metadata

base_model: Snowflake/snowflake-arctic-embed-m
datasets: []
language: []
library_name: sentence-transformers
pipeline_tag: sentence-similarity
tags:
  - sentence-transformers
  - sentence-similarity
  - feature-extraction
  - generated_from_trainer
  - dataset_size:1306883
  - loss:MultipleNegativesRankingLoss
widget:
  - source_sentence: 'query: today:2034-03-02 start of last year make Cilantro Spaghetti O''s'
    sentences:
      - >
        passage: With the advent of e-books, independent presses, and other
        developments, it’s never been easier to break into the writing scene
        nowadays. However, don’t be fooled by the opportunities. 1/10
      - >
        passage: January of 2033 cilantro spaghetti O's makes a quick and easy
        lunch or dinner, especially suitable for young kids. The meal doesn't
        require a ton of ingredients, and it's very simple to make.
      - >
        passage: Building back muscle can be very beneficial because it is a
        core muscle; most of your daily functions use your back muscles!
        Strengthening your back will enhance your posture and stability. 2007
        February
  - source_sentence: 'query: October ''39 add a Filter to Pixia'
    sentences:
      - >
        passage: 2039 fall Adding filters to software gives you extra options.
        Adding these extra options to Pixia is fairly easy. Just read this
        article and learn! 
      - >
        passage: August 2040 hitting rock bottom affects all levels of income,
        people from all backgrounds and walks of life and all ages. It's a term
        that encompasses all sorts of losses, mishaps and failures in life, so
        this article won't seek to define it.
      - >
        passage: Fractions and decimal numbers are simply two different ways of
        representing numbers that are less than one.  [1]  Since any number
        below one can be represented with either a fraction or a decimal, there
        are specific mathematic equations that allow you to figure out what the
        equivalent of a fraction would be in decimal form, and vice versa.
        06/01/47
  - source_sentence: 'query: Jul 18 1970 define Yourself'
    sentences:
      - >
        passage: 06/28/45 avoid the cost of purchasing food dishes for your
        four-legged friends and do a bit of recycling good by reusing unwanted
        plastic containers from your recycling.
      - >
        passage: 07/18/70 everyone struggles to figure out who people truly are.
        Often when they define themselves they focus on the negative or how they
        compare to other people.
      - >
        passage: While there are certainly other ways to treat acne , perhaps
        none is as DIY and cost-effective as using lemon juice. Lemon juice
        contains L-asorbic acid, a natural astringent which dries out the acne,
        as well as antibacterial compounds that fight acne-producing bacteria.
        10/12
  - source_sentence: 'query: Ease Regret'
    sentences:
      - >
        passage: How to ease regret? Well that's always a tough one. As a tattoo
        artist, I see a lot of regret and I myself have dealt with it before,
        but it's pretty easy to get over it.
      - >
        passage: 01/19/39 microsoft's Xbox 360 game console has a huge library
        of available games, many of which support voice commands or can be
        played online. These types of games require a microphone and headphone
        speakers to take advantage of all the game play features.
      - >
        passage: "oct 23 2028 according to retired Baltimore Ravens linebacker
        Ray Lewis, ""A linebacker's job is to knock out running backs, to knock
        out receivers, [and] to chase the football."""
  - source_sentence: 'query: today:2018-11-21 Find Potatoes in Minecraft PE end of last year '
    sentences:
      - >
        passage: spring '25 the Achilles tendon is a tendon that attaches the
        calf muscle to the heel bone. The tendon's position in the body puts it
        under a lot of strain, especially during exercise.
      - >
        passage: Spring 50 using a hair dryer to dry your hair too often can
        cause it to become dry and brittle. To keep your hair healthy, it’s
        better to use a towel to squeeze out the moisture, then let your hair
        continue air drying.
      - >
        passage: Potatoes are a crop in Minecraft PE (Pocket Edition) that can
        be eaten for health, planted in a garden, and much more. Getting a few
        potatoes is easy once you know that the quickest way to get them is
        usually killing zombies . 2017 Fall

SentenceTransformer based on Snowflake/snowflake-arctic-embed-m

This is a sentence-transformers model finetuned from Snowflake/snowflake-arctic-embed-m. It maps sentences & paragraphs to a 768-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: Snowflake/snowflake-arctic-embed-m
Maximum Sequence Length: 512 tokens
Output Dimensionality: 768 tokens
Similarity Function: Cosine Similarity

Model Sources

Documentation: Sentence Transformers Documentation
Repository: Sentence Transformers on GitHub
Hugging Face: Sentence Transformers on Hugging Face

Full Model Architecture

SentenceTransformer(
  (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel 
  (1): Pooling({'word_embedding_dimension': 768, '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("sentence_transformers_model_id")
# Run inference
sentences = [
    'query: today:2018-11-21 Find Potatoes in Minecraft PE end of last year ',
    'passage: Potatoes are a crop in Minecraft PE (Pocket Edition) that can be eaten for health, planted in a garden, and much more. Getting a few potatoes is easy once you know that the quickest way to get them is usually killing zombies . 2017 Fall\n',
    'passage: Spring 50 using a hair dryer to dry your hair too often can cause it to become dry and brittle. To keep your hair healthy, it’s better to use a towel to squeeze out the moisture, then let your hair continue air drying.\n',
]
embeddings = model.encode(sentences)
print(embeddings.shape)
# [3, 768]

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

Training Details

Training Dataset

Unnamed Dataset

Size: 1,306,883 training samples
Columns: anchors and positive
Approximate statistics based on the first 1000 samples:
anchors positive
type string string
details
min: 8 tokens
mean: 18.75 tokens
max: 32 tokens

min: 23 tokens
mean: 53.2 tokens
max: 111 tokens

	anchors	positive
type	string	string
details	min: 8 tokens mean: 18.75 tokens max: 32 tokens	min: 23 tokens mean: 53.2 tokens max: 111 tokens

Samples:

anchors	positive
`query: today:2022-04-21 Sell Fine Art Online this month`	`passage: So you're a new or aspiring artist and your creativity has spawned something unique and interesting. Now you're ready to display and sell this creation and perhaps make some money, but you're venturing into the unknown. Spring 2022`
`query: today:2015-01-16 5 days ago be Well Read`	`passage: "jan 11 2015 if you want to be well-read, then, in the words of William Faulkner, you'll have to ""Read, read, read. Read everything..."" You can start at the very beginning, or just make your way down an eclectic list of books that you'd like to read."`
`query: today:2046-07-13 Pick a Stage Name early last year`	`passage: Stage names are used by all types of performers, from musicians, actors and roller derby athletes to burlesque dancers, belly dancers, and exotic dancers. 01/01/45`

Loss: MultipleNegativesRankingLoss with these parameters:

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

Evaluation Dataset

Unnamed Dataset

Size: 1,000 evaluation samples
Columns: anchors and positive
Approximate statistics based on the first 1000 samples:
anchors positive
type string string
details
min: 6 tokens
mean: 16.55 tokens
max: 33 tokens

min: 11 tokens
mean: 50.32 tokens
max: 105 tokens

	anchors	positive
type	string	string
details	min: 6 tokens mean: 16.55 tokens max: 33 tokens	min: 11 tokens mean: 50.32 tokens max: 105 tokens

Samples:

anchors	positive
`query: today:2023-02-22 Be a Good Wrestler last winter`	`passage: Wrestling is not the same everywhere the sport takes place. If you want to be a good wrestler, you have to know the rules for the type of wrestling you want to do, and decide exactly what defines a 'good' wrestler for you. Winter 22`
`query: today:2047-09-13 21 days ago make a Lip Balm Container with Bottle Caps`	`passage: 2047 Monsoon nowadays, everyone is crazy about making lip balms and gloss, but most people forget the container. Fortunately, there are some solutions. This article will teach you how to make your own lip balm container.`
`query: today:2037-12-13 23 years ago swim Underwater Without Holding Your Nose`	`passage: 29/03/2014 swimming underwater without holding your nose opens up a world of new possibilities for aquatic recreation and fun. Whether you are looking to do a flip turn, start swimming competitively, or even just do a handstand underwater, learning to swim without holding your nose is essential.`

Loss: MultipleNegativesRankingLoss with these parameters:

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

Training Hyperparameters

Non-Default Hyperparameters

eval_strategy: steps
per_device_train_batch_size: 64
per_device_eval_batch_size: 64
learning_rate: 1e-05
weight_decay: 0.01
num_train_epochs: 1
warmup_ratio: 0.1
warmup_steps: 400
bf16: True
torch_compile: True
torch_compile_backend: inductor
batch_sampler: no_duplicates

All Hyperparameters

Click to expand

overwrite_output_dir: False
do_predict: False
eval_strategy: steps
prediction_loss_only: True
per_device_train_batch_size: 64
per_device_eval_batch_size: 64
per_gpu_train_batch_size: None
per_gpu_eval_batch_size: None
gradient_accumulation_steps: 1
eval_accumulation_steps: None
learning_rate: 1e-05
weight_decay: 0.01
adam_beta1: 0.9
adam_beta2: 0.999
adam_epsilon: 1e-08
max_grad_norm: 1.0
num_train_epochs: 1
max_steps: -1
lr_scheduler_type: linear
lr_scheduler_kwargs: {}
warmup_ratio: 0.1
warmup_steps: 400
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: False
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
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: True
torch_compile_backend: inductor
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
batch_sampler: no_duplicates
multi_dataset_batch_sampler: proportional

