Falsebatch_sampler: batch_samplermulti_dataset_batch_sampler: proportional
Training Logs
| Epoch | Step | Training Loss | loss | val_evaluator_cosine_map@100 |
|---|---|---|---|---|
| 0.5172 | 15 | 2.0908 | 1.008 | 0.6834 |
| 1.0 | 29 | - | 1.0080 | 0.6834 |
- The bold row denotes the saved checkpoint.
Framework Versions
- Python: 3.10.14
- Sentence Transformers: 3.0.1
- Transformers: 4.43.4
- PyTorch: 2.4.1+cu121
- Accelerate: 0.33.0
- Datasets: 2.21.0
- Tokenizers: 0.19.1
Citation
BibTeX
Sentence Transformers
@inproceedings{reimers-2019-sentence-bert,
title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
author = "Reimers, Nils and Gurevych, Iryna",
booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
month = "11",
year = "2019",
publisher = "Association for Computational Linguistics",
url = "https://arxiv.org/abs/1908.10084",
}
GISTEmbedLoss
@misc{solatorio2024gistembed,
title={GISTEmbed: Guided In-sample Selection of Training Negatives for Text Embedding Fine-tuning},
author={Aivin V. Solatorio},
year={2024},
eprint={2402.16829},
archivePrefix={arXiv},
primaryClass={cs.LG}
}