metadata

tags:
  - sentence-transformers
  - sentence-similarity
  - feature-extraction
  - generated_from_trainer
  - dataset_size:29547
  - loss:MultipleNegativesRankingLoss
base_model: BAAI/bge-small-en-v1.5
widget:
  - source_sentence: >-
      Are there any ADGM-specific guidelines or best practices for integrating
      anti-money laundering (AML) compliance into our technology and financial
      systems to manage operational risks effectively?
    sentences:
      - >-
        42) DISCLOSURE REQUIREMENTS . Material Exploration and drilling results
        Rule 12.5.1 sets out the reporting requirements relevant to disclosures
        of material Exploration and drilling results in relation to Petroleum
        Resources. Such disclosures should be presented in a factual and
        balanced manner, and contain sufficient information to allow investors
        and their advisers to make an informed judgement of its materiality.
        Care needs to be taken to ensure that a disclosure does not suggest,
        without reasonable grounds, that commercially recoverable or potentially
        recoverable quantities of Petroleum have been discovered, in the absence
        of determining and disclosing estimates of Petroleum Resources in
        accordance with Chapter 12 and the PRMS.
      - >-
        55) DIGITAL SECURITIES SETTLEMENT Digital Settlement Facilities (DSFs)
        For the purposes of this Guidance and distinct from RCHs, the FSRA will
        consider DSFs suitable for the purposes of settlement (MIR Rule 3.8) and
        custody (MIR Rule 2.10) of Digital Securities. A DSF, holding an FSP for
        Providing Custody, may provide custody and settlement services in
        Digital Securities for RIEs and MTFs (as applicable). Therefore, for the
        purposes of custody and settlement of Digital Securities, the
        arrangements that a RIE or MTF would normally have in place with a RCH
        can be replaced with arrangements provided by a DSF, provided that
        certain requirements, as described in this section, are met.
      - >-
        Part 6.Chapter 3.59.(1) The Regulator shall have the power to require an
        Institution in Resolution, or any of its Group Entities, to provide any
        services or facilities (excluding any financial support) that are
        necessary to enable the Recipient to operate the transferred business
        effectively, including where the Institution under Resolution or
        relevant Group Entity has entered into Insolvency Proceedings.
  - source_sentence: >-
      Can you provide further clarification on the specific measures deemed
      adequate for handling conflicts of interest related to the provision and
      management of credit within an Authorised Person's organization?
    sentences:
      - >-
        Part 19.Chapter 2.233.(3) If the Regulator considers that an auditor or
        actuary has committed a contravention of these Regulations, it may
        disqualify the auditor or actuary from being the auditor of, or (as the
        case may be), from acting as an actuary for, any Authorised Person,
        Recognised Body or Reporting Entity or any particular class thereof.
      - >-
        43) REGULATORY REQUIREMENTS FOR AUTHORISED PERSONS ENGAGED IN REGULATED
        ACTIVITIES IN RELATION TO VIRTUAL ASSETS Anti-Money Laundering and
        Countering Financing of Terrorism In order to develop a robust and
        sustainable regulatory framework for Virtual Assets, FSRA is of the view
        that a comprehensive application of its AML/CFT framework should be in
        place, including full compliance with, among other things, the: a) UAE
        AML/CFT Federal Laws, including the UAE Cabinet Resolution No. (10) of
        2019 Concerning the Executive Regulation of the Federal Law No. 20 of
        2018 concerning Anti-Money Laundering and Combating Terrorism Financing;
        b) UAE Cabinet Resolution 20 of 2019 concerning the procedures of
        dealing with those listed under the UN sanctions list and UAE/local
        terrorist lists issued by the Cabinet, including the FSRA AML and
        Sanctions Rules and Guidance (“AML Rules”) or such other AML rules as
        may be applicable in ADGM from time to time; and c) adoption of
        international best practices (including the FATF Recommendations).
      - >-
        4.4.2.(4) An Authorised Person with one or more branches outside the
        ADGM must implement and maintain Credit Risk policies adapted to each
        local market and its regulatory conditions.
  - source_sentence: >-
      How does the ADGM enforce the Market Abuse Provisions, such as those
      outlined in section 92 of the FSMR, especially for Accepted Spot
      Commodities, and what are the reporting obligations for companies in
      relation to market abuse and transaction reporting?
    sentences:
      - >-
        6.2.6.(b) If appointed, the Trustee must also take reasonable steps to
        ensure that its Employees comply with IFR 6.2.6(a) (i)- (iv).
      - >-
        8.3.2.Guidance on CDD.9. When employing an eKYC System to assist with
        CDD, a Relevant Person should: a. ensure that it has a thorough
        understanding of the eKYC System itself and the risks of eKYC, including
        those outlined by relevant guidance from FATF and other international
        standard setting bodies; b. comply with all the Rules of the Regulator
        relevant to eKYC including, but not limited to, applicable requirements
        regarding the business risk assessment, as per Rule 6.1, and
        outsourcing, as per Rule 9.3; c. combine eKYC with transaction
        monitoring, anti-fraud and cyber-security measures to support a wider
        framework preventing applicable Financial Crime; and d. take appropriate
        steps to identify, assess and mitigate the risk of the eKYC system being
        misused for the purposes of Financial Crime.
      - >-
        81) REGULATORY REQUIREMENTS - SPOT COMMODITY ACTIVITIES Market Abuse and
        Transaction Reporting (FSMR) Importantly, the Market Abuse Provisions
        (including section 92) in Part 8 of FSMR specifically cover Market Abuse
        Behaviour in relation to Accepted Spot Commodities admitted to trading
        on an RIE, MTF or OTF. In this regard, the FSRA imposes the same high
        regulatory standards to Accepted Spot Commodities traded on RIEs, MTFs
        or OTFs as it does to Financial Instruments traded on RIEs, MTFs or
        OTFs.
  - source_sentence: >-
      Can the ADGM provide examples of legal risks associated with
      securitisation that Authorised Persons should particularly be aware of and
      manage?
    sentences:
      - >-
        6.Introduction.Guidance.1. This Chapter includes the detailed Rules and
        associated guidance in respect of a firm's obligation to manage
        effectively its Exposures to Operational Risk. Operational Risk refers
        to the risk of incurring losses due to the failure of systems,
        processes, and personnel to perform expected tasks. Operational Risk
        losses also include losses arising out of legal risk. This Chapter aims
        to ensure that an Authorised Person has a robust Operational Risk
        management framework commensurate with the nature, scale and complexity
        of its operations and that it holds sufficient regulatory capital
        against Operational Risk Exposures.
      - >-
        APP4.A4.3.19 Own estimate haircuts . If an Authorised Person fails to
        comply with Rule A4.3.18, the Regulator may revoke its approval for the
        Authorised Person to use own estimate haircuts. The Authorised Person
        may also be required to revise its estimates for the purpose of
        calculating regulatory Capital Requirements if its estimates of E*, does
        not adequately reflect its Exposure to Counterparty Credit Risk.
      - >-
        2.5.6 Financial risk . All applicants are required to demonstrate they
        have a sound initial capital base and funding and must be able to meet
        the relevant prudential requirements of ADGM legislation, on an ongoing
        basis. This includes holding enough capital resources to cover expenses
        even if expected revenue takes time to materialise. Start-ups can
        encounter greater financial risks as they seek to establish and grow a
        new business.
  - source_sentence: >-
      Could you provide detailed guidance on the acceptable threshold for
      "significant loss" to clients in the context of IT infrastructure
      resilience for virtual asset service providers?
    sentences:
      - >-
        APP8.A8.11.1 An Insurer must calculate the asset management risk
        component in respect of a Long Term Insurance Fund according to the
        method set out in Rule A4.13, applied as though all references in that
        Rule to an Insurer were instead references to that fund.
      - >-
        60) REGULATORY REQUIREMENTS FOR AUTHORISED PERSONS ENGAGED IN REGULATED
        ACTIVITIES IN RELATION TO VIRTUAL ASSETS Security measures and
        procedures IT infrastructures should be strong enough to resist, without
        significant loss to Clients, a number of scenarios, including but not
        limited to: accidental destruction or breach of data, collusion or
        leakage of information by employees/former employees, successful hack of
        a cryptographic and hardware security module or server, or access by
        hackers of any single set of encryption/decryption keys that could
        result in a complete system breach.
      - >-
        APP4.A4.3.17.(2) An Authorised Person must not use own estimate haircuts
        unless it has received approval to adopt the internal models approach to
        calculate the Market Risk Capital Requirement.
pipeline_tag: sentence-similarity
library_name: sentence-transformers
metrics:
  - dot_score_accuracy@10
  - dot_score_precision@10
  - dot_score_recall@10
  - dot_score_ndcg@10
  - dot_score_mrr@10
  - dot_score_map@10
model-index:
  - name: SentenceTransformer based on BAAI/bge-small-en-v1.5
    results:
      - task:
          type: information-retrieval
          name: Information Retrieval
        dataset:
          name: qa eval
          type: qa_eval
        metrics:
          - type: dot_score_accuracy@10
            value: 0.8902439024390244
            name: Dot Score Accuracy@10
          - type: dot_score_precision@10
            value: 0.09842180774748924
            name: Dot Score Precision@10
          - type: dot_score_recall@10
            value: 0.8141678622668578
            name: Dot Score Recall@10
          - type: dot_score_ndcg@10
            value: 0.6920833764452019
            name: Dot Score Ndcg@10
          - type: dot_score_mrr@10
            value: 0.6942683780829393
            name: Dot Score Mrr@10
          - type: dot_score_map@10
            value: 0.6312994062801272
            name: Dot Score Map@10