Training Logs

Click to expand

Epoch	Step	Training Loss	loss
0.0000	1	2.366	-
0.0005	10	2.579	-
0.0010	20	2.3277	-
0.0015	30	2.3161	-
0.0020	40	2.0011	-
0.0024	50	1.7122	-
0.0029	60	1.3642	-
0.0034	70	1.2231	-
0.0039	80	1.1588	-
0.0044	90	0.7336	-
0.0049	100	0.7661	-
0.0054	110	0.75	-
0.0059	120	0.7174	-
0.0064	130	0.4378	-
0.0069	140	0.3111	-
0.0073	150	0.3669	-
0.0078	160	0.5555	-
0.0083	170	0.4091	-
0.0088	180	0.6413	-
0.0093	190	0.7201	-
0.0098	200	0.3625	-
0.0103	210	0.4803	-
0.0108	220	0.3996	-
0.0113	230	0.3793	-
0.0118	240	0.392	-
0.0122	250	0.2503	-
0.0127	260	0.6191	-
0.0132	270	0.5611	-
0.0137	280	0.2981	-
0.0142	290	0.241	-
0.0147	300	0.4188	-
0.0152	310	0.237	-
0.0157	320	0.1695	-
0.0162	330	0.1875	-
0.0166	340	0.1443	-
0.0171	350	0.1866	-
0.0176	360	0.3067	-
0.0181	370	0.1761	-
0.0186	380	0.1718	-
0.0191	390	0.1803	-
0.0196	400	0.2673	-
0.0201	410	0.2618	-
0.0206	420	0.251	-
0.0211	430	0.2658	-
0.0215	440	0.2297	-
0.0220	450	0.3406	-
0.0225	460	0.2442	-
0.0230	470	0.2298	-
0.0235	480	0.1933	-
0.0240	490	0.2423	-
0.0245	500	0.2097	-
0.0250	510	0.1965	-
0.0255	520	0.1495	-
0.0260	530	0.2032	-
0.0264	540	0.2886	-
0.0269	550	0.3213	-
0.0274	560	0.2248	-
0.0279	570	0.1526	-
0.0284	580	0.1385	-
0.0289	590	0.2057	-
0.0294	600	0.1922	-
0.0299	610	0.1751	-
0.0304	620	0.1187	-
0.0309	630	0.1134	-
0.0313	640	0.1652	-
0.0318	650	0.1367	-
0.0323	660	0.151	-
0.0328	670	0.1857	-
0.0333	680	0.1167	-
0.0338	690	0.2079	-
0.0343	700	0.1648	-
0.0348	710	0.1018	-
0.0353	720	0.1275	-
0.0357	730	0.111	-
0.0362	740	0.2017	-
0.0367	750	0.1191	-
0.0372	760	0.1073	-
0.0377	770	0.0634	-
0.0382	780	0.1171	-
0.0387	790	0.1355	-
0.0392	800	0.1463	-
0.0397	810	0.0858	-
0.0402	820	0.101	-
0.0406	830	0.1394	-
0.0411	840	0.1145	-
0.0416	850	0.0733	-
0.0421	860	0.0696	-
0.0426	870	0.077	-
0.0431	880	0.1467	-
0.0436	890	0.0996	-
0.0441	900	0.1186	-
0.0446	910	0.1218	-
0.0451	920	0.1363	-
0.0455	930	0.1104	-
0.0460	940	0.1837	-
0.0465	950	0.2613	-
0.0470	960	0.1383	-
0.0475	970	0.1419	-
0.0480	980	0.1432	-
0.0485	990	0.1567	-
0.0490	1000	0.0951	-
0.0495	1010	0.1453	-
0.0499	1020	0.119	-
0.0504	1030	0.0885	-
0.0509	1040	0.1004	-
0.0514	1050	0.0866	-
0.0519	1060	0.1143	-
0.0524	1070	0.1234	-
0.0529	1080	0.1153	-
0.0534	1090	0.118	-
0.0539	1100	0.0854	-
0.0544	1110	0.0583	-
0.0548	1120	0.1051	-
0.0553	1130	0.0925	-
0.0558	1140	0.0872	-
0.0563	1150	0.0791	-
0.0568	1160	0.0968	-
0.0573	1170	0.1191	-
0.0578	1180	0.0818	-
0.0583	1190	0.0714	-
0.0588	1200	0.067	-
0.0593	1210	0.1063	-
0.0597	1220	0.0478	-
0.0602	1230	0.0299	-
0.0607	1240	0.0352	-
0.0612	1250	0.0892	-
0.0617	1260	0.0486	-
0.0622	1270	0.069	-
0.0627	1280	0.139	-
0.0632	1290	0.066	-
0.0637	1300	0.0519	-
0.0641	1310	0.0597	-
0.0646	1320	0.0658	-
0.0651	1330	0.055	-
0.0656	1340	0.0691	-
0.0661	1350	0.1175	-
0.0666	1360	0.1444	-
0.0671	1370	0.0791	-
0.0676	1380	0.0489	-
0.0681	1390	0.0964	-
0.0686	1400	0.0636	-
0.0690	1410	0.0315	-
0.0695	1420	0.0266	-
0.0700	1430	0.0375	-
0.0705	1440	0.0341	-
0.0710	1450	0.0492	-
0.0715	1460	0.0494	-
0.0720	1470	0.0614	-
0.0725	1480	0.0346	-
0.0730	1490	0.0486	-
0.0735	1500	0.07	-
0.0739	1510	0.0562	-
0.0744	1520	0.0723	-
0.0749	1530	0.0647	-
0.0754	1540	0.0866	-
0.0759	1550	0.0922	-
0.0764	1560	0.0678	-
0.0769	1570	0.0714	-
0.0774	1580	0.0732	-
0.0779	1590	0.0486	-
0.0784	1600	0.0579	-
0.0788	1610	0.045	-
0.0793	1620	0.0693	-
0.0798	1630	0.0816	-
0.0803	1640	0.1091	-
0.0808	1650	0.0832	-
0.0813	1660	0.0634	-
0.0818	1670	0.0335	-
0.0823	1680	0.0708	-
0.0828	1690	0.0723	-
0.0832	1700	0.0603	-
0.0837	1710	0.0507	-
0.0842	1720	0.0418	-
0.0847	1730	0.0487	-
0.0852	1740	0.0594	-
0.0857	1750	0.0733	-
0.0862	1760	0.0693	-
0.0867	1770	0.0323	-
0.0872	1780	0.0781	-
0.0877	1790	0.0743	-
0.0881	1800	0.0462	-
0.0886	1810	0.0588	-
0.0891	1820	0.0435	-
0.0896	1830	0.0832	-
0.0901	1840	0.0386	-
0.0906	1850	0.0585	-
0.0911	1860	0.0302	-
0.0916	1870	0.0321	-
0.0921	1880	0.0591	-
0.0926	1890	0.0502	-
0.0930	1900	0.0517	-
0.0935	1910	0.042	-
0.0940	1920	0.0462	-
0.0945	1930	0.073	-
0.0950	1940	0.0245	-
0.0955	1950	0.0211	-
0.0960	1960	0.032	-
0.0965	1970	0.0671	-
0.0970	1980	0.0454	-
0.0974	1990	0.0437	-
0.0979	2000	0.0588	0.0434
0.0984	2010	0.0408	-
0.0989	2020	0.0562	-
0.0994	2030	0.0547	-
0.0999	2040	0.0998	-
0.1004	2050	0.0611	-
0.1009	2060	0.0524	-
0.1014	2070	0.0665	-
0.1019	2080	0.0703	-
0.1023	2090	0.0535	-
0.1028	2100	0.0631	-
0.1033	2110	0.0621	-
0.1038	2120	0.0452	-
0.1043	2130	0.0479	-
0.1048	2140	0.0388	-
0.1053	2150	0.0706	-
0.1058	2160	0.0489	-
0.1063	2170	0.0641	-
0.1068	2180	0.0647	-
0.1072	2190	0.0555	-
0.1077	2200	0.0488	-
0.1082	2210	0.0531	-
0.1087	2220	0.0741	-
0.1092	2230	0.0652	-
0.1097	2240	0.0444	-
0.1102	2250	0.0585	-
0.1107	2260	0.0566	-
0.1112	2270	0.0657	-
0.1116	2280	0.0372	-
0.1121	2290	0.0485	-
0.1126	2300	0.055	-
0.1131	2310	0.0429	-
0.1136	2320	0.0209	-
0.1141	2330	0.0189	-
0.1146	2340	0.0315	-
0.1151	2350	0.0536	-
0.1156	2360	0.0377	-
0.1161	2370	0.0687	-
0.1165	2380	0.0476	-
0.1170	2390	0.0328	-
0.1175	2400	0.05	-
0.1180	2410	0.0553	-
0.1185	2420	0.0352	-
0.1190	2430	0.0587	-
0.1195	2440	0.0386	-
0.1200	2450	0.1083	-
0.1205	2460	0.0673	-
0.1210	2470	0.0301	-
0.1214	2480	0.0614	-
0.1219	2490	0.0706	-
0.1224	2500	0.0289	-
0.1229	2510	0.0197	-
0.1234	2520	0.0205	-
0.1239	2530	0.0245	-
0.1244	2540	0.0303	-
0.1249	2550	0.0541	-
0.1254	2560	0.0188	-
0.1259	2570	0.0413	-
0.1263	2580	0.0288	-
0.1268	2590	0.0566	-
0.1273	2600	0.0427	-
0.1278	2610	0.0519	-
0.1283	2620	0.0402	-
0.1288	2630	0.0383	-
0.1293	2640	0.0517	-
0.1298	2650	0.0612	-
0.1303	2660	0.0569	-
0.1307	2670	0.0511	-
0.1312	2680	0.0371	-
0.1317	2690	0.037	-
0.1322	2700	0.052	-
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0.1332	2720	0.0625	-
0.1337	2730	0.0777	-
0.1342	2740	0.0664	-
0.1347	2750	0.0682	-
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0.1356	2770	0.0436	-
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0.1366	2790	0.0397	-
0.1371	2800	0.0586	-
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0.1401	2860	0.0273	-
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0.1420	2900	0.0249	-
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0.1440	2940	0.0375	-
0.1445	2950	0.0303	-
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0.1459	2980	0.0435	-
0.1464	2990	0.0476	-
0.1469	3000	0.0361	-
