all-MiniLM-L6-v3-pair_score

This is a sentence-transformers model finetuned from sentence-transformers/all-MiniLM-L6-v2 on the pairs_three_scores_v3 dataset. It maps sentences & paragraphs to a 384-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more.

Model Details

Model Description

• Model Type: Sentence Transformer
• Base model: sentence-transformers/all-MiniLM-L6-v2
• Maximum Sequence Length: 256 tokens
• Output Dimensionality: 384 dimensions
• Similarity Function: Cosine Similarity
• Training Dataset:
  • pairs_three_scores_v3
• Language: en
• License: apache-2.0

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': 256, 'do_lower_case': False, 'architecture': 'BertModel'})
  (1): Pooling({'word_embedding_dimension': 384, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, '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 = [
    'dolo d',
    'wooden coaster',
    'moisturizing tan oil',
]
embeddings = model.encode(sentences)
print(embeddings.shape)
# [3, 384]

# Get the similarity scores for the embeddings
similarities = model.similarity(embeddings, embeddings)
print(similarities)
# tensor([[1.0000, 0.2556, 0.2935],
#         [0.2556, 1.0000, 0.6472],
#         [0.2935, 0.6472, 1.0000]])

Training Details

Training Dataset

pairs_three_scores_v3

• Dataset: pairs_three_scores_v3 at 20443d9
• Size: 9,471,753 training samples
• Columns: sentence1, sentence2, and score
• Approximate statistics based on the first 1000 samples:

  	sentence1	sentence2	score
  type	string	string	float
  details	min: 3 tokens mean: 5.86 tokens max: 64 tokens	min: 3 tokens mean: 5.92 tokens max: 52 tokens	min: 0.13 mean: 0.45 max: 1.0

• Samples:

  sentence1	sentence2	score
  dark teal rashguard	padded cups swimsuit	1.0
  ketchup	chicken taco	0.2318208515644073
  cotton bed suit	candy	0.2588416039943695

• Loss: CoSENTLoss with these parameters:

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

Evaluation Dataset

pairs_three_scores_v3

• Dataset: pairs_three_scores_v3 at 20443d9
• Size: 47,597 evaluation samples
• Columns: sentence1, sentence2, and score
• Approximate statistics based on the first 1000 samples:

  	sentence1	sentence2	score
  type	string	string	float
  details	min: 3 tokens mean: 5.86 tokens max: 52 tokens	min: 3 tokens mean: 5.98 tokens max: 73 tokens	min: 0.14 mean: 0.42 max: 1.0

• Samples:

  sentence1	sentence2	score
  kids toy	crossfit ladder	0.2139182686805725
  cheese fries	printed sarong	0.245885968208313
  foot medicine	mini bot	0.2264718264341354

• Loss: CoSENTLoss with these parameters:

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

Training Hyperparameters

Non-Default Hyperparameters

• eval_strategy: steps
• per_device_train_batch_size: 32
• per_device_eval_batch_size: 32
• learning_rate: 2e-05
• num_train_epochs: 1
• warmup_ratio: 0.1
• fp16: True

All Hyperparameters

Click to expand

• overwrite_output_dir: False
• do_predict: False
• eval_strategy: steps
• prediction_loss_only: True
• per_device_train_batch_size: 32
• per_device_eval_batch_size: 32
• per_gpu_train_batch_size: None
• per_gpu_eval_batch_size: None
• gradient_accumulation_steps: 1
• 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: 1
• max_steps: -1
• lr_scheduler_type: linear
• 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: False
• fp16: True
• 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: None
• hub_always_push: False
• hub_revision: None
• gradient_checkpointing: False
• gradient_checkpointing_kwargs: None
• include_inputs_for_metrics: False
• include_for_metrics: []
• 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
• 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
• liger_kernel_config: None
• eval_use_gather_object: False
• average_tokens_across_devices: False
• prompts: None
• batch_sampler: batch_sampler
• multi_dataset_batch_sampler: proportional
• router_mapping: {}
• learning_rate_mapping: {}