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 512-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: 512 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': 512, '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("raul-delarosa99/bge-small-en-v1.5-RIRAG_ObliQA")
# Run inference
sentences = [
    'Could you provide detailed guidance on the acceptable threshold for "significant loss" to clients in the context of IT infrastructure resilience for virtual asset service providers?',
    '60) REGULATORY REQUIREMENTS FOR AUTHORISED PERSONS ENGAGED IN REGULATED ACTIVITIES IN RELATION TO VIRTUAL ASSETS Security measures and procedures IT infrastructures should be strong enough to resist, without significant loss to Clients, a number of scenarios, including but not limited to: accidental destruction or breach of data, collusion or leakage of information by employees/former employees, successful hack of a cryptographic and hardware security module or server, or access by hackers of any single set of encryption/decryption keys that could result in a complete system breach.',
    'APP8.A8.11.1 An Insurer must calculate the asset management risk component in respect of a Long Term Insurance Fund according to the method set out in Rule A4.13, applied as though all references in that Rule to an Insurer were instead references to that fund.',
]
embeddings = model.encode(sentences)
print(embeddings.shape)
# [3, 512]

# Get the similarity scores for the embeddings
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [3, 3]

Evaluation

Metrics

Information Retrieval

Dataset: qa_eval
Evaluated with InformationRetrievalEvaluator

Metric	Fine Tunned	Base Model
dot_score_accuracy@10	0.8902	0.7909
dot_score_precision@10	0.0984	0.0842
dot_score_recall@10	0.8142	0.7135
dot_score_ndcg@10	0.6921	0.6009
dot_score_mrr@10	0.6943	0.6015
dot_score_map@10	0.6313	0.5462

Training Details

Training Dataset

Unnamed Dataset

Size: 29,547 training samples
Columns: anchor and positive
Approximate statistics based on the first 1000 samples:
anchor positive
type string string
details
min: 15 tokens
mean: 34.89 tokens
max: 96 tokens

min: 25 tokens
mean: 122.21 tokens
max: 512 tokens

	anchor	positive
type	string	string
details	min: 15 tokens mean: 34.89 tokens max: 96 tokens	min: 25 tokens mean: 122.21 tokens max: 512 tokens

Samples:

anchor	positive
`Under Rules 7.3.2 and 7.3.3, what are the two specific conditions related to the maturity of a financial instrument that would trigger a disclosure requirement?`	`7.3.4 Events that trigger a disclosure. For the purposes of Rules 7.3.2 and 7.3.3, a Person is taken to hold Financial Instruments in or relating to a Reporting Entity, if the Person holds a Financial Instrument that on its maturity will confer on him: (1) an unconditional right to acquire the Financial Instrument; or (2) the discretion as to his right to acquire the Financial Instrument.`
`Best Execution and Transaction Handling: What constitutes 'Best Execution' under Rule 6.5 in the context of virtual assets, and how should Authorised Persons document and demonstrate this?`	17.1.4 The following COBS Rules should be read as applying to all Transactions undertaken by an Authorised Person conducting a Regulated Activity in relation to Virtual Assets, irrespective of any restrictions on application or any exception to these Rules elsewhere in COBS - (a) Rule 3.4 (Suitability); (b) Rule 6.5 (Best Execution); (c) Rule 6.7 (Aggregation and Allocation); (d) Rule 6.10 (Confirmation Notes); (e) Rule 6.11 (Periodic Statements); and (f) Chapter 12 (Key Information and Client Agreement).
`How does the FSRA define and evaluate "principal risks and uncertainties" for a Petroleum Reporting Entity, particularly for the remaining six months of the financial year?`	10.1.7.(2) A Reporting Entity must: (a) prepare such report: (i) for the first six months of each financial year or period, and if there is a change to the accounting reference date, prepare such report in respect of the period up to the old accounting reference date; and (ii) in accordance with the applicable IFRS standards or other standards acceptable to the Regulator; (b) ensure the financial statements have either been audited or reviewed by auditors, and the audit or review by the auditor is included within the report; and (c) ensure that the report includes: (i) except in the case of a Mining Exploration Reporting Entity or a Petroleum Exploration Reporting Entity, an indication of important events that have occurred during the first six months of the financial year, and their impact on the financial statements; (ii) except in the case of a Mining Exploration Reporting Entity or a Petroleum Exploration Reporting Entity, a description of the principal risks and uncertainties for the remaining six months of the financial year; and (iii) a condensed set of financial statements, an interim management report and associated responsibility statements.