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0.1494	3050	0.0283	-
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0.1503	3070	0.0427	-
0.1508	3080	0.0362	-
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0.1518	3100	0.0435	-
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0.1528	3120	0.0359	-
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0.1547	3160	0.0468	-
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0.1567	3200	0.0437	-
0.1572	3210	0.0422	-
0.1577	3220	0.0502	-
0.1582	3230	0.0336	-
0.1587	3240	0.0564	-
0.1591	3250	0.0433	-
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0.1606	3280	0.0427	-
0.1611	3290	0.0391	-
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0.1621	3310	0.0586	-
0.1626	3320	0.0628	-
0.1631	3330	0.0537	-
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0.1640	3350	0.0519	-
0.1645	3360	0.0627	-
0.1650	3370	0.0295	-
0.1655	3380	0.0397	-
0.1660	3390	0.0442	-
0.1665	3400	0.044	-
0.1670	3410	0.0211	-
0.1675	3420	0.0192	-
0.1680	3430	0.0237	-
0.1685	3440	0.0461	-
0.1689	3450	0.03	-
0.1694	3460	0.0524	-
0.1699	3470	0.0493	-
0.1704	3480	0.0292	-
0.1709	3490	0.0411	-
0.1714	3500	0.0336	-
0.1719	3510	0.0405	-
0.1724	3520	0.0465	-
0.1729	3530	0.0217	-
0.1734	3540	0.079	-
0.1738	3550	0.0656	-
0.1743	3560	0.0307	-
0.1748	3570	0.0326	-
0.1753	3580	0.0512	-
0.1758	3590	0.032	-
0.1763	3600	0.0154	-
0.1768	3610	0.0193	-
0.1773	3620	0.0195	-
0.1778	3630	0.0141	-
0.1782	3640	0.047	-
0.1787	3650	0.0158	-
0.1792	3660	0.037	-
0.1797	3670	0.0203	-
0.1802	3680	0.0335	-
0.1807	3690	0.0371	-
0.1812	3700	0.0493	-
0.1817	3710	0.0313	-
0.1822	3720	0.0415	-
0.1827	3730	0.0671	-
0.1831	3740	0.0583	-
0.1836	3750	0.0451	-
0.1841	3760	0.0482	-
0.1846	3770	0.0466	-
0.1851	3780	0.03	-
0.1856	3790	0.0198	-
0.1861	3800	0.0339	-
0.1866	3810	0.044	-
0.1871	3820	0.0528	-
0.1876	3830	0.0607	-
0.1880	3840	0.0587	-
0.1885	3850	0.0225	-
0.1890	3860	0.0297	-
0.1895	3870	0.0593	-
0.1900	3880	0.041	-
0.1905	3890	0.0441	-
0.1910	3900	0.0374	-
0.1915	3910	0.0294	-
0.1920	3920	0.042	-
0.1924	3930	0.0346	-
0.1929	3940	0.0389	-
0.1934	3950	0.0224	-
0.1939	3960	0.0341	-
0.1944	3970	0.0404	-
0.1949	3980	0.0334	-
0.1954	3990	0.0297	-
0.1959	4000	0.0262	0.0290
0.1964	4010	0.0407	-
0.1969	4020	0.0438	-
0.1973	4030	0.0321	-
0.1978	4040	0.0227	-
0.1983	4050	0.0211	-
0.1988	4060	0.0238	-
0.1993	4070	0.0237	-
0.1998	4080	0.0332	-
0.2003	4090	0.0292	-
0.2008	4100	0.0253	-
0.2013	4110	0.0432	-
0.2018	4120	0.0157	-
0.2022	4130	0.0181	-
0.2027	4140	0.014	-
0.2032	4150	0.0249	-
0.2037	4160	0.0376	-
0.2042	4170	0.0292	-
0.2047	4180	0.0258	-
0.2052	4190	0.0216	-
0.2057	4200	0.0504	-
0.2062	4210	0.0313	-
0.2067	4220	0.0549	-
0.2071	4230	0.0538	-
0.2076	4240	0.0478	-
0.2081	4250	0.0694	-
0.2086	4260	0.0398	-
0.2091	4270	0.0442	-
0.2096	4280	0.0276	-
0.2101	4290	0.0451	-
0.2106	4300	0.0355	-
0.2111	4310	0.0312	-
0.2115	4320	0.0194	-
0.2120	4330	0.0355	-
0.2125	4340	0.0232	-
0.2130	4350	0.0336	-
0.2135	4360	0.0434	-
0.2140	4370	0.05	-
0.2145	4380	0.0208	-
0.2150	4390	0.0422	-
0.2155	4400	0.0377	-
0.2160	4410	0.0513	-
0.2164	4420	0.0304	-
0.2169	4430	0.0383	-
0.2174	4440	0.0478	-
0.2179	4450	0.042	-
0.2184	4460	0.0222	-
0.2189	4470	0.0318	-
0.2194	4480	0.0321	-
0.2199	4490	0.0326	-
0.2204	4500	0.0158	-
0.2209	4510	0.0151	-
0.2213	4520	0.0194	-
0.2218	4530	0.0388	-
0.2223	4540	0.0285	-
0.2228	4550	0.0292	-
0.2233	4560	0.0431	-
0.2238	4570	0.0248	-
0.2243	4580	0.0332	-
0.2248	4590	0.0296	-
0.2253	4600	0.0252	-
0.2257	4610	0.0355	-
0.2262	4620	0.0191	-
0.2267	4630	0.0507	-
0.2272	4640	0.0499	-
0.2277	4650	0.0263	-
0.2282	4660	0.0193	-
0.2287	4670	0.0425	-
0.2292	4680	0.047	-
0.2297	4690	0.0132	-
0.2302	4700	0.0251	-
0.2306	4710	0.015	-
0.2311	4720	0.0183	-
0.2316	4730	0.03	-
0.2321	4740	0.0183	-
0.2326	4750	0.0226	-
0.2331	4760	0.0194	-
0.2336	4770	0.0245	-
0.2341	4780	0.0352	-
0.2346	4790	0.0277	-
0.2351	4800	0.0317	-
0.2355	4810	0.0328	-
0.2360	4820	0.0578	-
0.2365	4830	0.0343	-
0.2370	4840	0.0562	-
0.2375	4850	0.0395	-
0.2380	4860	0.0462	-
0.2385	4870	0.0312	-
0.2390	4880	0.0297	-
0.2395	4890	0.0255	-
0.2399	4900	0.051	-
0.2404	4910	0.0494	-
0.2409	4920	0.053	-
0.2414	4930	0.0689	-
0.2419	4940	0.038	-
0.2424	4950	0.0219	-
0.2429	4960	0.0458	-
0.2434	4970	0.0275	-
0.2439	4980	0.0355	-
0.2444	4990	0.0268	-
0.2448	5000	0.0215	-
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0.2478	5060	0.0365	-
0.2483	5070	0.0343	-
0.2488	5080	0.022	-
0.2493	5090	0.0283	-
0.2497	5100	0.0167	-
0.2502	5110	0.0531	-
0.2507	5120	0.0124	-
0.2512	5130	0.0221	-
0.2517	5140	0.0136	-
0.2522	5150	0.0144	-
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0.2546	5200	0.0193	-
0.2551	5210	0.0331	-
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0.2561	5230	0.0127	-
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0.2590	5290	0.0269	-
0.2595	5300	0.0341	-
0.2600	5310	0.0494	-
0.2605	5320	0.0496	-
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0.2625	5360	0.0264	-
0.2630	5370	0.0345	-
0.2635	5380	0.034	-
0.2639	5390	0.025	-
0.2644	5400	0.0242	-
0.2649	5410	0.0197	-
0.2654	5420	0.0256	-
0.2659	5430	0.0288	-
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0.2669	5450	0.0327	-
0.2674	5460	0.035	-
0.2679	5470	0.0247	-
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0.2688	5490	0.03	-
0.2693	5500	0.0392	-
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0.2728	5570	0.0668	-
0.2732	5580	0.0863	-
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0.2742	5600	0.0493	-
0.2747	5610	0.0428	-
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0.2757	5630	0.0661	-
0.2762	5640	0.0591	-
0.2767	5650	0.0329	-
0.2772	5660	0.0603	-
0.2777	5670	0.0637	-
0.2781	5680	0.0292	-
0.2786	5690	0.0171	-
0.2791	5700	0.0156	-
0.2796	5710	0.0358	-
0.2801	5720	0.0368	-
0.2806	5730	0.0351	-
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0.2821	5760	0.0349	-
0.2826	5770	0.0367	-
0.2830	5780	0.0446	-
0.2835	5790	0.0402	-
0.2840	5800	0.0338	-
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0.2850	5820	0.0818	-
0.2855	5830	0.0386	-
0.2860	5840	0.0336	-
0.2865	5850	0.0432	-
0.2870	5860	0.0488	-
0.2874	5870	0.0209	-
0.2879	5880	0.0179	-
0.2884	5890	0.019	-
0.2889	5900	0.0245	-
0.2894	5910	0.0242	-
0.2899	5920	0.0325	-
0.2904	5930	0.0259	-
0.2909	5940	0.0187	-
0.2914	5950	0.0284	-
0.2919	5960	0.0261	-
0.2923	5970	0.0408	-
0.2928	5980	0.0296	-