Training Logs

Click to expand

Epoch	Step	Training Loss	Validation Loss
0.0003	100	8.5543	-
0.0007	200	8.6	-
0.0010	300	8.5499	-
0.0014	400	8.4112	-
0.0017	500	8.1668	-
0.0020	600	8.5378	-
0.0024	700	8.219	-
0.0027	800	8.0136	-
0.0030	900	7.984	-
0.0034	1000	7.993	-
0.0037	1100	7.7521	-
0.0041	1200	7.4567	-
0.0044	1300	7.5293	-
0.0047	1400	7.7901	-
0.0051	1500	7.2762	-
0.0054	1600	7.2931	-
0.0057	1700	7.2633	-
0.0061	1800	7.1048	-
0.0064	1900	7.0104	-
0.0068	2000	7.0739	-
0.0071	2100	6.8409	-
0.0074	2200	6.8249	-
0.0078	2300	6.7962	-
0.0081	2400	6.6336	-
0.0084	2500	6.6762	-
0.0088	2600	6.7014	-
0.0091	2700	6.4232	-
0.0095	2800	6.4653	-
0.0098	2900	6.3434	-
0.0101	3000	6.2601	-
0.0105	3100	6.1802	-
0.0108	3200	6.1244	-
0.0111	3300	6.0974	-
0.0115	3400	6.0251	-
0.0118	3500	5.9347	-
0.0122	3600	5.9335	-
0.0125	3700	5.857	-
0.0128	3800	5.812	-
0.0132	3900	5.7809	-
0.0135	4000	5.7333	-
0.0139	4100	5.7377	-
0.0142	4200	5.7161	-
0.0145	4300	5.6978	-
0.0149	4400	5.6842	-
0.0152	4500	5.7181	-
0.0155	4600	5.7154	-
0.0159	4700	5.6806	-
0.0162	4800	5.6344	-
0.0166	4900	5.6526	-
0.0169	5000	5.6194	-
0.0172	5100	5.6385	-
0.0176	5200	5.6033	-
0.0179	5300	5.5977	-
0.0182	5400	5.5977	-
0.0186	5500	5.5902	-
0.0189	5600	5.5953	-
0.0193	5700	5.6296	-
0.0196	5800	5.5941	-
0.0199	5900	5.6035	-
0.0203	6000	5.562	-
0.0206	6100	5.5278	-
0.0209	6200	5.5814	-
0.0213	6300	5.5035	-
0.0216	6400	5.5207	-
0.0220	6500	5.5469	-
0.0223	6600	5.5609	-
0.0226	6700	5.5151	-
0.0230	6800	5.5287	-
0.0233	6900	5.5206	-
0.0236	7000	5.5404	-
0.0240	7100	5.526	-
0.0243	7200	5.4757	-
0.0247	7300	5.4772	-
0.0250	7400	5.4913	-
0.0253	7500	5.5248	-
0.0257	7600	5.4647	-
0.0260	7700	5.5019	-
0.0264	7800	5.4669	-
0.0267	7900	5.5086	-
0.0270	8000	5.4991	-
0.0274	8100	5.4793	-
0.0277	8200	5.4831	-
0.0280	8300	5.4471	-
0.0284	8400	5.4326	-
0.0287	8500	5.4976	-
0.0291	8600	5.4668	-
0.0294	8700	5.4771	-
0.0297	8800	5.4404	-
0.0301	8900	5.4583	-
0.0304	9000	5.4886	-
0.0307	9100	5.4702	-
0.0311	9200	5.4677	-
0.0314	9300	5.4125	-
0.0318	9400	5.3749	-
0.0321	9500	5.4526	-
0.0324	9600	5.4316	-
0.0328	9700	5.4474	-
0.0331	9800	5.416	-
0.0334	9900	5.435	-
0.0338	10000	5.398	-
0.0341	10100	5.4398	-
0.0345	10200	5.3648	-
0.0348	10300	5.4092	-
0.0351	10400	5.3668	-
0.0355	10500	5.4398	-
0.0358	10600	5.3977	-
0.0361	10700	5.3933	-
0.0365	10800	5.3387	-
0.0368	10900	5.427	-
0.0372	11000	5.4103	-
0.0375	11100	5.386	-
0.0378	11200	5.4336	-
0.0382	11300	5.3859	-
0.0385	11400	5.3415	-
0.0389	11500	5.4092	-
0.0392	11600	5.3357	-
0.0395	11700	5.3728	-
0.0399	11800	5.3573	-
0.0402	11900	5.4147	-