Loss: MultipleNegativesRankingLoss with these parameters:

{
    "scale": 20.0,
    "similarity_fct": "dot_score"
}

Training Hyperparameters

Non-Default Hyperparameters

eval_strategy: epoch
per_device_train_batch_size: 64
per_device_eval_batch_size: 512
gradient_accumulation_steps: 4
learning_rate: 2e-05
num_train_epochs: 15
lr_scheduler_type: cosine
warmup_ratio: 0.1
bf16: True
load_best_model_at_end: True
optim: adamw_torch_fused
batch_sampler: no_duplicates

All Hyperparameters

Click to expand

overwrite_output_dir: False
do_predict: False
eval_strategy: epoch
prediction_loss_only: True
per_device_train_batch_size: 64
per_device_eval_batch_size: 512
per_gpu_train_batch_size: None
per_gpu_eval_batch_size: None
gradient_accumulation_steps: 4
eval_accumulation_steps: None
torch_empty_cache_steps: None
learning_rate: 2e-05
weight_decay: 0.0
adam_beta1: 0.9
adam_beta2: 0.999
adam_epsilon: 1e-08
max_grad_norm: 1.0
num_train_epochs: 15
max_steps: -1
lr_scheduler_type: cosine
lr_scheduler_kwargs: {}
warmup_ratio: 0.1
warmup_steps: 0
log_level: passive
log_level_replica: warning
log_on_each_node: True
logging_nan_inf_filter: True
save_safetensors: True
save_on_each_node: False
save_only_model: False
restore_callback_states_from_checkpoint: False
no_cuda: False
use_cpu: False
use_mps_device: False
seed: 42
data_seed: None
jit_mode_eval: False
use_ipex: False
bf16: True
fp16: False
fp16_opt_level: O1
half_precision_backend: auto
bf16_full_eval: False
fp16_full_eval: False
tf32: None
local_rank: 0
ddp_backend: None
tpu_num_cores: None
tpu_metrics_debug: False
debug: []
dataloader_drop_last: False
dataloader_num_workers: 0
dataloader_prefetch_factor: None
past_index: -1
disable_tqdm: False
remove_unused_columns: True
label_names: None
load_best_model_at_end: True
ignore_data_skip: False
fsdp: []
fsdp_min_num_params: 0
fsdp_config: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}
fsdp_transformer_layer_cls_to_wrap: None
accelerator_config: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None}
deepspeed: None
label_smoothing_factor: 0.0
optim: adamw_torch_fused
optim_args: None
adafactor: False
group_by_length: False
length_column_name: length
ddp_find_unused_parameters: None
ddp_bucket_cap_mb: None
ddp_broadcast_buffers: False
dataloader_pin_memory: True
dataloader_persistent_workers: False
skip_memory_metrics: True
use_legacy_prediction_loop: False
push_to_hub: False
resume_from_checkpoint: None
hub_model_id: None
hub_strategy: every_save
hub_private_repo: False
hub_always_push: False
gradient_checkpointing: False
gradient_checkpointing_kwargs: None
include_inputs_for_metrics: False
eval_do_concat_batches: True
fp16_backend: auto
push_to_hub_model_id: None
push_to_hub_organization: None
mp_parameters:
auto_find_batch_size: False
full_determinism: False
torchdynamo: None
ray_scope: last
ddp_timeout: 1800
torch_compile: False
torch_compile_backend: None
torch_compile_mode: None
dispatch_batches: None
split_batches: None
include_tokens_per_second: False
include_num_input_tokens_seen: False
neftune_noise_alpha: None
optim_target_modules: None
batch_eval_metrics: False
eval_on_start: False
use_liger_kernel: False
eval_use_gather_object: False
batch_sampler: no_duplicates
multi_dataset_batch_sampler: proportional