0.2933	5990	0.0268	-
0.2938	6000	0.0507	0.0185
0.2943	6010	0.0452	-
0.2948	6020	0.0371	-
0.2953	6030	0.0485	-
0.2958	6040	0.0349	-
0.2963	6050	0.0252	-
0.2968	6060	0.0263	-
0.2972	6070	0.0365	-
0.2977	6080	0.0295	-
0.2982	6090	0.0469	-
0.2987	6100	0.0588	-
0.2992	6110	0.0461	-
0.2997	6120	0.047	-
0.3002	6130	0.0132	-
0.3007	6140	0.0393	-
0.3012	6150	0.0548	-
0.3017	6160	0.0238	-
0.3021	6170	0.034	-
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0.3031	6190	0.0304	-
0.3036	6200	0.0268	-
0.3041	6210	0.0281	-
0.3046	6220	0.0415	-
0.3051	6230	0.0176	-
0.3056	6240	0.0389	-
0.3061	6250	0.0512	-
0.3065	6260	0.0212	-
0.3070	6270	0.0297	-
0.3075	6280	0.0201	-
0.3080	6290	0.0518	-
0.3085	6300	0.0279	-
0.3090	6310	0.0277	-
0.3095	6320	0.0157	-
0.3100	6330	0.02	-
0.3105	6340	0.0291	-
0.3110	6350	0.0249	-
0.3114	6360	0.0318	-
0.3119	6370	0.0319	-
0.3124	6380	0.0122	-
0.3129	6390	0.0511	-
0.3134	6400	0.0171	-
0.3139	6410	0.0165	-
0.3144	6420	0.0206	-
0.3149	6430	0.0336	-
0.3154	6440	0.0266	-
0.3159	6450	0.0335	-
0.3163	6460	0.0298	-
0.3168	6470	0.0206	-
0.3173	6480	0.0344	-
0.3178	6490	0.0276	-
0.3183	6500	0.0675	-
0.3188	6510	0.0203	-
0.3193	6520	0.0346	-
0.3198	6530	0.0558	-
0.3203	6540	0.0319	-
0.3207	6550	0.0293	-
0.3212	6560	0.0304	-
0.3217	6570	0.0415	-
0.3222	6580	0.024	-
0.3227	6590	0.0392	-
0.3232	6600	0.0278	-
0.3237	6610	0.0339	-
0.3242	6620	0.0192	-
0.3247	6630	0.0272	-
0.3252	6640	0.0505	-
0.3256	6650	0.0214	-
0.3261	6660	0.0198	-
0.3266	6670	0.0278	-
0.3271	6680	0.0521	-
0.3276	6690	0.0241	-
0.3281	6700	0.0259	-
0.3286	6710	0.0312	-
0.3291	6720	0.0222	-
0.3296	6730	0.0418	-
0.3301	6740	0.0222	-
0.3305	6750	0.0261	-
0.3310	6760	0.035	-
0.3315	6770	0.0232	-
0.3320	6780	0.0119	-
0.3325	6790	0.0131	-
0.3330	6800	0.0173	-
0.3335	6810	0.0324	-
0.3340	6820	0.0162	-
0.3345	6830	0.0319	-
0.3349	6840	0.0373	-
0.3354	6850	0.0166	-
0.3359	6860	0.023	-
0.3364	6870	0.0286	-
0.3369	6880	0.0294	-
0.3374	6890	0.0233	-
0.3379	6900	0.0201	-
0.3384	6910	0.0719	-
0.3389	6920	0.0336	-
0.3394	6930	0.0239	-
0.3398	6940	0.0263	-
0.3403	6950	0.0464	-
0.3408	6960	0.0218	-
0.3413	6970	0.0193	-
0.3418	6980	0.0132	-
0.3423	6990	0.011	-
0.3428	7000	0.0142	-
0.3433	7010	0.0282	-
0.3438	7020	0.0102	-
0.3443	7030	0.0365	-
0.3447	7040	0.0119	-
0.3452	7050	0.0205	-
0.3457	7060	0.0252	-
0.3462	7070	0.0236	-
0.3467	7080	0.0186	-
0.3472	7090	0.0323	-
0.3477	7100	0.0285	-
0.3482	7110	0.0484	-
0.3487	7120	0.0285	-
0.3492	7130	0.026	-
0.3496	7140	0.0386	-
0.3501	7150	0.0183	-
0.3506	7160	0.0184	-
0.3511	7170	0.0305	-
0.3516	7180	0.0223	-
0.3521	7190	0.0361	-
0.3526	7200	0.0368	-
0.3531	7210	0.0307	-
0.3536	7220	0.017	-
0.3540	7230	0.0226	-
0.3545	7240	0.0349	-
0.3550	7250	0.0145	-
0.3555	7260	0.0346	-
0.3560	7270	0.0162	-
0.3565	7280	0.0297	-
0.3570	7290	0.0257	-
0.3575	7300	0.024	-
0.3580	7310	0.0334	-
0.3585	7320	0.0179	-
0.3589	7330	0.0204	-
0.3594	7340	0.0401	-
0.3599	7350	0.0235	-
0.3604	7360	0.0226	-
0.3609	7370	0.0184	-
0.3614	7380	0.0186	-
0.3619	7390	0.0319	-
0.3624	7400	0.0144	-
0.3629	7410	0.0283	-
0.3634	7420	0.0161	-
0.3638	7430	0.0146	-
0.3643	7440	0.017	-
0.3648	7450	0.0229	-
0.3653	7460	0.0225	-
0.3658	7470	0.014	-
0.3663	7480	0.0356	-
0.3668	7490	0.0191	-
0.3673	7500	0.0087	-
0.3678	7510	0.0137	-
0.3682	7520	0.0135	-
0.3687	7530	0.0348	-
0.3692	7540	0.0253	-
0.3697	7550	0.0246	-
0.3702	7560	0.0204	-
0.3707	7570	0.0312	-
0.3712	7580	0.0206	-
0.3717	7590	0.0424	-
0.3722	7600	0.0395	-
0.3727	7610	0.0265	-
0.3731	7620	0.0322	-
0.3736	7630	0.022	-
0.3741	7640	0.0285	-
0.3746	7650	0.0201	-
0.3751	7660	0.0442	-
0.3756	7670	0.0194	-
0.3761	7680	0.0221	-
0.3766	7690	0.0218	-
0.3771	7700	0.0232	-
0.3776	7710	0.024	-
0.3780	7720	0.0249	-
0.3785	7730	0.0287	-
0.3790	7740	0.0259	-
0.3795	7750	0.0154	-
0.3800	7760	0.0183	-
0.3805	7770	0.0274	-
0.3810	7780	0.0282	-
0.3815	7790	0.0251	-
0.3820	7800	0.0272	-
0.3824	7810	0.0337	-
0.3829	7820	0.0424	-
0.3834	7830	0.0127	-
0.3839	7840	0.0253	-
0.3844	7850	0.0211	-
0.3849	7860	0.024	-
0.3854	7870	0.0161	-
0.3859	7880	0.0082	-
0.3864	7890	0.0134	-
0.3869	7900	0.0243	-
0.3873	7910	0.0161	-
0.3878	7920	0.0247	-
0.3883	7930	0.0354	-
0.3888	7940	0.0199	-
0.3893	7950	0.0274	-
0.3898	7960	0.0169	-
0.3903	7970	0.0226	-
0.3908	7980	0.0309	-
0.3913	7990	0.0167	-
0.3918	8000	0.0584	0.0171
0.3922	8010	0.044	-
0.3927	8020	0.0204	-
0.3932	8030	0.0141	-
0.3937	8040	0.04	-
0.3942	8050	0.0275	-
0.3947	8060	0.0103	-
0.3952	8070	0.0128	-
0.3957	8080	0.0112	-
0.3962	8090	0.0125	-
0.3967	8100	0.018	-
0.3971	8110	0.0084	-
0.3976	8120	0.0215	-
0.3981	8130	0.0167	-
0.3986	8140	0.0253	-
0.3991	8150	0.0205	-
0.3996	8160	0.0175	-
0.4001	8170	0.028	-
0.4006	8180	0.0167	-
0.4011	8190	0.0472	-
0.4015	8200	0.0239	-
0.4020	8210	0.0209	-
0.4025	8220	0.024	-
0.4030	8230	0.0385	-
0.4035	8240	0.0168	-
0.4040	8250	0.0199	-
0.4045	8260	0.024	-
0.4050	8270	0.0214	-
0.4055	8280	0.0363	-
0.4060	8290	0.0324	-
0.4064	8300	0.0297	-
0.4069	8310	0.0322	-
0.4074	8320	0.0118	-
0.4079	8330	0.0316	-
0.4084	8340	0.0213	-
0.4089	8350	0.0247	-
0.4094	8360	0.0174	-
0.4099	8370	0.0123	-
0.4104	8380	0.0276	-
0.4109	8390	0.0223	-
0.4113	8400	0.0239	-
0.4118	8410	0.0225	-
0.4123	8420	0.0206	-
0.4128	8430	0.0225	-
0.4133	8440	0.0239	-
0.4138	8450	0.0182	-
0.4143	8460	0.0276	-
0.4148	8470	0.0135	-
0.4153	8480	0.0282	-
0.4157	8490	0.0202	-
0.4162	8500	0.0115	-
0.4167	8510	0.0093	-
0.4172	8520	0.0304	-
0.4177	8530	0.0188	-
0.4182	8540	0.0144	-
0.4187	8550	0.015	-
0.4192	8560	0.0158	-
0.4197	8570	0.0311	-
0.4202	8580	0.0175	-
0.4206	8590	0.0109	-
0.4211	8600	0.0105	-
0.4216	8610	0.0119	-
0.4221	8620	0.0243	-
0.4226	8630	0.0123	-
0.4231	8640	0.0245	-
0.4236	8650	0.0219	-
0.4241	8660	0.0205	-
0.4246	8670	0.0249	-
0.4251	8680	0.0383	-
0.4255	8690	0.0392	-
0.4260	8700	0.0233	-
0.4265	8710	0.0308	-
0.4270	8720	0.0228	-
0.4275	8730	0.0282	-
0.4280	8740	0.0354	-
0.4285	8750	0.0244	-
0.4290	8760	0.0194	-
0.4295	8770	0.012	-
0.4299	8780	0.0191	-
0.4304	8790	0.0189	-
0.4309	8800	0.0262	-
0.4314	8810	0.0317	-
0.4319	8820	0.0227	-
0.4324	8830	0.0244	-
0.4329	8840	0.0182	-
0.4334	8850	0.0231	-
0.4339	8860	0.0288	-
0.4344	8870	0.0423	-
0.4348	8880	0.0638	-
0.4353	8890	0.0615	-
0.4358	8900	0.0422	-
0.4363	8910	0.0256	-
0.4368	8920	0.0316	-
0.4373	8930	0.0233	-
0.4378	8940	0.0212	-
0.4383	8950	0.0234	-
0.4388	8960	0.0151	-
0.4393	8970	0.0143	-
0.4397	8980	0.0118	-