0.0405	12000	5.3372	-
0.0409	12100	5.3304	-
0.0412	12200	5.3455	-
0.0416	12300	5.3661	-
0.0419	12400	5.3408	-
0.0422	12500	5.3245	-
0.0426	12600	5.3471	-
0.0429	12700	5.3219	-
0.0432	12800	5.3887	-
0.0436	12900	5.336	-
0.0439	13000	5.3083	-
0.0443	13100	5.3431	-
0.0446	13200	5.3283	-
0.0449	13300	5.2799	-
0.0453	13400	5.2954	-
0.0456	13500	5.3397	-
0.0459	13600	5.3993	-
0.0463	13700	5.2968	-
0.0466	13800	5.3538	-
0.0470	13900	5.3536	-
0.0473	14000	5.2641	-
0.0476	14100	5.3082	-
0.0480	14200	5.3142	-
0.0483	14300	5.3041	-
0.0486	14400	5.324	-
0.0490	14500	5.302	-
0.0493	14600	5.2788	-
0.0497	14700	5.2983	-
0.0500	14800	5.2804	-
0.0503	14900	5.2973	-
0.0507	15000	5.3024	-
0.0510	15100	5.3098	-
0.0514	15200	5.2582	-
0.0517	15300	5.2328	-
0.0520	15400	5.3007	-
0.0524	15500	5.2905	-
0.0527	15600	5.2972	-
0.0530	15700	5.2887	-
0.0534	15800	5.292	-
0.0537	15900	5.2554	-
0.0541	16000	5.2682	-
0.0544	16100	5.2651	-
0.0547	16200	5.2482	-
0.0551	16300	5.2551	-
0.0554	16400	5.2693	-
0.0557	16500	5.3347	-
0.0561	16600	5.2303	-
0.0564	16700	5.2391	-
0.0568	16800	5.2186	-
0.0571	16900	5.2485	-
0.0574	17000	5.2627	-
0.0578	17100	5.2384	-
0.0581	17200	5.2563	-
0.0584	17300	5.2151	-
0.0588	17400	5.2619	-
0.0591	17500	5.247	-
0.0595	17600	5.2767	-
0.0598	17700	5.2704	-
0.0601	17800	5.2618	-
0.0605	17900	5.2537	-
0.0608	18000	5.2114	-
0.0612	18100	5.2842	-
0.0615	18200	5.2284	-
0.0618	18300	5.2392	-
0.0622	18400	5.2839	-
0.0625	18500	5.2267	-
0.0628	18600	5.2084	-
0.0632	18700	5.2299	-
0.0635	18800	5.2147	-
0.0639	18900	5.2464	-
0.0642	19000	5.2392	-
0.0645	19100	5.1927	-
0.0649	19200	5.1818	-
0.0652	19300	5.2327	-
0.0655	19400	5.197	-
0.0659	19500	5.2153	-
0.0662	19600	5.2352	-
0.0666	19700	5.2252	-
0.0669	19800	5.2463	-
0.0672	19900	5.2187	-
0.0676	20000	5.2253	-
0.0679	20100	5.2005	-
0.0682	20200	5.1709	-
0.0686	20300	5.1968	-
0.0689	20400	5.1651	-
0.0693	20500	5.1985	-
0.0696	20600	5.2081	-
0.0699	20700	5.251	-
0.0703	20800	5.2081	-
0.0706	20900	5.1253	-
0.0709	21000	5.2484	-
0.0713	21100	5.1858	-
0.0716	21200	5.1655	-
0.0720	21300	5.2198	-
0.0723	21400	5.2	-
0.0726	21500	5.1432	-
0.0730	21600	5.2466	-
0.0733	21700	5.1881	-
0.0737	21800	5.1995	-
0.0740	21900	5.1741	-
0.0743	22000	5.1876	-
0.0747	22100	5.1496	-
0.0750	22200	5.1809	-
0.0753	22300	5.1816	-
0.0757	22400	5.1937	-
0.0760	22500	5.1642	-
0.0764	22600	5.1701	-
0.0767	22700	5.1906	-
0.0770	22800	5.2037	-
0.0774	22900	5.1287	-
0.0777	23000	5.1497	-
0.0780	23100	5.2365	-
0.0784	23200	5.1887	-
0.0787	23300	5.1839	-
0.0791	23400	5.14	-
0.0794	23500	5.1564	-
0.0797	23600	5.1563	-