Training Logs

Click to expand

Epoch	Step	Training Loss	qa_eval_dot_score_map@10
0.0087	1	1.9006	-
0.0173	2	1.9774	-
0.0260	3	1.8898	-
0.0346	4	1.7339	-
0.0433	5	1.7743	-
0.0519	6	1.8456	-
0.0606	7	1.8348	-
0.0693	8	1.7493	-
0.0779	9	1.6397	-
0.0866	10	1.6803	-
0.0952	11	1.6503	-
0.1039	12	1.7065	-
0.1126	13	1.864	-
0.1212	14	1.7811	-
0.1299	15	1.6896	-
0.1385	16	1.7036	-
0.1472	17	1.769	-
0.1558	18	1.8405	-
0.1645	19	1.8686	-
0.1732	20	1.7136	-
0.1818	21	1.9135	-
0.1905	22	1.9542	-
0.1991	23	1.7373	-
0.2078	24	1.7295	-
0.2165	25	1.6764	-
0.2251	26	1.6606	-
0.2338	27	1.5261	-
0.2424	28	1.6864	-
0.2511	29	1.6683	-
0.2597	30	1.6443	-
0.2684	31	1.587	-
0.2771	32	1.5673	-
0.2857	33	1.575	-
0.2944	34	1.5552	-
0.3030	35	1.6614	-
0.3117	36	1.5392	-
0.3203	37	1.5684	-
0.3290	38	1.3392	-
0.3377	39	1.3909	-
0.3463	40	1.3444	-
0.3550	41	1.3642	-
0.3636	42	1.3242	-
0.3723	43	1.4779	-
0.3810	44	1.2574	-
0.3896	45	1.3639	-
0.3983	46	1.2723	-
0.4069	47	1.2563	-
0.4156	48	1.1769	-
0.4242	49	1.2596	-
0.4329	50	1.2703	-
0.4416	51	1.3731	-
0.4502	52	1.163	-
0.4589	53	1.4455	-
0.4675	54	1.0285	-
0.4762	55	1.1616	-
0.4848	56	1.1341	-
0.4935	57	1.163	-
0.5022	58	1.187	-
0.5108	59	1.0557	-
0.5195	60	1.1115	-
0.5281	61	1.0469	-
0.5368	62	1.2311	-
0.5455	63	0.9378	-
0.5541	64	1.0355	-
0.5628	65	1.4079	-
0.5714	66	1.1047	-
0.5801	67	0.9298	-
0.5887	68	1.2011	-
0.5974	69	1.0149	-
0.6061	70	1.1661	-
0.6147	71	0.8674	-
0.6234	72	1.0458	-
0.6320	73	0.9858	-
0.6407	74	1.2019	-
0.6494	75	0.9794	-
0.6580	76	0.9604	-
0.6667	77	1.0405	-
0.6753	78	1.1605	-
0.6840	79	1.0779	-
0.6926	80	1.16	-
0.7013	81	1.2139	-
0.7100	82	1.0696	-
0.7186	83	1.1806	-
0.7273	84	1.1762	-
0.7359	85	0.975	-
0.7446	86	1.1304	-
0.7532	87	1.1431	-
0.7619	88	1.0669	-
0.7706	89	1.0858	-
0.7792	90	1.0494	-
0.7879	91	1.0815	-
0.7965	92	0.9833	-
0.8052	93	1.1571	-
0.8139	94	0.9771	-
0.8225	95	0.88	-
0.8312	96	0.9501	-
0.8398	97	1.2409	-
0.8485	98	1.1644	-
0.8571	99	1.1176	-
0.8658	100	0.8971	-
0.8745	101	1.032	-
0.8831	102	1.0456	-
0.8918	103	0.878	-
0.9004	104	0.9627	-
0.9091	105	0.7828	-
0.9177	106	0.9415	-
0.9264	107	0.9118	-
0.9351	108	1.0132	-
0.9437	109	0.9399	-
0.9524	110	0.9332	-
0.9610	111	0.9197	-
0.9697	112	0.9294	-
0.9784	113	1.1636	-
0.9870	114	0.9484	-
0.9957	115	1.1682	-
1.0043	116	0.6774	0.6055
1.0065	117	0.5901	-
1.0152	118	0.9436	-
1.0238	119	1.04	-
1.0325	120	0.8038	-
1.0411	121	0.8559	-
1.0498	122	1.1118	-
1.0584	123	0.8408	-
1.0671	124	0.9209	-
1.0758	125	0.7588	-
1.0844	126	0.8141	-
1.0931	127	0.7161	-
1.1017	128	0.7939	-
1.1104	129	1.0256	-
1.1190	130	0.8305	-
1.1277	131	0.8177	-
1.1364	132	0.8632	-
1.1450	133	0.9084	-
1.1537	134	1.0142	-
1.1623	135	1.2425	-
1.1710	136	0.8622	-
1.1797	137	1.0148	-
1.1883	138	1.1104	-
1.1970	139	1.0222	-
1.2056	140	0.9621	-
1.2143	141	0.8216	-
1.2229	142	0.8159	-
1.2316	143	0.7278	-
1.2403	144	0.9867	-
1.2489	145	1.0389	-
1.2576	146	0.8307	-
1.2662	147	0.943	-
1.2749	148	0.8681	-
1.2835	149	0.9374	-
1.2922	150	0.9335	-
1.3009	151	1.0568	-
1.3095	152	0.8154	-
1.3182	153	1.1342	-
1.3268	154	0.9235	-
1.3355	155	0.8155	-
1.3442	156	0.7959	-
1.3528	157	0.9586	-
1.3615	158	0.811	-
1.3701	159	0.8997	-
1.3788	160	0.94	-
1.3874	161	0.7088	-
1.3961	162	0.9682	-
1.4048	163	0.8308	-
1.4134	164	0.7775	-
1.4221	165	0.9181	-
1.4307	166	0.9467	-
1.4394	167	0.9216	-
1.4481	168	0.877	-
1.4567	169	0.9788	-
1.4654	170	0.9094	-
1.4740	171	0.8269	-
1.4827	172	0.6962	-
1.4913	173	0.9412	-
1.5	174	1.1315	-
1.5087	175	0.7554	-
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1.5260	177	0.8115	-
1.5346	178	0.8798	-
1.5433	179	0.8248	-
1.5519	180	0.712	-
1.5606	181	1.0581	-
1.5693	182	0.9755	-
1.5779	183	0.8808	-
1.5866	184	0.8207	-
1.5952	185	0.8627	-
1.6039	186	0.9566	-
1.6126	187	0.6412	-
1.6212	188	0.7806	-
1.6299	189	0.8012	-
1.6385	190	0.9907	-
1.6472	191	0.8961	-
1.6558	192	0.7042	-
1.6645	193	0.8451	-
1.6732	194	1.0143	-
1.6818	195	0.9189	-
1.6905	196	0.8588	-
1.6991	197	0.9458	-
1.7078	198	0.9716	-
1.7165	199	0.9424	-
1.7251	200	0.9257	-
1.7338	201	0.838	-
1.7424	202	1.0036	-
1.7511	203	0.8486	-
1.7597	204	1.0168	-
1.7684	205	0.8885	-
1.7771	206	0.8234	-
1.7857	207	1.0461	-
1.7944	208	0.9209	-
1.8030	209	0.9177	-
1.8117	210	0.8683	-
1.8203	211	0.799	-
1.8290	212	0.8423	-
1.8377	213	1.0716	-
1.8463	214	1.0086	-
1.8550	215	0.9491	-
1.8636	216	0.876	-
1.8723	217	0.753	-
1.8810	218	1.0414	-
1.8896	219	0.7402	-
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1.9069	221	0.7436	-
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1.9416	225	0.8423	-
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1.9589	227	0.7574	-
1.9675	228	0.8446	-
1.9762	229	0.8368	-
1.9848	230	0.9048	-
1.9935	231	0.973	-
2.0022	232	0.8729	0.6196
2.0043	233	0.2569	-
2.0130	234	0.8799	-
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2.0303	236	0.7625	-
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2.0649	240	0.685	-
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2.1515	250	0.7587	-
2.1602	251	1.1161	-
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2.1948	255	0.9162	-
2.2035	256	0.8561	-
2.2121	257	0.7099	-
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2.2381	260	0.6752	-
2.2468	261	0.9701	-
2.2554	262	0.7685	-
2.2641	263	0.845	-
2.2727	264	0.7365	-
2.2814	265	0.7538	-
2.2900	266	0.7401	-
2.2987	267	0.9054	-
2.3074	268	0.7733	-
2.3160	269	0.9947	-
2.3247	270	0.7427	-
2.3333	271	0.757	-
2.3420	272	0.731	-