0.4402	8990	0.016	-
0.4407	9000	0.0073	-
0.4412	9010	0.0095	-
0.4417	9020	0.0144	-
0.4422	9030	0.0203	-
0.4427	9040	0.01	-
0.4432	9050	0.0222	-
0.4437	9060	0.017	-
0.4442	9070	0.0118	-
0.4446	9080	0.0134	-
0.4451	9090	0.0104	-
0.4456	9100	0.0107	-
0.4461	9110	0.0113	-
0.4466	9120	0.0104	-
0.4471	9130	0.0261	-
0.4476	9140	0.0188	-
0.4481	9150	0.013	-
0.4486	9160	0.0154	-
0.4490	9170	0.0177	-
0.4495	9180	0.008	-
0.4500	9190	0.0055	-
0.4505	9200	0.0077	-
0.4510	9210	0.0101	-
0.4515	9220	0.0068	-
0.4520	9230	0.0104	-
0.4525	9240	0.0042	-
0.4530	9250	0.0107	-
0.4535	9260	0.007	-
0.4539	9270	0.0101	-
0.4544	9280	0.0079	-
0.4549	9290	0.0095	-
0.4554	9300	0.0102	-
0.4559	9310	0.0086	-
0.4564	9320	0.018	-
0.4569	9330	0.0109	-
0.4574	9340	0.009	-
0.4579	9350	0.008	-
0.4584	9360	0.0112	-
0.4588	9370	0.0099	-
0.4593	9380	0.0069	-
0.4598	9390	0.0081	-
0.4603	9400	0.0091	-
0.4608	9410	0.0189	-
0.4613	9420	0.011	-
0.4618	9430	0.0143	-
0.4623	9440	0.0054	-
0.4628	9450	0.0062	-
0.4632	9460	0.0132	-
0.4637	9470	0.0088	-
0.4642	9480	0.0143	-
0.4647	9490	0.0059	-
0.4652	9500	0.0077	-
0.4657	9510	0.0094	-
0.4662	9520	0.0116	-
0.4667	9530	0.0098	-
0.4672	9540	0.0088	-
0.4677	9550	0.0115	-
0.4681	9560	0.0127	-
0.4686	9570	0.0096	-
0.4691	9580	0.0067	-
0.4696	9590	0.0083	-
0.4701	9600	0.0075	-
0.4706	9610	0.0096	-
0.4711	9620	0.0064	-
0.4716	9630	0.0065	-
0.4721	9640	0.0056	-
0.4726	9650	0.0067	-
0.4730	9660	0.0061	-
0.4735	9670	0.0084	-
0.4740	9680	0.0088	-
0.4745	9690	0.0037	-
0.4750	9700	0.0095	-
0.4755	9710	0.0042	-
0.4760	9720	0.0045	-
0.4765	9730	0.0051	-
0.4770	9740	0.0075	-
0.4774	9750	0.0069	-
0.4779	9760	0.0095	-
0.4784	9770	0.0095	-
0.4789	9780	0.0071	-
0.4794	9790	0.0079	-
0.4799	9800	0.0077	-
0.4804	9810	0.0091	-
0.4809	9820	0.009	-
0.4814	9830	0.0083	-
0.4819	9840	0.008	-
0.4823	9850	0.006	-
0.4828	9860	0.0104	-
0.4833	9870	0.0066	-
0.4838	9880	0.0104	-
0.4843	9890	0.0048	-
0.4848	9900	0.0058	-
0.4853	9910	0.0049	-
0.4858	9920	0.008	-
0.4863	9930	0.0078	-
0.4868	9940	0.0105	-
0.4872	9950	0.0083	-
0.4877	9960	0.0075	-
0.4882	9970	0.0068	-
0.4887	9980	0.0091	-
0.4892	9990	0.0084	-
0.4897	10000	0.009	0.0398
0.4902	10010	0.0072	-
0.4907	10020	0.0062	-
0.4912	10030	0.0104	-
0.4917	10040	0.0124	-
0.4921	10050	0.0062	-
0.4926	10060	0.0047	-
0.4931	10070	0.0066	-
0.4936	10080	0.0084	-
0.4941	10090	0.0069	-
0.4946	10100	0.0043	-
0.4951	10110	0.0035	-
0.4956	10120	0.0065	-
0.4961	10130	0.0044	-
0.4965	10140	0.0077	-
0.4970	10150	0.009	-
0.4975	10160	0.005	-
0.4980	10170	0.0061	-
0.4985	10180	0.0063	-
0.4990	10190	0.0094	-
0.4995	10200	0.0058	-
0.5000	10210	0.0055	-
0.5005	10220	0.0163	-
0.5010	10230	0.0096	-
0.5014	10240	0.0055	-
0.5019	10250	0.0067	-
0.5024	10260	0.0067	-
0.5029	10270	0.0079	-
0.5034	10280	0.0036	-
0.5039	10290	0.0046	-
0.5044	10300	0.0042	-
0.5049	10310	0.0041	-
0.5054	10320	0.006	-
0.5059	10330	0.003	-
0.5063	10340	0.0044	-
0.5068	10350	0.0041	-
0.5073	10360	0.0035	-
0.5078	10370	0.0065	-
0.5083	10380	0.0042	-
0.5088	10390	0.0061	-
0.5093	10400	0.0049	-
0.5098	10410	0.0066	-
0.5103	10420	0.0059	-
0.5107	10430	0.0079	-
0.5112	10440	0.0077	-
0.5117	10450	0.0088	-
0.5122	10460	0.0059	-
0.5127	10470	0.0049	-
0.5132	10480	0.0068	-
0.5137	10490	0.0051	-
0.5142	10500	0.0105	-
0.5147	10510	0.0118	-
0.5152	10520	0.0069	-
0.5156	10530	0.0048	-
0.5161	10540	0.0045	-
0.5166	10550	0.009	-
0.5171	10560	0.0105	-
0.5176	10570	0.0074	-
0.5181	10580	0.0055	-
0.5186	10590	0.0057	-
0.5191	10600	0.0063	-
0.5196	10610	0.0097	-
0.5201	10620	0.0093	-
0.5205	10630	0.0062	-
0.5210	10640	0.0075	-
0.5215	10650	0.0068	-
0.5220	10660	0.0058	-
0.5225	10670	0.0052	-
0.5230	10680	0.0034	-
0.5235	10690	0.0043	-
0.5240	10700	0.0052	-
0.5245	10710	0.0044	-
0.5249	10720	0.0054	-
0.5254	10730	0.0026	-
0.5259	10740	0.0035	-
0.5264	10750	0.0037	-
0.5269	10760	0.0046	-
0.5274	10770	0.0079	-
0.5279	10780	0.009	-
0.5284	10790	0.0053	-
0.5289	10800	0.0042	-
0.5294	10810	0.0037	-
0.5298	10820	0.003	-
0.5303	10830	0.0051	-
0.5308	10840	0.0079	-
0.5313	10850	0.0044	-
0.5318	10860	0.006	-
0.5323	10870	0.0044	-
0.5328	10880	0.0055	-
0.5333	10890	0.0051	-
0.5338	10900	0.005	-
0.5343	10910	0.0076	-
0.5347	10920	0.005	-
0.5352	10930	0.0069	-
0.5357	10940	0.0075	-
0.5362	10950	0.0049	-
0.5367	10960	0.0041	-
0.5372	10970	0.0057	-
0.5377	10980	0.0074	-
0.5382	10990	0.0043	-
0.5387	11000	0.0049	-
0.5392	11010	0.007	-
0.5396	11020	0.0046	-
0.5401	11030	0.0075	-
0.5406	11040	0.0065	-
0.5411	11050	0.0081	-
0.5416	11060	0.0045	-
0.5421	11070	0.0038	-
0.5426	11080	0.0057	-
0.5431	11090	0.0049	-
0.5436	11100	0.0047	-
0.5440	11110	0.0066	-
0.5445	11120	0.0066	-
0.5450	11130	0.0057	-
0.5455	11140	0.0053	-
0.5460	11150	0.0049	-
0.5465	11160	0.0073	-
0.5470	11170	0.0054	-
0.5475	11180	0.0063	-
0.5480	11190	0.0033	-
0.5485	11200	0.003	-
0.5489	11210	0.0046	-
0.5494	11220	0.0042	-
0.5499	11230	0.0031	-
0.5504	11240	0.0101	-
0.5509	11250	0.0033	-
0.5514	11260	0.0037	-
0.5519	11270	0.0047	-
0.5524	11280	0.0054	-
0.5529	11290	0.0039	-
0.5534	11300	0.0055	-
0.5538	11310	0.0058	-
0.5543	11320	0.0079	-
0.5548	11330	0.0072	-
0.5553	11340	0.0033	-
0.5558	11350	0.0049	-
0.5563	11360	0.0065	-
0.5568	11370	0.0019	-
0.5573	11380	0.0031	-
0.5578	11390	0.0043	-
0.5582	11400	0.0029	-
0.5587	11410	0.0028	-
0.5592	11420	0.0035	-
0.5597	11430	0.0037	-
0.5602	11440	0.0033	-
0.5607	11450	0.0032	-
0.5612	11460	0.0073	-
0.5617	11470	0.0063	-
0.5622	11480	0.0065	-
0.5627	11490	0.0036	-
0.5631	11500	0.0102	-
0.5636	11510	0.0063	-
0.5641	11520	0.0063	-
0.5646	11530	0.0075	-
0.5651	11540	0.0057	-
0.5656	11550	0.0046	-
0.5661	11560	0.0039	-
0.5666	11570	0.0045	-
0.5671	11580	0.0066	-
0.5676	11590	0.0062	-
0.5680	11600	0.0075	-
0.5685	11610	0.0065	-
0.5690	11620	0.0043	-
0.5695	11630	0.0051	-
0.5700	11640	0.0054	-
0.5705	11650	0.0048	-
0.5710	11660	0.0051	-
0.5715	11670	0.0041	-
0.5720	11680	0.0031	-
0.5724	11690	0.0044	-
0.5729	11700	0.0046	-
0.5734	11710	0.0041	-
0.5739	11720	0.0059	-
0.5744	11730	0.0041	-
0.5749	11740	0.0094	-
0.5754	11750	0.0115	-
0.5759	11760	0.0039	-
0.5764	11770	0.0043	-
0.5769	11780	0.0027	-
0.5773	11790	0.0075	-
0.5778	11800	0.0049	-
0.5783	11810	0.006	-
0.5788	11820	0.0022	-
0.5793	11830	0.0029	-
0.5798	11840	0.0038	-
0.5803	11850	0.0034	-
0.5808	11860	0.0044	-
0.5813	11870	0.0041	-
0.5818	11880	0.0029	-
0.5822	11890	0.0051	-
0.5827	11900	0.0039	-
0.5832	11910	0.0032	-