0.0801	23700	5.1304	-
0.0804	23800	5.1396	-
0.0807	23900	5.1855	-
0.0811	24000	5.1261	-
0.0814	24100	5.1513	-
0.0818	24200	5.1831	-
0.0821	24300	5.1528	-
0.0824	24400	5.1627	-
0.0828	24500	5.1977	-
0.0831	24600	5.1581	-
0.0834	24700	5.1431	-
0.0838	24800	5.1283	-
0.0841	24900	5.119	-
0.0845	25000	5.16	-
0.0848	25100	5.0883	-
0.0851	25200	5.1296	-
0.0855	25300	5.1656	-
0.0858	25400	5.1838	-
0.0862	25500	5.143	-
0.0865	25600	5.1425	-
0.0868	25700	5.1688	-
0.0872	25800	5.1244	-
0.0875	25900	5.1768	-
0.0878	26000	5.0833	-
0.0882	26100	5.156	-
0.0885	26200	5.1316	-
0.0889	26300	5.0822	-
0.0892	26400	5.171	-
0.0895	26500	5.1086	-
0.0899	26600	5.1662	-
0.0902	26700	5.1199	-
0.0905	26800	5.1017	-
0.0909	26900	5.1395	-
0.0912	27000	5.0965	-
0.0916	27100	5.1601	-
0.0919	27200	5.1287	-
0.0922	27300	5.1043	-
0.0926	27400	5.1731	-
0.0929	27500	5.0753	-
0.0932	27600	5.0652	-
0.0936	27700	5.0486	-
0.0939	27800	5.1666	-
0.0943	27900	5.0874	-
0.0946	28000	5.1067	-
0.0949	28100	5.1343	-
0.0953	28200	5.1388	-
0.0956	28300	5.0612	-
0.0959	28400	5.1483	-
0.0963	28500	5.0916	-
0.0966	28600	5.0832	-
0.0970	28700	5.1159	-
0.0973	28800	5.1106	-
0.0976	28900	5.1023	-
0.0980	29000	5.118	-
0.0983	29100	5.1124	-
0.0987	29200	5.0681	-
0.0990	29300	5.0571	-
0.0993	29400	5.1392	-
0.0997	29500	5.1233	-
0.1000	29600	5.0955	-
0.1003	29700	5.1061	-
0.1007	29800	5.0452	-
0.1010	29900	5.0765	-
0.1014	30000	5.1392	-
0.1017	30100	5.1531	-
0.1020	30200	5.0519	-
0.1024	30300	5.0716	-
0.1027	30400	5.085	-
0.1030	30500	5.0861	-
0.1034	30600	5.0899	-
0.1037	30700	5.1359	-
0.1041	30800	5.1282	-
0.1044	30900	5.0434	-
0.1047	31000	4.9944	-
0.1051	31100	5.0506	-
0.1054	31200	5.0776	-
0.1057	31300	5.0936	-
0.1061	31400	5.1263	-
0.1064	31500	5.0565	-
0.1068	31600	5.0325	-
0.1071	31700	5.0659	-
0.1074	31800	5.0832	-
0.1078	31900	5.0547	-
0.1081	32000	5.076	-
0.1084	32100	5.1404	-
0.1088	32200	5.0772	-
0.1091	32300	5.0456	-
0.1095	32400	5.043	-
0.1098	32500	5.1274	-
0.1101	32600	5.0867	-
0.1105	32700	5.0387	-
0.1108	32800	5.0668	-
0.1112	32900	5.0457	-
0.1115	33000	5.0935	-
0.1118	33100	5.0719	-
0.1122	33200	5.0413	-
0.1125	33300	5.0453	-
0.1128	33400	5.0794	-
0.1132	33500	5.0538	-
0.1135	33600	5.0063	-
0.1139	33700	5.0519	-
0.1142	33800	5.0741	-
0.1145	33900	5.1217	-
0.1149	34000	5.0522	-
0.1152	34100	5.1153	-
0.1155	34200	5.0664	-
0.1159	34300	5.0579	-
0.1162	34400	5.0745	-
0.1166	34500	5.0625	-
0.1169	34600	4.986	-
0.1172	34700	5.0523	-
0.1176	34800	5.0493	-
0.1179	34900	5.0604	-
0.1182	35000	5.092	-
0.1186	35100	5.0126	-
0.1189	35200	5.0364	-
0.1193	35300	5.0786	-