2.3506	273	0.719	-
2.3593	274	0.7435	-
2.3680	275	0.7489	-
2.3766	276	0.9108	-
2.3853	277	0.6027	-
2.3939	278	0.8813	-
2.4026	279	0.7801	-
2.4113	280	0.6287	-
2.4199	281	0.7375	-
2.4286	282	0.824	-
2.4372	283	0.8206	-
2.4459	284	0.7805	-
2.4545	285	0.8443	-
2.4632	286	0.8887	-
2.4719	287	0.6984	-
2.4805	288	0.6718	-
2.4892	289	0.8184	-
2.4978	290	1.0259	-
2.5065	291	0.7422	-
2.5152	292	0.7539	-
2.5238	293	0.7422	-
2.5325	294	0.81	-
2.5411	295	0.8015	-
2.5498	296	0.613	-
2.5584	297	0.8623	-
2.5671	298	1.0711	-
2.5758	299	0.76	-
2.5844	300	0.7372	-
2.5931	301	0.7346	-
2.6017	302	0.8559	-
2.6104	303	0.5926	-
2.6190	304	0.6945	-
2.6277	305	0.6985	-
2.6364	306	0.8489	-
2.6450	307	0.8123	-
2.6537	308	0.745	-
2.6623	309	0.6543	-
2.6710	310	0.9022	-
2.6797	311	0.862	-
2.6883	312	0.757	-
2.6970	313	0.8539	-
2.7056	314	0.9205	-
2.7143	315	0.8702	-
2.7229	316	0.8144	-
2.7316	317	0.8202	-
2.7403	318	0.9092	-
2.7489	319	0.7811	-
2.7576	320	0.8792	-
2.7662	321	0.8316	-
2.7749	322	0.8053	-
2.7835	323	0.9033	-
2.7922	324	0.8172	-
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2.8095	326	0.8106	-
2.8182	327	0.7183	-
2.8268	328	0.7571	-
2.8355	329	0.9051	-
2.8442	330	0.8819	-
2.8528	331	0.96	-
2.8615	332	0.78	-
2.8701	333	0.6932	-
2.8788	334	0.8553	-
2.8874	335	0.8483	-
2.8961	336	0.6056	-
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2.9221	339	0.5951	-
2.9307	340	0.761	-
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2.9567	343	0.7565	-
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2.9740	345	0.6321	-
2.9827	346	0.903	-
2.9913	347	0.9233	-
3.0	348	0.8918	0.6255
3.0022	349	0.1279	-
3.0108	350	0.7773	-
3.0195	351	0.6327	-
3.0281	352	0.8916	-
3.0368	353	0.5167	-
3.0455	354	0.7534	-
3.0541	355	0.7801	-
3.0628	356	0.7414	-
3.0714	357	0.6463	-
3.0801	358	0.5396	-
3.0887	359	0.6017	-
3.0974	360	0.5227	-
3.1061	361	0.7126	-
3.1147	362	0.72	-
3.1234	363	0.5806	-
3.1320	364	0.7322	-
3.1407	365	0.6927	-
3.1494	366	0.6769	-
3.1580	367	0.9597	-
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3.1840	370	0.8548	-
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3.2013	372	0.764	-
3.2100	373	0.7351	-
3.2186	374	0.7067	-
3.2273	375	0.6169	-
3.2359	376	0.6254	-
3.2446	377	0.885	-
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3.2619	379	0.7562	-
3.2706	380	0.6885	-
3.2792	381	0.6008	-
3.2879	382	0.7576	-
3.2965	383	0.7722	-
3.3052	384	0.7928	-
3.3139	385	0.8219	-
3.3225	386	0.6765	-
3.3312	387	0.734	-
3.3398	388	0.7175	-
3.3485	389	0.6636	-
3.3571	390	0.7042	-
3.3658	391	0.6494	-
3.3745	392	0.8241	-
3.3831	393	0.5427	-
3.3918	394	0.8621	-
3.4004	395	0.7231	-
3.4091	396	0.6559	-
3.4177	397	0.6104	-
3.4264	398	0.7446	-
3.4351	399	0.6819	-
3.4437	400	0.8372	-
3.4524	401	0.6876	-
3.4610	402	0.8287	-
3.4697	403	0.5788	-
3.4784	404	0.6705	-
3.4870	405	0.695	-
3.4957	406	0.8201	-
3.5043	407	0.7945	-
3.5130	408	0.6987	-
3.5216	409	0.6608	-
3.5303	410	0.7317	-
3.5390	411	0.7741	-
3.5476	412	0.5483	-
3.5563	413	0.7905	-
3.5649	414	0.992	-
3.5736	415	0.7882	-
3.5823	416	0.657	-
3.5909	417	0.6594	-
3.5996	418	0.685	-
3.6082	419	0.6642	-
3.6169	420	0.5495	-
3.6255	421	0.7218	-
3.6342	422	0.7213	-
3.6429	423	0.7952	-
3.6515	424	0.7017	-
3.6602	425	0.6022	-
3.6688	426	0.7381	-
3.6775	427	0.8468	-
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3.6948	429	0.7335	-
3.7035	430	0.8116	-
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3.7208	432	0.7372	-
3.7294	433	0.7981	-
3.7381	434	0.7403	-
3.7468	435	0.7155	-
3.7554	436	0.8701	-
3.7641	437	0.7498	-
3.7727	438	0.7587	-
3.7814	439	0.8279	-
3.7900	440	0.7874	-
3.7987	441	0.7485	-
3.8074	442	0.7507	-
3.8160	443	0.677	-
3.8247	444	0.6333	-
3.8333	445	0.8852	-
3.8420	446	0.8133	-
3.8506	447	0.8243	-
3.8593	448	0.799	-
3.8680	449	0.5416	-
3.8766	450	0.7698	-
3.8853	451	0.7377	-
3.8939	452	0.6497	-
3.9026	453	0.5655	-
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3.9286	456	0.6761	-
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3.9545	459	0.6768	-
3.9632	460	0.7143	-
3.9719	461	0.6354	-
3.9805	462	0.8287	-
3.9892	463	0.8693	-
3.9978	464	0.8556	-
4.0065	465	0.1944	0.6289
4.0087	466	0.6191	-
4.0173	467	0.5704	-
4.0260	468	0.7962	-
4.0346	469	0.5724	-
4.0433	470	0.6306	-
4.0519	471	0.7907	-
4.0606	472	0.6824	-
4.0693	473	0.5694	-
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4.0866	475	0.5828	-
4.0952	476	0.4895	-
4.1039	477	0.6107	-
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4.1212	479	0.6403	-
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4.1472	482	0.6679	-
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4.1732	485	0.6347	-
4.1818	486	0.7909	-
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4.1991	488	0.6485	-
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4.2165	490	0.6418	-
4.2251	491	0.5497	-
4.2338	492	0.4937	-
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4.2511	494	0.7473	-
4.2597	495	0.6607	-
4.2684	496	0.6082	-
4.2771	497	0.6264	-
4.2857	498	0.7039	-
4.2944	499	0.6696	-
4.3030	500	0.8482	-
4.3117	501	0.6083	-
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4.3290	503	0.6899	-
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4.3550	506	0.7	-
4.3636	507	0.6006	-
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4.3810	509	0.6257	-
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4.3983	511	0.6165	-
4.4069	512	0.6916	-