0.5837	11920	0.0034	-
0.5842	11930	0.0068	-
0.5847	11940	0.0031	-
0.5852	11950	0.0064	-
0.5857	11960	0.0046	-
0.5862	11970	0.0036	-
0.5867	11980	0.0042	-
0.5871	11990	0.0042	-
0.5876	12000	0.0094	0.0591
0.5881	12010	0.0065	-
0.5886	12020	0.0047	-
0.5891	12030	0.0042	-
0.5896	12040	0.0033	-
0.5901	12050	0.0046	-
0.5906	12060	0.0038	-
0.5911	12070	0.007	-
0.5915	12080	0.0038	-
0.5920	12090	0.008	-
0.5925	12100	0.0048	-
0.5930	12110	0.0053	-
0.5935	12120	0.0054	-
0.5940	12130	0.0045	-
0.5945	12140	0.0054	-
0.5950	12150	0.0044	-
0.5955	12160	0.0026	-
0.5960	12170	0.0034	-
0.5964	12180	0.0046	-
0.5969	12190	0.0052	-
0.5974	12200	0.0032	-
0.5979	12210	0.0057	-
0.5984	12220	0.0051	-
0.5989	12230	0.0069	-
0.5994	12240	0.0028	-
0.5999	12250	0.0043	-
0.6004	12260	0.0041	-
0.6009	12270	0.0045	-
0.6013	12280	0.0044	-
0.6018	12290	0.0028	-
0.6023	12300	0.0033	-
0.6028	12310	0.0035	-
0.6033	12320	0.0027	-
0.6038	12330	0.0088	-
0.6043	12340	0.0057	-
0.6048	12350	0.005	-
0.6053	12360	0.0037	-
0.6057	12370	0.0056	-
0.6062	12380	0.0036	-
0.6067	12390	0.005	-
0.6072	12400	0.004	-
0.6077	12410	0.0065	-
0.6082	12420	0.0067	-
0.6087	12430	0.0039	-
0.6092	12440	0.0033	-
0.6097	12450	0.0059	-
0.6102	12460	0.0048	-
0.6106	12470	0.0027	-
0.6111	12480	0.002	-
0.6116	12490	0.0026	-
0.6121	12500	0.0023	-
0.6126	12510	0.003	-
0.6131	12520	0.0021	-
0.6136	12530	0.0056	-
0.6141	12540	0.0029	-
0.6146	12550	0.0047	-
0.6151	12560	0.0048	-
0.6155	12570	0.0076	-
0.6160	12580	0.0035	-
0.6165	12590	0.0057	-
0.6170	12600	0.004	-
0.6175	12610	0.0066	-
0.6180	12620	0.0052	-
0.6185	12630	0.0038	-
0.6190	12640	0.0046	-
0.6195	12650	0.0027	-
0.6200	12660	0.0036	-
0.6204	12670	0.0058	-
0.6209	12680	0.0041	-
0.6214	12690	0.0053	-
0.6219	12700	0.0065	-
0.6224	12710	0.0047	-
0.6229	12720	0.003	-
0.6234	12730	0.0035	-
0.6239	12740	0.0069	-
0.6244	12750	0.0034	-
0.6248	12760	0.006	-
0.6253	12770	0.0028	-
0.6258	12780	0.003	-
0.6263	12790	0.0047	-
0.6268	12800	0.004	-
0.6273	12810	0.0045	-
0.6278	12820	0.0032	-
0.6283	12830	0.0049	-
0.6288	12840	0.0063	-
0.6293	12850	0.0056	-
0.6297	12860	0.0028	-
0.6302	12870	0.0041	-
0.6307	12880	0.0057	-
0.6312	12890	0.0045	-
0.6317	12900	0.005	-
0.6322	12910	0.0024	-
0.6327	12920	0.0022	-
0.6332	12930	0.0036	-
0.6337	12940	0.0024	-
0.6342	12950	0.005	-
0.6346	12960	0.0049	-
0.6351	12970	0.0031	-
0.6356	12980	0.0057	-
0.6361	12990	0.0024	-
0.6366	13000	0.0021	-
0.6371	13010	0.0031	-
0.6376	13020	0.0042	-
0.6381	13030	0.0037	-
0.6386	13040	0.0036	-
0.6390	13050	0.0048	-
0.6395	13060	0.0021	-
0.6400	13070	0.0043	-
0.6405	13080	0.0034	-
0.6410	13090	0.0068	-
0.6415	13100	0.0075	-
0.6420	13110	0.007	-
0.6425	13120	0.0036	-
0.6430	13130	0.004	-
0.6435	13140	0.0067	-
0.6439	13150	0.004	-
0.6444	13160	0.0041	-
0.6449	13170	0.0041	-
0.6454	13180	0.0038	-
0.6459	13190	0.0025	-
0.6464	13200	0.0057	-
0.6469	13210	0.0092	-
0.6474	13220	0.0046	-
0.6479	13230	0.0047	-
0.6484	13240	0.0029	-
0.6488	13250	0.0028	-
0.6493	13260	0.003	-
0.6498	13270	0.0048	-
0.6503	13280	0.0041	-
0.6508	13290	0.004	-
0.6513	13300	0.0027	-
0.6518	13310	0.0063	-
0.6523	13320	0.0056	-
0.6528	13330	0.002	-
0.6532	13340	0.0049	-
0.6537	13350	0.0045	-
0.6542	13360	0.0042	-
0.6547	13370	0.0025	-
0.6552	13380	0.0017	-
0.6557	13390	0.0024	-
0.6562	13400	0.004	-
0.6567	13410	0.0029	-
0.6572	13420	0.0077	-
0.6577	13430	0.0042	-
0.6581	13440	0.003	-
0.6586	13450	0.0053	-
0.6591	13460	0.0055	-
0.6596	13470	0.0037	-
0.6601	13480	0.0047	-
0.6606	13490	0.0021	-
0.6611	13500	0.0066	-
0.6616	13510	0.0064	-
0.6621	13520	0.0056	-
0.6626	13530	0.0036	-
0.6630	13540	0.0113	-
0.6635	13550	0.0037	-
0.6640	13560	0.0018	-
0.6645	13570	0.0025	-
0.6650	13580	0.0027	-
0.6655	13590	0.004	-
0.6660	13600	0.0042	-
0.6665	13610	0.0019	-
0.6670	13620	0.0029	-
0.6675	13630	0.0025	-
0.6679	13640	0.0044	-
0.6684	13650	0.0039	-
0.6689	13660	0.003	-
0.6694	13670	0.0027	-
0.6699	13680	0.0023	-
0.6704	13690	0.0034	-
0.6709	13700	0.0039	-
0.6714	13710	0.0055	-
0.6719	13720	0.0032	-
0.6723	13730	0.0041	-
0.6728	13740	0.0035	-
0.6733	13750	0.0091	-
0.6738	13760	0.0038	-
0.6743	13770	0.0034	-
0.6748	13780	0.0054	-
0.6753	13790	0.0064	-
0.6758	13800	0.0031	-
0.6763	13810	0.0074	-
0.6768	13820	0.0036	-
0.6772	13830	0.0067	-
0.6777	13840	0.0038	-
0.6782	13850	0.0035	-
0.6787	13860	0.0027	-
0.6792	13870	0.0029	-
0.6797	13880	0.0038	-
0.6802	13890	0.0039	-
0.6807	13900	0.0032	-
0.6812	13910	0.0037	-
0.6817	13920	0.003	-
0.6821	13930	0.005	-
0.6826	13940	0.0032	-
0.6831	13950	0.0026	-
0.6836	13960	0.0043	-
0.6841	13970	0.0032	-
0.6846	13980	0.0056	-
0.6851	13990	0.0031	-
0.6856	14000	0.0027	0.0570
0.6861	14010	0.0015	-
0.6865	14020	0.0032	-
0.6870	14030	0.0032	-
0.6875	14040	0.0029	-
0.6880	14050	0.0023	-
0.6885	14060	0.0044	-
0.6890	14070	0.0042	-
0.6895	14080	0.0015	-
0.6900	14090	0.0018	-
0.6905	14100	0.0021	-
0.6910	14110	0.0023	-
0.6914	14120	0.0044	-
0.6919	14130	0.0024	-
0.6924	14140	0.0043	-
0.6929	14150	0.0029	-
0.6934	14160	0.003	-
0.6939	14170	0.0031	-
0.6944	14180	0.0032	-
0.6949	14190	0.0044	-
0.6954	14200	0.0053	-
0.6959	14210	0.0054	-
0.6963	14220	0.0043	-
0.6968	14230	0.0058	-
0.6973	14240	0.003	-
0.6978	14250	0.0062	-
0.6983	14260	0.003	-
0.6988	14270	0.003	-
0.6993	14280	0.0022	-
0.6998	14290	0.0049	-
0.7003	14300	0.0036	-
0.7007	14310	0.0039	-
0.7012	14320	0.0042	-
0.7017	14330	0.0051	-
0.7022	14340	0.0033	-
0.7027	14350	0.0021	-
0.7032	14360	0.0028	-
0.7037	14370	0.0089	-
0.7042	14380	0.0025	-
0.7047	14390	0.0026	-
0.7052	14400	0.0046	-
0.7056	14410	0.0057	-
0.7061	14420	0.0041	-
0.7066	14430	0.0019	-
0.7071	14440	0.0041	-
0.7076	14450	0.0027	-
0.7081	14460	0.0028	-
0.7086	14470	0.0013	-
0.7091	14480	0.0032	-
0.7096	14490	0.003	-
0.7101	14500	0.0016	-
0.7105	14510	0.0034	-
0.7110	14520	0.0043	-
0.7115	14530	0.0023	-
0.7120	14540	0.0044	-
0.7125	14550	0.003	-
0.7130	14560	0.0028	-
0.7135	14570	0.0024	-
0.7140	14580	0.003	-
0.7145	14590	0.0046	-
0.7150	14600	0.005	-
0.7154	14610	0.002	-
0.7159	14620	0.0046	-
0.7164	14630	0.0044	-
0.7169	14640	0.004	-
0.7174	14650	0.0012	-
0.7179	14660	0.0019	-
0.7184	14670	0.0024	-
0.7189	14680	0.0014	-
0.7194	14690	0.0017	-
0.7198	14700	0.0019	-
0.7203	14710	0.0043	-
0.7208	14720	0.0018	-
0.7213	14730	0.0029	-
0.7218	14740	0.0019	-
0.7223	14750	0.0029	-
0.7228	14760	0.0046	-
0.7233	14770	0.0051	-
0.7238	14780	0.0043	-
0.7243	14790	0.0072	-