0.1196	35400	4.987	-
0.1199	35500	5.0576	-
0.1203	35600	5.107	-
0.1206	35700	5.0821	-
0.1209	35800	5.0358	-
0.1213	35900	5.0318	-
0.1216	36000	5.0704	-
0.1220	36100	5.0673	-
0.1223	36200	5.0318	-
0.1226	36300	5.0451	-
0.1230	36400	5.0771	-
0.1233	36500	4.9725	-
0.1237	36600	4.9978	-
0.1240	36700	5.0809	-
0.1243	36800	5.082	-
0.1247	36900	5.0218	-
0.1250	37000	5.0966	-
0.1253	37100	5.0324	-
0.1257	37200	5.0176	-
0.1260	37300	4.9759	-
0.1264	37400	5.0103	-
0.1267	37500	5.0879	-
0.1270	37600	5.1212	-
0.1274	37700	5.0088	-
0.1277	37800	5.0324	-
0.1280	37900	5.0377	-
0.1284	38000	4.9602	-
0.1287	38100	5.0729	-
0.1291	38200	5.0652	-
0.1294	38300	5.0473	-
0.1297	38400	5.0464	-
0.1301	38500	5.0358	-
0.1304	38600	5.0125	-
0.1307	38700	4.9896	-
0.1311	38800	5.04	-
0.1314	38900	5.041	-
0.1318	39000	5.0003	-
0.1321	39100	5.0349	-
0.1324	39200	5.0464	-
0.1328	39300	4.9725	-
0.1331	39400	4.9779	-
0.1334	39500	5.0121	-
0.1338	39600	5.0162	-
0.1341	39700	5.0073	-
0.1345	39800	4.9717	-
0.1348	39900	5.0454	-
0.1351	40000	5.0491	-
0.1355	40100	5.0194	-
0.1358	40200	5.0115	-
0.1362	40300	5.0525	-
0.1365	40400	4.9704	-
0.1368	40500	5.007	-
0.1372	40600	5.0687	-
0.1375	40700	4.9654	-
0.1378	40800	4.9286	-
0.1382	40900	4.9936	-
0.1385	41000	5.0092	-
0.1389	41100	4.9932	-
0.1392	41200	4.9964	-
0.1395	41300	5.0209	-
0.1399	41400	4.9691	-
0.1402	41500	4.9788	-
0.1405	41600	4.9373	-
0.1409	41700	5.0369	-
0.1412	41800	4.9693	-
0.1416	41900	5.0034	-
0.1419	42000	5.0015	-
0.1422	42100	5.0444	-
0.1426	42200	5.0619	-
0.1429	42300	4.9554	-
0.1432	42400	4.9683	-
0.1436	42500	4.9994	-
0.1439	42600	4.9749	-
0.1443	42700	4.9638	-
0.1446	42800	5.0391	-
0.1449	42900	5.0378	-
0.1453	43000	5.0482	-
0.1456	43100	4.9923	-
0.1459	43200	5.0294	-
0.1463	43300	4.9877	-
0.1466	43400	4.9689	-
0.1470	43500	4.9814	-
0.1473	43600	4.9876	-
0.1476	43700	4.9566	-
0.1480	43800	4.9699	-
0.1483	43900	5.0062	-
0.1487	44000	5.0232	-
0.1490	44100	4.9744	-
0.1493	44200	4.9793	-
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0.1500	44400	4.9977	-
0.1503	44500	4.9502	-
0.1507	44600	4.9373	-
0.1510	44700	5.0194	-
0.1514	44800	4.94	-
0.1517	44900	4.9778	-
0.1520	45000	5.0185	-
0.1524	45100	5.0341	-
0.1527	45200	4.9483	-
0.1530	45300	4.9309	-
0.1534	45400	4.9241	-
0.1537	45500	4.9292	-
0.1541	45600	4.9899	-
0.1544	45700	4.9306	-
0.1547	45800	5.0179	-
0.1551	45900	4.9933	-
0.1554	46000	4.9675	-
0.1557	46100	5.0506	-
0.1561	46200	5.004	-
0.1564	46300	4.9817	-
0.1568	46400	4.9893	-
0.1571	46500	4.9504	-
0.1574	46600	4.9642	-
0.1578	46700	4.9842	-
0.1581	46800	4.9588	-
0.1584	46900	4.9494	-