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4.4416	516	0.6939	-
4.4502	517	0.6063	-
4.4589	518	0.8358	-
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4.5195	525	0.7055	-
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4.5368	527	0.7006	-
4.5455	528	0.5229	-
4.5541	529	0.644	-
4.5628	530	0.9475	-
4.5714	531	0.7377	-
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4.5974	534	0.567	-
4.6061	535	0.6702	-
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4.6234	537	0.7309	-
4.6320	538	0.6186	-
4.6407	539	0.7609	-
4.6494	540	0.6534	-
4.6580	541	0.631	-
4.6667	542	0.6848	-
4.6753	543	0.7369	-
4.6840	544	0.6701	-
4.6926	545	0.7026	-
4.7013	546	0.8015	-
4.7100	547	0.7156	-
4.7186	548	0.777	-
4.7273	549	0.7183	-
4.7359	550	0.6676	-
4.7446	551	0.7282	-
4.7532	552	0.8139	-
4.7619	553	0.6971	-
4.7706	554	0.789	-
4.7792	555	0.7111	-
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4.7965	557	0.6932	-
4.8052	558	0.7179	-
4.8139	559	0.6709	-
4.8225	560	0.5513	-
4.8312	561	0.6358	-
4.8398	562	0.8794	-
4.8485	563	0.8012	-
4.8571	564	0.7704	-
4.8658	565	0.5793	-
4.8745	566	0.6684	-
4.8831	567	0.7118	-
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4.9004	569	0.6474	-
4.9091	570	0.4803	-
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4.9264	572	0.5408	-
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4.9437	574	0.6174	-
4.9524	575	0.673	-
4.9610	576	0.605	-
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4.9784	578	0.7883	-
4.9870	579	0.6792	-
4.9957	580	0.8864	-
5.0043	581	0.4167	0.6309
5.0065	582	0.361	-
5.0152	583	0.5761	-
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5.0325	585	0.5485	-
5.0411	586	0.5697	-
5.0498	587	0.7429	-
5.0584	588	0.5572	-
5.0671	589	0.6251	-
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5.1104	594	0.7192	-
5.1190	595	0.5647	-
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5.1450	598	0.5949	-
5.1537	599	0.6975	-
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5.1710	601	0.5849	-
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5.1970	604	0.7155	-
5.2056	605	0.6464	-
5.2143	606	0.5768	-
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5.2576	611	0.6033	-
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5.2749	613	0.5909	-
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5.3095	617	0.5592	-
5.3182	618	0.8025	-
5.3268	619	0.6697	-
5.3355	620	0.5803	-
5.3442	621	0.5033	-
5.3528	622	0.6487	-
5.3615	623	0.5773	-
5.3701	624	0.6942	-
5.3788	625	0.705	-
5.3874	626	0.4615	-
5.3961	627	0.6896	-
5.4048	628	0.574	-
5.4134	629	0.5646	-
5.4221	630	0.6161	-
5.4307	631	0.62	-
5.4394	632	0.6008	-
5.4481	633	0.6211	-
5.4567	634	0.6955	-
5.4654	635	0.653	-
5.4740	636	0.5276	-
5.4827	637	0.4808	-
5.4913	638	0.7161	-
5.5	639	0.8616	-
5.5087	640	0.512	-
5.5173	641	0.6684	-
5.5260	642	0.541	-
5.5346	643	0.6973	-
5.5433	644	0.6102	-
5.5519	645	0.5356	-
5.5606	646	0.746	-
5.5693	647	0.7803	-
5.5779	648	0.6416	-
5.5866	649	0.5584	-
5.5952	650	0.6438	-
5.6039	651	0.6314	-
5.6126	652	0.4553	-
5.6212	653	0.6072	-
5.6299	654	0.5339	-
5.6385	655	0.7554	-
5.6472	656	0.6722	-
5.6558	657	0.4837	-
5.6645	658	0.5541	-
5.6732	659	0.7474	-
5.6818	660	0.6365	-
5.6905	661	0.5829	-
5.6991	662	0.6911	-
5.7078	663	0.7004	-
5.7165	664	0.7334	-
5.7251	665	0.6566	-
5.7338	666	0.6036	-
5.7424	667	0.7154	-
5.7511	668	0.6535	-
5.7597	669	0.7195	-
5.7684	670	0.6096	-
5.7771	671	0.5585	-
5.7857	672	0.7309	-
5.7944	673	0.6704	-
5.8030	674	0.6668	-
5.8117	675	0.6278	-
5.8203	676	0.5564	-
5.8290	677	0.5742	-
5.8377	678	0.8192	-
5.8463	679	0.7909	-
5.8550	680	0.6763	-
5.8636	681	0.6167	-
5.8723	682	0.4931	-
5.8810	683	0.776	-
5.8896	684	0.5377	-
5.8983	685	0.5475	-
5.9069	686	0.499	-
5.9156	687	0.6195	-
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5.9329	689	0.6015	-
5.9416	690	0.6208	-
5.9502	691	0.5888	-
5.9589	692	0.5349	-
5.9675	693	0.6403	-
5.9762	694	0.632	-
5.9848	695	0.7104	-
5.9935	696	0.7362	-
6.0022	697	0.5433	0.6325
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10.5152	1222	0.4756	-
10.5238	1223	0.4841	-
10.5325	1224	0.5584	-
10.5411	1225	0.5004	-
10.5498	1226	0.3817	-
10.5584	1227	0.6102	-
10.5671	1228	0.7687	-
10.5758	1229	0.5308	-
10.5844	1230	0.452	-
10.5931	1231	0.5039	-
10.6017	1232	0.6055	-
10.6104	1233	0.3844	-
10.6190	1234	0.4218	-
10.6277	1235	0.4416	-
10.6364	1236	0.5421	-
10.6450	1237	0.5322	-
10.6537	1238	0.4721	-
10.6623	1239	0.4056	-
10.6710	1240	0.6013	-
10.6797	1241	0.5255	-
10.6883	1242	0.4308	-
10.6970	1243	0.5676	-
10.7056	1244	0.6479	-
10.7143	1245	0.5906	-
10.7229	1246	0.532	-
10.7316	1247	0.5369	-
10.7403	1248	0.6101	-
10.7489	1249	0.5431	-
10.7576	1250	0.6082	-
10.7662	1251	0.5268	-
10.7749	1252	0.5575	-
10.7835	1253	0.6384	-
10.7922	1254	0.5748	-
10.8009	1255	0.5649	-
10.8095	1256	0.5138	-
10.8182	1257	0.462	-
10.8268	1258	0.4283	-
10.8355	1259	0.6663	-
10.8442	1260	0.6701	-
10.8528	1261	0.7241	-
10.8615	1262	0.531	-
10.8701	1263	0.419	-
10.8788	1264	0.5243	-
10.8874	1265	0.5435	-
10.8961	1266	0.3779	-
10.9048	1267	0.4786	-
10.9134	1268	0.4009	-
10.9221	1269	0.3688	-
10.9307	1270	0.4826	-
10.9394	1271	0.463	-
10.9481	1272	0.4702	-
10.9567	1273	0.4832	-
10.9654	1274	0.5406	-
10.9740	1275	0.3679	-
10.9827	1276	0.665	-
10.9913	1277	0.6234	-
11.0	1278	0.5647	0.6328
11.0022	1279	0.0752	-
11.0108	1280	0.5275	-
11.0195	1281	0.3868	-
11.0281	1282	0.6256	-
11.0368	1283	0.367	-
11.0455	1284	0.4882	-
11.0541	1285	0.5133	-