0.7247	14800	0.0057	-
0.7252	14810	0.0035	-
0.7257	14820	0.009	-
0.7262	14830	0.0021	-
0.7267	14840	0.0024	-
0.7272	14850	0.0025	-
0.7277	14860	0.0043	-
0.7282	14870	0.0038	-
0.7287	14880	0.0045	-
0.7292	14890	0.0047	-
0.7296	14900	0.0023	-
0.7301	14910	0.0041	-
0.7306	14920	0.0032	-
0.7311	14930	0.0049	-
0.7316	14940	0.0023	-
0.7321	14950	0.0027	-
0.7326	14960	0.0026	-
0.7331	14970	0.0036	-
0.7336	14980	0.0034	-
0.7340	14990	0.0038	-
0.7345	15000	0.0032	-
0.7350	15010	0.0026	-
0.7355	15020	0.0029	-
0.7360	15030	0.0038	-
0.7365	15040	0.0019	-
0.7370	15050	0.0027	-
0.7375	15060	0.002	-
0.7380	15070	0.006	-
0.7385	15080	0.0019	-
0.7389	15090	0.0037	-
0.7394	15100	0.0038	-
0.7399	15110	0.0026	-
0.7404	15120	0.0063	-
0.7409	15130	0.0019	-
0.7414	15140	0.0024	-
0.7419	15150	0.0046	-
0.7424	15160	0.0022	-
0.7429	15170	0.0025	-
0.7434	15180	0.0017	-
0.7438	15190	0.0019	-
0.7443	15200	0.0028	-
0.7448	15210	0.0031	-
0.7453	15220	0.0032	-
0.7458	15230	0.0026	-
0.7463	15240	0.0049	-
0.7468	15250	0.0028	-
0.7473	15260	0.0042	-
0.7478	15270	0.0031	-
0.7482	15280	0.0077	-
0.7487	15290	0.0023	-
0.7492	15300	0.0035	-
0.7497	15310	0.003	-
0.7502	15320	0.0028	-
0.7507	15330	0.0028	-
0.7512	15340	0.0041	-
0.7517	15350	0.0028	-
0.7522	15360	0.0027	-
0.7527	15370	0.0029	-
0.7531	15380	0.0025	-
0.7536	15390	0.0081	-
0.7541	15400	0.0017	-
0.7546	15410	0.0095	-
0.7551	15420	0.0068	-
0.7556	15430	0.0043	-
0.7561	15440	0.0017	-
0.7566	15450	0.0037	-
0.7571	15460	0.0064	-
0.7576	15470	0.0033	-
0.7580	15480	0.0063	-
0.7585	15490	0.0032	-
0.7590	15500	0.0031	-
0.7595	15510	0.006	-
0.7600	15520	0.002	-
0.7605	15530	0.0024	-
0.7610	15540	0.0042	-
0.7615	15550	0.003	-
0.7620	15560	0.002	-
0.7625	15570	0.0018	-
0.7629	15580	0.0022	-
0.7634	15590	0.0039	-
0.7639	15600	0.0026	-
0.7644	15610	0.0028	-
0.7649	15620	0.0034	-
0.7654	15630	0.0021	-
0.7659	15640	0.0031	-
0.7664	15650	0.0028	-
0.7669	15660	0.0031	-
0.7673	15670	0.0024	-
0.7678	15680	0.0038	-
0.7683	15690	0.0048	-
0.7688	15700	0.004	-
0.7693	15710	0.0025	-
0.7698	15720	0.0055	-
0.7703	15730	0.0036	-
0.7708	15740	0.0013	-
0.7713	15750	0.0015	-
0.7718	15760	0.0018	-
0.7722	15770	0.0017	-
0.7727	15780	0.0018	-
0.7732	15790	0.0032	-
0.7737	15800	0.0042	-
0.7742	15810	0.0022	-
0.7747	15820	0.0022	-
0.7752	15830	0.0036	-
0.7757	15840	0.0024	-
0.7762	15850	0.0027	-
0.7767	15860	0.0033	-
0.7771	15870	0.0028	-
0.7776	15880	0.004	-
0.7781	15890	0.0029	-
0.7786	15900	0.0073	-
0.7791	15910	0.0033	-
0.7796	15920	0.0021	-
0.7801	15930	0.005	-
0.7806	15940	0.0027	-
0.7811	15950	0.0028	-
0.7815	15960	0.0026	-
0.7820	15970	0.0056	-
0.7825	15980	0.0039	-
0.7830	15990	0.0035	-
0.7835	16000	0.002	0.0490
0.7840	16010	0.0044	-
0.7845	16020	0.0028	-
0.7850	16030	0.0026	-
0.7855	16040	0.0014	-
0.7860	16050	0.003	-
0.7864	16060	0.0022	-
0.7869	16070	0.0027	-
0.7874	16080	0.0025	-
0.7879	16090	0.0023	-
0.7884	16100	0.0041	-
0.7889	16110	0.0049	-
0.7894	16120	0.0039	-
0.7899	16130	0.0026	-
0.7904	16140	0.0024	-
0.7909	16150	0.0039	-
0.7913	16160	0.0058	-
0.7918	16170	0.0021	-
0.7923	16180	0.003	-
0.7928	16190	0.0027	-
0.7933	16200	0.0018	-
0.7938	16210	0.0046	-
0.7943	16220	0.0016	-
0.7948	16230	0.0023	-
0.7953	16240	0.0023	-
0.7957	16250	0.0011	-
0.7962	16260	0.0047	-
0.7967	16270	0.0014	-
0.7972	16280	0.0015	-
0.7977	16290	0.0015	-
0.7982	16300	0.0049	-
0.7987	16310	0.0024	-
0.7992	16320	0.0024	-
0.7997	16330	0.0018	-
0.8002	16340	0.0027	-
0.8006	16350	0.0042	-
0.8011	16360	0.0046	-
0.8016	16370	0.005	-
0.8021	16380	0.0028	-
0.8026	16390	0.0034	-
0.8031	16400	0.0083	-
0.8036	16410	0.0041	-
0.8041	16420	0.0046	-
0.8046	16430	0.0024	-
0.8051	16440	0.0034	-
0.8055	16450	0.0028	-
0.8060	16460	0.0028	-
0.8065	16470	0.0015	-
0.8070	16480	0.0026	-
0.8075	16490	0.0032	-
0.8080	16500	0.0029	-
0.8085	16510	0.0035	-
0.8090	16520	0.0022	-
0.8095	16530	0.0018	-
0.8100	16540	0.0028	-
0.8104	16550	0.0059	-
0.8109	16560	0.0028	-
0.8114	16570	0.002	-
0.8119	16580	0.0045	-
0.8124	16590	0.0046	-
0.8129	16600	0.0057	-
0.8134	16610	0.0026	-
0.8139	16620	0.0018	-
0.8144	16630	0.004	-
0.8148	16640	0.0028	-
0.8153	16650	0.0051	-
0.8158	16660	0.0036	-
0.8163	16670	0.0012	-
0.8168	16680	0.0019	-
0.8173	16690	0.0027	-
0.8178	16700	0.0042	-
0.8183	16710	0.0027	-
0.8188	16720	0.0037	-
0.8193	16730	0.0023	-
0.8197	16740	0.0037	-
0.8202	16750	0.0021	-
0.8207	16760	0.0024	-
0.8212	16770	0.0019	-
0.8217	16780	0.0036	-
0.8222	16790	0.004	-
0.8227	16800	0.0018	-
0.8232	16810	0.0027	-
0.8237	16820	0.0028	-
0.8242	16830	0.0019	-
0.8246	16840	0.0013	-
0.8251	16850	0.0028	-
0.8256	16860	0.0035	-
0.8261	16870	0.0014	-
0.8266	16880	0.0033	-
0.8271	16890	0.0011	-
0.8276	16900	0.0021	-
0.8281	16910	0.0017	-
0.8286	16920	0.0045	-
0.8290	16930	0.0025	-
0.8295	16940	0.0027	-
0.8300	16950	0.0015	-
0.8305	16960	0.003	-
0.8310	16970	0.0052	-
0.8315	16980	0.0028	-
0.8320	16990	0.0028	-
0.8325	17000	0.0023	-
0.8330	17010	0.0055	-
0.8335	17020	0.0031	-
0.8339	17030	0.0025	-
0.8344	17040	0.0016	-
0.8349	17050	0.0033	-
0.8354	17060	0.0058	-
0.8359	17070	0.0042	-
0.8364	17080	0.0065	-
0.8369	17090	0.0015	-
0.8374	17100	0.0023	-
0.8379	17110	0.0028	-
0.8384	17120	0.0021	-
0.8388	17130	0.0033	-
0.8393	17140	0.0018	-
0.8398	17150	0.0033	-
0.8403	17160	0.0033	-
0.8408	17170	0.002	-
0.8413	17180	0.0038	-
0.8418	17190	0.0016	-
0.8423	17200	0.0028	-
0.8428	17210	0.0045	-
0.8432	17220	0.0017	-
0.8437	17230	0.0023	-
0.8442	17240	0.0024	-
0.8447	17250	0.0017	-
0.8452	17260	0.0038	-
0.8457	17270	0.002	-
0.8462	17280	0.0027	-
0.8467	17290	0.0014	-
0.8472	17300	0.0019	-
0.8477	17310	0.0023	-
0.8481	17320	0.0021	-
0.8486	17330	0.0027	-
0.8491	17340	0.0019	-
0.8496	17350	0.0033	-
0.8501	17360	0.0013	-
0.8506	17370	0.0022	-
0.8511	17380	0.0012	-
0.8516	17390	0.0014	-
0.8521	17400	0.0018	-
0.8526	17410	0.0022	-
0.8530	17420	0.0018	-
0.8535	17430	0.0017	-
0.8540	17440	0.003	-
0.8545	17450	0.0018	-
0.8550	17460	0.0033	-
0.8555	17470	0.0047	-
0.8560	17480	0.0048	-
0.8565	17490	0.0031	-
0.8570	17500	0.0023	-
0.8575	17510	0.0023	-
0.8579	17520	0.0057	-
0.8584	17530	0.0044	-
0.8589	17540	0.0015	-
0.8594	17550	0.0036	-
0.8599	17560	0.0024	-
0.8604	17570	0.0049	-
0.8609	17580	0.0024	-
0.8614	17590	0.0024	-
0.8619	17600	0.0028	-
0.8623	17610	0.0033	-
0.8628	17620	0.0015	-
0.8633	17630	0.0021	-
0.8638	17640	0.0025	-
0.8643	17650	0.0029	-
0.8648	17660	0.0017	-