0.1588	47000	4.9755	-
0.1591	47100	4.9461	-
0.1595	47200	5.0211	-
0.1598	47300	4.9446	-
0.1601	47400	4.9225	-
0.1605	47500	4.9519	-
0.1608	47600	4.945	-
0.1612	47700	4.9631	-
0.1615	47800	4.9267	-
0.1618	47900	5.0355	-
0.1622	48000	4.9002	-
0.1625	48100	4.9572	-
0.1628	48200	5.0013	-
0.1632	48300	4.9299	-
0.1635	48400	4.9727	-
0.1639	48500	4.9029	-
0.1642	48600	4.9522	-
0.1645	48700	4.9334	-
0.1649	48800	4.9471	-
0.1652	48900	4.996	-
0.1655	49000	4.9827	-
0.1659	49100	4.9589	-
0.1662	49200	4.9481	-
0.1666	49300	4.9706	-
0.1669	49400	4.9905	-
0.1672	49500	4.9558	-
0.1676	49600	4.9106	-
0.1679	49700	4.9778	-
0.1682	49800	4.9378	-
0.1686	49900	4.9751	-
0.1689	50000	4.9972	-
0.1693	50100	4.9111	-
0.1696	50200	5.0006	-
0.1699	50300	4.8554	-
0.1703	50400	4.9431	-
0.1706	50500	5.0108	-
0.1709	50600	4.9781	-
0.1713	50700	4.9461	-
0.1716	50800	4.9513	-
0.1720	50900	4.9632	-
0.1723	51000	5.0076	-
0.1726	51100	4.9223	-
0.1730	51200	4.932	-
0.1733	51300	5.0103	-
0.1737	51400	4.9544	-
0.1740	51500	4.9667	-
0.1743	51600	4.969	-
0.1747	51700	4.9381	-
0.1750	51800	4.9829	-
0.1753	51900	4.8435	-
0.1757	52000	4.9457	-
0.1760	52100	4.9183	-
0.1764	52200	4.9492	-
0.1767	52300	4.9364	-
0.1770	52400	4.9594	-
0.1774	52500	4.9696	-
0.1777	52600	4.9499	-
0.1780	52700	4.8783	-
0.1784	52800	4.9151	-
0.1787	52900	4.9831	-
0.1791	53000	4.9847	-
0.1794	53100	4.9254	-
0.1797	53200	4.9535	-
0.1801	53300	4.9282	-
0.1804	53400	4.9553	-
0.1807	53500	4.9741	-
0.1811	53600	4.9183	-
0.1814	53700	4.9164	-
0.1818	53800	4.9932	-
0.1821	53900	4.9209	-
0.1824	54000	4.8924	-
0.1828	54100	4.9283	-
0.1831	54200	4.8663	-
0.1835	54300	4.9097	-
0.1838	54400	4.9539	-
0.1841	54500	4.8333	-
0.1845	54600	4.9931	-
0.1848	54700	4.924	-
0.1851	54800	4.8957	-
0.1855	54900	4.9357	-
0.1858	55000	4.9503	-
0.1862	55100	4.8727	-
0.1865	55200	4.9348	-
0.1868	55300	4.9341	-
0.1872	55400	4.9663	-
0.1875	55500	4.9695	-
0.1878	55600	4.935	-
0.1882	55700	4.9284	-
0.1885	55800	4.9204	-
0.1889	55900	4.8737	-
0.1892	56000	4.9939	-
0.1895	56100	4.9326	-
0.1899	56200	4.9521	-
0.1902	56300	4.8859	-
0.1905	56400	4.9932	-
0.1909	56500	4.9222	-
0.1912	56600	4.8968	-
0.1916	56700	4.8832	-
0.1919	56800	4.8904	-
0.1922	56900	4.8728	-
0.1926	57000	5.0176	-
0.1929	57100	4.8761	-
0.1932	57200	4.9197	-
0.1936	57300	4.9099	-
0.1939	57400	4.9459	-
0.1943	57500	4.9537	-
0.1946	57600	4.93	-
0.1949	57700	4.9788	-
0.1953	57800	4.8861	-
0.1956	57900	4.9497	-
0.1960	58000	4.9218	-
0.1963	58100	4.8598	-
0.1966	58200	4.8662	-
0.1970	58300	4.9078	-
0.1973	58400	4.9093	-
0.1976	58500	4.9097	-
0.1980	58600	4.9812	-