11.0628	1286	0.4792	-
11.0714	1287	0.4569	-
11.0801	1288	0.343	-
11.0887	1289	0.3211	-
11.0974	1290	0.3144	-
11.1061	1291	0.473	-
11.1147	1292	0.4542	-
11.1234	1293	0.3663	-
11.1320	1294	0.4938	-
11.1407	1295	0.4637	-
11.1494	1296	0.4742	-
11.1580	1297	0.6703	-
11.1667	1298	0.565	-
11.1753	1299	0.4693	-
11.1840	1300	0.611	-
11.1926	1301	0.6661	-
11.2013	1302	0.4809	-
11.2100	1303	0.4522	-
11.2186	1304	0.4558	-
11.2273	1305	0.3736	-
11.2359	1306	0.3751	-
11.2446	1307	0.6145	-
11.2532	1308	0.4541	-
11.2619	1309	0.5261	-
11.2706	1310	0.4238	-
11.2792	1311	0.4296	-
11.2879	1312	0.571	-
11.2965	1313	0.5237	-
11.3052	1314	0.5737	-
11.3139	1315	0.5907	-
11.3225	1316	0.4247	-
11.3312	1317	0.5088	-
11.3398	1318	0.4855	-
11.3485	1319	0.4466	-
11.3571	1320	0.5195	-
11.3658	1321	0.4342	-
11.3745	1322	0.5931	-
11.3831	1323	0.3858	-
11.3918	1324	0.574	-
11.4004	1325	0.4964	-
11.4091	1326	0.4535	-
11.4177	1327	0.3827	-
11.4264	1328	0.4909	-
11.4351	1329	0.4393	-
11.4437	1330	0.503	-
11.4524	1331	0.4652	-
11.4610	1332	0.5689	-
11.4697	1333	0.3687	-
11.4784	1334	0.4452	-
11.4870	1335	0.4505	-
11.4957	1336	0.6276	-
11.5043	1337	0.5335	-
11.5130	1338	0.516	-
11.5216	1339	0.4928	-
11.5303	1340	0.5267	-
11.5390	1341	0.5297	-
11.5476	1342	0.3845	-
11.5563	1343	0.5278	-
11.5649	1344	0.7476	-
11.5736	1345	0.6165	-
11.5823	1346	0.4645	-
11.5909	1347	0.474	-
11.5996	1348	0.5226	-
11.6082	1349	0.4623	-
11.6169	1350	0.358	-
11.6255	1351	0.4829	-
11.6342	1352	0.5048	-
11.6429	1353	0.6036	-
11.6515	1354	0.4636	-
11.6602	1355	0.395	-
11.6688	1356	0.4938	-
11.6775	1357	0.615	-
11.6861	1358	0.4713	-
11.6948	1359	0.5593	-
11.7035	1360	0.5867	-
11.7121	1361	0.5837	-
11.7208	1362	0.5604	-
11.7294	1363	0.5921	-
11.7381	1364	0.4883	-
11.7468	1365	0.5155	-
11.7554	1366	0.6476	-
11.7641	1367	0.5669	-
11.7727	1368	0.5497	-
11.7814	1369	0.5628	-
11.7900	1370	0.5638	-
11.7987	1371	0.5488	-
11.8074	1372	0.4876	-
11.8160	1373	0.4965	-
11.8247	1374	0.4073	-
11.8333	1375	0.5895	-
11.8420	1376	0.6314	-
11.8506	1377	0.5981	-
11.8593	1378	0.6069	-
11.8680	1379	0.3712	-
11.8766	1380	0.5786	-
11.8853	1381	0.5229	-
11.8939	1382	0.4629	-
11.9026	1383	0.3954	-
11.9113	1384	0.4073	-
11.9199	1385	0.4061	-
11.9286	1386	0.4772	-
11.9372	1387	0.442	-
11.9459	1388	0.4583	-
11.9545	1389	0.48	-
11.9632	1390	0.4688	-
11.9719	1391	0.4506	-
11.9805	1392	0.6412	-
11.9892	1393	0.6197	-
11.9978	1394	0.6069	-
12.0065	1395	0.0766	0.6308
12.0087	1396	0.4194	-
12.0173	1397	0.3977	-
12.0260	1398	0.575	-
12.0346	1399	0.3988	-
12.0433	1400	0.4292	-
12.0519	1401	0.5677	-
12.0606	1402	0.5057	-
12.0693	1403	0.447	-
12.0779	1404	0.3676	-
12.0866	1405	0.3618	-
12.0952	1406	0.3369	-
12.1039	1407	0.4366	-
12.1126	1408	0.4554	-
12.1212	1409	0.438	-
12.1299	1410	0.4623	-
12.1385	1411	0.4519	-
12.1472	1412	0.4792	-
12.1558	1413	0.6448	-
12.1645	1414	0.5919	-
12.1732	1415	0.4439	-
12.1818	1416	0.6254	-
12.1905	1417	0.6867	-
12.1991	1418	0.4858	-
12.2078	1419	0.5247	-
12.2165	1420	0.5206	-
12.2251	1421	0.3791	-
12.2338	1422	0.3486	-
12.2424	1423	0.5623	-
12.2511	1424	0.5472	-
12.2597	1425	0.501	-
12.2684	1426	0.3658	-
12.2771	1427	0.427	-
12.2857	1428	0.55	-
12.2944	1429	0.5389	-
12.3030	1430	0.601	-
12.3117	1431	0.4281	-
12.3203	1432	0.5827	-
12.3290	1433	0.4799	-
12.3377	1434	0.4664	-
12.3463	1435	0.4134	-
12.3550	1436	0.5237	-
12.3636	1437	0.4357	-
12.3723	1438	0.5842	-
12.3810	1439	0.4751	-
12.3896	1440	0.4842	-
12.3983	1441	0.4643	-
12.4069	1442	0.4726	-
12.4156	1443	0.3779	-
12.4242	1444	0.5046	-
12.4329	1445	0.4202	-
12.4416	1446	0.4742	-
12.4502	1447	0.5148	-
12.4589	1448	0.6015	-
12.4675	1449	0.3856	-
12.4762	1450	0.4316	-
12.4848	1451	0.4171	-
12.4935	1452	0.5762	-
12.5022	1453	0.6035	-
12.5108	1454	0.5113	-
12.5195	1455	0.5098	-
12.5281	1456	0.468	-
12.5368	1457	0.5314	-
12.5455	1458	0.3761	-
12.5541	1459	0.5039	-
12.5628	1460	0.7329	-
12.5714	1461	0.6484	-
12.5801	1462	0.3605	-
12.5887	1463	0.5505	-
12.5974	1464	0.4275	-
12.6061	1465	0.5235	-
12.6147	1466	0.2997	-
12.6234	1467	0.5186	-
12.6320	1468	0.434	-
12.6407	1469	0.6209	-
12.6494	1470	0.5143	-
12.6580	1471	0.4516	-
12.6667	1472	0.4884	-
12.6753	1473	0.5524	-
12.6840	1474	0.504	-
12.6926	1475	0.521	-
12.7013	1476	0.6132	-
12.7100	1477	0.5367	-
12.7186	1478	0.588	-
12.7273	1479	0.588	-
12.7359	1480	0.4314	-
12.7446	1481	0.5411	-
12.7532	1482	0.5413	-
12.7619	1483	0.5773	-
12.7706	1484	0.6148	-
12.7792	1485	0.5527	-
12.7879	1486	0.591	-
12.7965	1487	0.5036	-
12.8052	1488	0.5067	-
12.8139	1489	0.5065	-
12.8225	1490	0.3709	-
12.8312	1491	0.449	-
12.8398	1492	0.7186	-
12.8485	1493	0.6695	-
12.8571	1494	0.5495	-
12.8658	1495	0.4541	-
12.8745	1496	0.5049	-
12.8831	1497	0.5705	-
12.8918	1498	0.4004	-
12.9004	1499	0.4942	-
12.9091	1500	0.3692	-
12.9177	1501	0.4546	-
12.9264	1502	0.3945	-
12.9351	1503	0.4457	-
12.9437	1504	0.4465	-
12.9524	1505	0.4991	-
12.9610	1506	0.4168	-
12.9697	1507	0.4398	-
12.9784	1508	0.6129	-
12.9870	1509	0.5171	-
12.9957	1510	0.68	-
13.0043	1511	0.257	0.6320
13.0065	1512	0.2875	-
13.0152	1513	0.4426	-
13.0238	1514	0.5968	-
13.0325	1515	0.4575	-
13.0411	1516	0.4208	-
13.0498	1517	0.6111	-
13.0584	1518	0.4491	-
13.0671	1519	0.4238	-
13.0758	1520	0.3598	-
13.0844	1521	0.3611	-
13.0931	1522	0.3166	-
13.1017	1523	0.3495	-
13.1104	1524	0.504	-
13.1190	1525	0.3953	-
13.1277	1526	0.3837	-
13.1364	1527	0.4702	-
13.1450	1528	0.4842	-
13.1537	1529	0.5316	-
13.1623	1530	0.6843	-