0.8653	17670	0.0056	-
0.8658	17680	0.0026	-
0.8663	17690	0.0047	-
0.8668	17700	0.0014	-
0.8672	17710	0.0015	-
0.8677	17720	0.0025	-
0.8682	17730	0.0026	-
0.8687	17740	0.0016	-
0.8692	17750	0.0013	-
0.8697	17760	0.0012	-
0.8702	17770	0.0023	-
0.8707	17780	0.0029	-
0.8712	17790	0.0031	-
0.8717	17800	0.0049	-
0.8721	17810	0.0013	-
0.8726	17820	0.0064	-
0.8731	17830	0.0022	-
0.8736	17840	0.0016	-
0.8741	17850	0.003	-
0.8746	17860	0.0014	-
0.8751	17870	0.0067	-
0.8756	17880	0.0083	-
0.8761	17890	0.0019	-
0.8765	17900	0.0016	-
0.8770	17910	0.0033	-
0.8775	17920	0.0041	-
0.8780	17930	0.002	-
0.8785	17940	0.001	-
0.8790	17950	0.0011	-
0.8795	17960	0.0012	-
0.8800	17970	0.0015	-
0.8805	17980	0.0021	-
0.8810	17990	0.0026	-
0.8814	18000	0.0021	0.0448
0.8819	18010	0.002	-
0.8824	18020	0.0014	-
0.8829	18030	0.0042	-
0.8834	18040	0.0029	-
0.8839	18050	0.0021	-
0.8844	18060	0.0054	-
0.8849	18070	0.0019	-
0.8854	18080	0.0027	-
0.8859	18090	0.0027	-
0.8863	18100	0.0027	-
0.8868	18110	0.0024	-
0.8873	18120	0.0015	-
0.8878	18130	0.0018	-
0.8883	18140	0.0024	-
0.8888	18150	0.0032	-
0.8893	18160	0.0032	-
0.8898	18170	0.0031	-
0.8903	18180	0.0017	-
0.8907	18190	0.0018	-
0.8912	18200	0.0037	-
0.8917	18210	0.0031	-
0.8922	18220	0.002	-
0.8927	18230	0.0034	-
0.8932	18240	0.1906	-
0.8937	18250	0.351	-
0.8942	18260	0.5168	-
0.8947	18270	0.5152	-
0.8952	18280	0.523	-
0.8956	18290	0.4944	-
0.8961	18300	0.4338	-
0.8966	18310	0.5081	-
0.8971	18320	0.5696	-
0.8976	18330	0.4026	-
0.8981	18340	0.4199	-
0.8986	18350	0.4634	-
0.8991	18360	0.3412	-
0.8996	18370	0.2186	-
0.9001	18380	0.2601	-
0.9005	18390	0.3498	-
0.9010	18400	0.3581	-
0.9015	18410	0.3591	-
0.9020	18420	0.6837	-
0.9025	18430	0.3771	-
0.9030	18440	0.3668	-
0.9035	18450	0.4416	-
0.9040	18460	0.4595	-
0.9045	18470	0.4018	-
0.9050	18480	0.3949	-
0.9054	18490	0.4405	-
0.9059	18500	0.6876	-
0.9064	18510	0.5136	-
0.9069	18520	0.3375	-
0.9074	18530	0.5366	-
0.9079	18540	0.5452	-
0.9084	18550	0.2111	-
0.9089	18560	0.2063	-
0.9094	18570	0.2081	-
0.9098	18580	0.2191	-
0.9103	18590	0.2627	-
0.9108	18600	0.3576	-
0.9113	18610	0.3057	-
0.9118	18620	0.2285	-
0.9123	18630	0.2382	-
0.9128	18640	0.4497	-
0.9133	18650	0.4454	-
0.9138	18660	0.4261	-
0.9143	18670	0.3817	-
0.9147	18680	0.4061	-
0.9152	18690	0.4599	-
0.9157	18700	0.4495	-
0.9162	18710	0.4845	-
0.9167	18720	0.3828	-
0.9172	18730	0.3363	-
0.9177	18740	0.3168	-
0.9182	18750	0.3446	-
0.9187	18760	0.4216	-
0.9192	18770	0.5225	-
0.9196	18780	0.6365	-
0.9201	18790	0.6862	-
0.9206	18800	0.5061	-
0.9211	18810	0.2393	-
0.9216	18820	0.3754	-
0.9221	18830	0.5556	-
0.9226	18840	0.3949	-
0.9231	18850	0.4205	-
0.9236	18860	0.3714	-
0.9240	18870	0.4053	-
0.9245	18880	0.3883	-
0.9250	18890	0.4215	-
0.9255	18900	0.4832	-
0.9260	18910	0.2436	-
0.9265	18920	0.5187	-
0.9270	18930	0.6508	-
0.9275	18940	0.3121	-
0.9280	18950	0.4087	-
0.9285	18960	0.3446	-
0.9289	18970	0.5238	-
0.9294	18980	0.4235	-
0.9299	18990	0.4245	-
0.9304	19000	0.3187	-
0.9309	19010	0.2934	-
0.9314	19020	0.3663	-
0.9319	19030	0.3008	-
0.9324	19040	0.3393	-
0.9329	19050	0.3709	-
0.9334	19060	0.1932	-
0.9338	19070	0.4171	-
0.9343	19080	0.1919	-
0.9348	19090	0.2027	-
0.9353	19100	0.2582	-
0.9358	19110	0.369	-
0.9363	19120	0.328	-
0.9368	19130	0.3849	-
0.9373	19140	0.3674	-
0.9378	19150	0.3073	-
0.9382	19160	0.5203	-
0.9387	19170	0.4155	-
0.9392	19180	0.7028	-
0.9397	19190	0.3729	-
0.9402	19200	0.5078	-
0.9407	19210	0.3943	-
0.9412	19220	0.4632	-
0.9417	19230	0.3888	-
0.9422	19240	0.3964	-
0.9427	19250	0.455	-
0.9431	19260	0.317	-
0.9436	19270	0.3751	-
0.9441	19280	0.2708	-
0.9446	19290	0.388	-
0.9451	19300	0.3031	-
0.9456	19310	0.4066	-
0.9461	19320	0.5319	-
0.9466	19330	0.4542	-
0.9471	19340	0.3651	-
0.9476	19350	0.5735	-
0.9480	19360	0.5513	-
0.9485	19370	0.4974	-
0.9490	19380	0.4595	-
0.9495	19390	0.5328	-
0.9500	19400	0.3446	-
0.9505	19410	0.6614	-
0.9510	19420	0.2901	-
0.9515	19430	0.4307	-
0.9520	19440	0.4485	-
0.9525	19450	0.3602	-
0.9529	19460	0.2205	-
0.9534	19470	0.2284	-
0.9539	19480	0.3192	-
0.9544	19490	0.3411	-
0.9549	19500	0.3456	-
0.9554	19510	0.5697	-
0.9559	19520	0.4079	-
0.9564	19530	0.3506	-
0.9569	19540	0.3633	-
0.9573	19550	0.4242	-
0.9578	19560	0.3901	-
0.9583	19570	0.3431	-
0.9588	19580	0.2729	-
0.9593	19590	0.7525	-
0.9598	19600	0.5994	-
0.9603	19610	0.3297	-
0.9608	19620	0.3776	-
0.9613	19630	0.5645	-
0.9618	19640	0.2827	-
0.9622	19650	0.1762	-
0.9627	19660	0.2111	-
0.9632	19670	0.189	-
0.9637	19680	0.199	-
0.9642	19690	0.3563	-
0.9647	19700	0.1437	-
0.9652	19710	0.3137	-
0.9657	19720	0.2047	-
0.9662	19730	0.3588	-
0.9667	19740	0.4485	-
0.9671	19750	0.3865	-
0.9676	19760	0.3426	-
0.9681	19770	0.313	-
0.9686	19780	0.3855	-
0.9691	19790	0.5034	-
0.9696	19800	0.3947	-
0.9701	19810	0.3187	-
0.9706	19820	0.4312	-
0.9711	19830	0.3716	-
0.9715	19840	0.3138	-
0.9720	19850	0.432	-
0.9725	19860	0.383	-
0.9730	19870	0.6391	-
0.9735	19880	0.6725	-
0.9740	19890	0.4883	-
0.9745	19900	0.3178	-
0.9750	19910	0.352	-
0.9755	19920	0.5241	-
0.9760	19930	0.3948	-
0.9764	19940	0.4116	-
0.9769	19950	0.2887	-
0.9774	19960	0.3842	-
0.9779	19970	0.3788	-
0.9784	19980	0.3712	-
0.9789	19990	0.4555	-
0.9794	20000	0.3345	0.0061
0.9799	20010	0.4337	-
0.9804	20020	0.6855	-
0.9809	20030	0.314	-
0.9813	20040	0.3292	-
0.9818	20050	0.402	-
0.9823	20060	0.3808	-
0.9828	20070	0.4869	-
0.9833	20080	0.4321	-
0.9838	20090	0.3204	-
0.9843	20100	0.2569	-
0.9848	20110	0.3711	-
0.9853	20120	0.2859	-
0.9857	20130	0.3584	-
0.9862	20140	0.2938	-
0.9867	20150	0.1946	-
0.9872	20160	0.3905	-
0.9877	20170	0.1974	-
0.9882	20180	0.2081	-
0.9887	20190	0.2422	-
0.9892	20200	0.3892	-
0.9897	20210	0.333	-
0.9902	20220	0.3938	-
0.9906	20230	0.387	-
0.9911	20240	0.2612	-
0.9916	20250	0.4627	-
0.9921	20260	0.3612	-
0.9926	20270	0.6533	-
0.9931	20280	0.5566	-
0.9936	20290	0.4453	-
0.9941	20300	0.4542	-
0.9946	20310	0.4094	-
0.9951	20320	0.4279	-
0.9955	20330	0.3092	-
0.9960	20340	0.4567	-
0.9965	20350	0.3881	-
0.9970	20360	0.3317	-
0.9975	20370	0.3048	-
0.9980	20380	0.3111	-
0.9985	20390	0.3632	-
0.9990	20400	0.4409	-
0.9995	20410	0.4903	-
1.0000	20420	0.4353	-

Framework Versions

Python: 3.10.12
Sentence Transformers: 3.0.1
Transformers: 4.42.3
PyTorch: 2.3.1+cu121
Accelerate: 0.32.1
Datasets: 2.20.0
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",
}

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}
}