0.1983	58700	4.9271	-
0.1987	58800	4.9356	-
0.1990	58900	4.9484	-
0.1993	59000	4.9343	-
0.1997	59100	4.9373	-
0.2000	59200	4.8939	-
0.2003	59300	4.9049	-
0.2007	59400	4.9983	-
0.2010	59500	4.9028	-
0.2014	59600	4.9137	-
0.2017	59700	4.9345	-
0.2020	59800	4.8995	-
0.2024	59900	4.8777	-
0.2027	60000	4.9307	-
0.2030	60100	4.9376	-
0.2034	60200	5.0084	-
0.2037	60300	4.9158	-
0.2041	60400	4.8929	-
0.2044	60500	4.9542	-
0.2047	60600	4.902	-
0.2051	60700	4.9411	-
0.2054	60800	4.9208	-
0.2057	60900	4.9301	-
0.2061	61000	4.87	-
0.2064	61100	4.9178	-
0.2068	61200	4.8734	-
0.2071	61300	4.9558	-
0.2074	61400	4.8823	-
0.2078	61500	4.968	-
0.2081	61600	4.9245	-
0.2085	61700	4.884	-
0.2088	61800	4.9429	-
0.2091	61900	4.8694	-
0.2095	62000	4.9184	-
0.2098	62100	4.8312	-
0.2101	62200	5.016	-
0.2105	62300	4.8494	-
0.2108	62400	4.9141	-
0.2112	62500	4.886	-
0.2115	62600	4.9067	-
0.2118	62700	4.9216	-
0.2122	62800	4.9161	-
0.2125	62900	4.8998	-
0.2128	63000	4.9685	-
0.2132	63100	4.8565	-
0.2135	63200	4.8966	-
0.2139	63300	4.8619	-
0.2142	63400	4.8985	-
0.2145	63500	4.919	-
0.2149	63600	4.8981	-
0.2152	63700	4.8751	-
0.2155	63800	4.9504	-
0.2159	63900	4.9268	-
0.2162	64000	4.8953	-
0.2166	64100	4.8928	-
0.2169	64200	4.9416	-
0.2172	64300	4.954	-
0.2176	64400	4.9701	-
0.2179	64500	4.8288	-
0.2182	64600	4.8947	-
0.2186	64700	4.937	-
0.2189	64800	4.9564	-
0.2193	64900	4.9389	-
0.2196	65000	4.9016	-
0.2199	65100	4.9286	-
0.2203	65200	4.8148	-
0.2206	65300	4.8827	-
0.2210	65400	4.9238	-
0.2213	65500	4.9203	-
0.2216	65600	4.8955	-
0.2220	65700	4.9596	-
0.2223	65800	4.8949	-
0.2226	65900	4.9337	-
0.2230	66000	4.922	-
0.2233	66100	4.9209	-
0.2237	66200	4.8248	-
0.2240	66300	4.8552	-
0.2243	66400	4.9219	-
0.2247	66500	4.8865	-
0.2250	66600	4.9245	-
0.2253	66700	4.8662	-
0.2257	66800	4.8957	-
0.2260	66900	4.8718	-
0.2264	67000	4.8851	-
0.2267	67100	4.9095	-
0.2270	67200	4.9115	-
0.2274	67300	4.8678	-
0.2277	67400	4.9343	-
0.2280	67500	4.9016	-
0.2284	67600	4.9622	-
0.2287	67700	4.8757	-
0.2291	67800	4.9506	-
0.2294	67900	4.8308	-
0.2297	68000	4.9111	-
0.2301	68100	4.8584	-
0.2304	68200	4.8509	-
0.2307	68300	4.8663	-
0.2311	68400	4.9019	-
0.2314	68500	4.9005	-
0.2318	68600	4.9656	-
0.2321	68700	4.9261	-
0.2324	68800	4.9777	-
0.2328	68900	4.8981	-
0.2331	69000	4.9077	-
0.2335	69100	4.8928	-
0.2338	69200	4.8908	-
0.2341	69300	4.8863	-
0.2345	69400	4.8638	-
0.2348	69500	4.8793	-
0.2351	69600	4.8441	-
0.2355	69700	4.8761	-
0.2358	69800	4.9386	-
0.2362	69900	4.7907	-
0.2365	70000	4.9164	-
0.2368	70100	4.9436	-
0.2372	70200	4.8705	-
0.2375	70300	4.9411	-