13.1710	1531	0.4119	-
13.1797	1532	0.566	-
13.1883	1533	0.6289	-
13.1970	1534	0.5133	-
13.2056	1535	0.4918	-
13.2143	1536	0.4334	-
13.2229	1537	0.448	-
13.2316	1538	0.3901	-
13.2403	1539	0.4498	-
13.2489	1540	0.5765	-
13.2576	1541	0.4494	-
13.2662	1542	0.4161	-
13.2749	1543	0.4489	-
13.2835	1544	0.4961	-
13.2922	1545	0.566	-
13.3009	1546	0.5464	-
13.3095	1547	0.4544	-
13.3182	1548	0.6022	-
13.3268	1549	0.5352	-
13.3355	1550	0.4455	-
13.3442	1551	0.3528	-
13.3528	1552	0.5256	-
13.3615	1553	0.4336	-
13.3701	1554	0.5276	-
13.3788	1555	0.5581	-
13.3874	1556	0.3553	-
13.3961	1557	0.4821	-
13.4048	1558	0.4381	-
13.4134	1559	0.4295	-
13.4221	1560	0.4617	-
13.4307	1561	0.4944	-
13.4394	1562	0.4638	-
13.4481	1563	0.4674	-
13.4567	1564	0.5274	-
13.4654	1565	0.5064	-
13.4740	1566	0.418	-
13.4827	1567	0.3655	-
13.4913	1568	0.5358	-
13.5	1569	0.6803	-
13.5087	1570	0.4324	-
13.5173	1571	0.5466	-
13.5260	1572	0.4046	-
13.5346	1573	0.5154	-
13.5433	1574	0.4974	-
13.5519	1575	0.4288	-
13.5606	1576	0.6139	-
13.5693	1577	0.639	-
13.5779	1578	0.4972	-
13.5866	1579	0.4443	-
13.5952	1580	0.5152	-
13.6039	1581	0.5252	-
13.6126	1582	0.3276	-
13.6212	1583	0.4941	-
13.6299	1584	0.4694	-
13.6385	1585	0.5771	-
13.6472	1586	0.5345	-
13.6558	1587	0.393	-
13.6645	1588	0.4361	-
13.6732	1589	0.6306	-
13.6818	1590	0.4791	-
13.6905	1591	0.4615	-
13.6991	1592	0.5878	-
13.7078	1593	0.6018	-
13.7165	1594	0.6244	-
13.7251	1595	0.4856	-
13.7338	1596	0.5106	-
13.7424	1597	0.6139	-
13.7511	1598	0.5438	-
13.7597	1599	0.6439	-
13.7684	1600	0.5334	-
13.7771	1601	0.4414	-
13.7857	1602	0.6284	-
13.7944	1603	0.5911	-
13.8030	1604	0.5587	-
13.8117	1605	0.443	-
13.8203	1606	0.4535	-
13.8290	1607	0.4474	-
13.8377	1608	0.6536	-
13.8463	1609	0.6585	-
13.8550	1610	0.5697	-
13.8636	1611	0.4965	-
13.8723	1612	0.3808	-
13.8810	1613	0.6171	-
13.8896	1614	0.4141	-
13.8983	1615	0.3974	-
13.9069	1616	0.4146	-
13.9156	1617	0.4761	-
13.9242	1618	0.3364	-
13.9329	1619	0.4532	-
13.9416	1620	0.4791	-
13.9502	1621	0.506	-
13.9589	1622	0.441	-
13.9675	1623	0.5164	-
13.9762	1624	0.4755	-
13.9848	1625	0.5755	-
13.9935	1626	0.5869	-
14.0022	1627	0.3876	0.6315
14.0043	1628	0.1324	-
14.0130	1629	0.4829	-
14.0216	1630	0.5558	-
14.0303	1631	0.458	-
14.0390	1632	0.3926	-
14.0476	1633	0.5138	-
14.0563	1634	0.6099	-
14.0649	1635	0.3593	-
14.0736	1636	0.4445	-
14.0823	1637	0.349	-
14.0909	1638	0.3149	-
14.0996	1639	0.3561	-
14.1082	1640	0.5296	-
14.1169	1641	0.4211	-
14.1255	1642	0.4022	-
14.1342	1643	0.5006	-
14.1429	1644	0.5073	-
14.1515	1645	0.451	-
14.1602	1646	0.6265	-
14.1688	1647	0.5661	-
14.1775	1648	0.5828	-
14.1861	1649	0.6311	-
14.1948	1650	0.6223	-
14.2035	1651	0.4654	-
14.2121	1652	0.4027	-
14.2208	1653	0.4681	-
14.2294	1654	0.405	-
14.2381	1655	0.3793	-
14.2468	1656	0.5966	-
14.2554	1657	0.4515	-
14.2641	1658	0.4629	-
14.2727	1659	0.4519	-
14.2814	1660	0.4831	-
14.2900	1661	0.4968	-
14.2987	1662	0.5746	-
14.3074	1663	0.5295	-
14.3160	1664	0.6171	-
14.3247	1665	0.4421	-
14.3333	1666	0.4878	-
14.3420	1667	0.3967	-
14.3506	1668	0.4288	-
14.3593	1669	0.4503	-
14.3680	1670	0.4961	-
14.3766	1671	0.5604	-
14.3853	1672	0.3602	-
14.3939	1673	0.5758	-
14.4026	1674	0.4466	-
14.4113	1675	0.3795	-
14.4199	1676	0.4125	-
14.4286	1677	0.4842	-
14.4372	1678	0.4994	-
14.4459	1679	0.4349	-
14.4545	1680	0.5829	-
14.4632	1681	0.4991	-
14.4719	1682	0.436	-
14.4805	1683	0.3637	-
14.4892	1684	0.4688	-
14.4978	1685	0.6854	-
14.5065	1686	0.4746	-
14.5152	1687	0.4519	-
14.5238	1688	0.4684	-
14.5325	1689	0.5273	-
14.5411	1690	0.5172	-
14.5498	1691	0.3482	-
14.5584	1692	0.5758	-
14.5671	1693	0.7693	-
14.5758	1694	0.4892	-
14.5844	1695	0.4738	-
14.5931	1696	0.5148	-
14.6017	1697	0.564	-
14.6104	1698	0.3945	-
14.6190	1699	0.4066	-
14.6277	1700	0.4445	-
14.6364	1701	0.569	-
14.6450	1702	0.4889	-
14.6537	1703	0.4877	-
14.6623	1704	0.383	-
14.6710	1705	0.5956	-
14.6797	1706	0.5391	-
14.6883	1707	0.4022	-
14.6970	1708	0.5472	-
14.7056	1709	0.6352	-
14.7143	1710	0.5842	-
14.7229	1711	0.4791	-
14.7316	1712	0.5339	-
14.7403	1713	0.6199	-
14.7489	1714	0.5332	-
14.7576	1715	0.5798	-
14.7662	1716	0.5493	-
14.7749	1717	0.5171	-
14.7835	1718	0.5666	-
14.7922	1719	0.527	-
14.8009	1720	0.5072	-
14.8095	1721	0.4886	-
14.8182	1722	0.4516	-
14.8268	1723	0.4257	-
14.8355	1724	0.6247	-
14.8442	1725	0.6085	0.6313

The bold row denotes the saved checkpoint.

Framework Versions

Python: 3.10.12
Sentence Transformers: 3.2.1
Transformers: 4.45.2
PyTorch: 2.2.1+cu121
Accelerate: 1.0.1
Datasets: 3.0.1
Tokenizers: 0.20.1

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",
}

MultipleNegativesRankingLoss

@misc{henderson2017efficient,
    title={Efficient Natural Language Response Suggestion for Smart Reply},
    author={Matthew Henderson and Rami Al-Rfou and Brian Strope and Yun-hsuan Sung and Laszlo Lukacs and Ruiqi Guo and Sanjiv Kumar and Balint Miklos and Ray Kurzweil},
    year={2017},
    eprint={1705.00652},
    archivePrefix={arXiv},
    primaryClass={cs.CL}
}

ObliQA: Obligation-based Question-Answering Dataset for Regulatory Compliance

@misc{gokhan2024regnlpactionfacilitatingcompliance,
      title={RegNLP in Action: Facilitating Compliance Through Automated Information Retrieval and Answer Generation}, 
      author={Tuba Gokhan and Kexin Wang and Iryna Gurevych and Ted Briscoe},
      year={2024},
      eprint={2409.05677},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2409.05677}, 
}