0.2378	70400	4.8095	-
0.2382	70500	4.8982	-
0.2385	70600	4.9643	-
0.2389	70700	4.9109	-
0.2392	70800	4.8748	-
0.2395	70900	4.8604	-
0.2399	71000	4.875	-
0.2402	71100	4.8938	-
0.2405	71200	4.937	-
0.2409	71300	4.8388	-
0.2412	71400	4.8042	-
0.2416	71500	4.8276	-
0.2419	71600	4.9012	-
0.2422	71700	4.8148	-
0.2426	71800	4.825	-
0.2429	71900	4.8757	-
0.2432	72000	4.8921	-
0.2436	72100	4.8451	-
0.2439	72200	4.8799	-
0.2443	72300	4.9356	-
0.2446	72400	4.8407	-
0.2449	72500	4.8695	-
0.2453	72600	4.8583	-
0.2456	72700	4.8534	-
0.2460	72800	4.8507	-
0.2463	72900	4.91	-
0.2466	73000	4.8185	-
0.2470	73100	4.8645	-
0.2473	73200	4.8791	-
0.2476	73300	4.8696	-
0.2480	73400	4.8497	-
0.2483	73500	4.8313	-
0.2487	73600	4.8589	-
0.2490	73700	4.854	-
0.2493	73800	4.8749	-
0.2497	73900	4.7947	-
0.2500	74000	4.8777	-
0.2503	74100	4.8406	-
0.2507	74200	4.7891	-
0.2510	74300	4.8322	-
0.2514	74400	4.8821	-
0.2517	74500	4.869	-
0.2520	74600	4.8612	-
0.2524	74700	4.9032	-
0.2527	74800	4.8653	-
0.2530	74900	4.923	-
0.2534	75000	4.872	-
0.2537	75100	4.8515	-
0.2541	75200	4.8256	-
0.2544	75300	4.8724	-
0.2547	75400	4.7972	-
0.2551	75500	4.9169	-
0.2554	75600	4.8624	-
0.2557	75700	4.8851	-
0.2561	75800	4.9017	-
0.2564	75900	4.8139	-
0.2568	76000	4.9106	-
0.2571	76100	4.8266	-
0.2574	76200	4.9193	-
0.2578	76300	4.8741	-
0.2581	76400	4.8969	-
0.2585	76500	4.8692	-
0.2588	76600	4.8522	-
0.2591	76700	4.8404	-
0.2595	76800	4.8656	-
0.2598	76900	4.9239	-
0.2601	77000	4.8614	-
0.2605	77100	4.8268	-
0.2608	77200	4.9226	-
0.2612	77300	4.9012	-
0.2615	77400	4.932	-
0.2618	77500	4.819	-
0.2622	77600	4.8629	-
0.2625	77700	4.8338	-
0.2628	77800	4.9236	-
0.2632	77900	4.828	-
0.2635	78000	4.8597	-
0.2639	78100	4.7881	-
0.2642	78200	4.8051	-
0.2645	78300	4.8784	-
0.2649	78400	4.8191	-
0.2652	78500	4.8565	-
0.2655	78600	4.8376	-
0.2659	78700	4.8517	-
0.2662	78800	4.8949	-
0.2666	78900	4.8793	-
0.2669	79000	4.7791	-
0.2672	79100	4.9199	-
0.2676	79200	4.8445	-
0.2679	79300	4.7827	-
0.2682	79400	4.866	-
0.2686	79500	4.8705	-
0.2689	79600	4.8263	-
0.2693	79700	4.8025	-
0.2696	79800	4.827	-
0.2699	79900	4.8514	-
0.2703	80000	4.8089	-
0.2706	80100	4.8084	-
0.2710	80200	4.8536	-
0.2713	80300	4.7914	-
0.2716	80400	4.8869	-
0.2720	80500	4.8748	-
0.2723	80600	4.8397	-
0.2726	80700	4.8711	-
0.2730	80800	4.7916	-
0.2733	80900	4.8676	-
0.2737	81000	4.8455	-
0.2740	81100	4.8033	-
0.2743	81200	4.8189	-
0.2747	81300	4.7976	-
0.2750	81400	4.8829	-
0.2753	81500	4.7807	-
0.2757	81600	4.7853	-
0.2760	81700	4.8133	-
0.2764	81800	4.8552	-
0.2767	81900	4.8419	-
0.2770	82000	4.8318	-
0.2774	82100	4.8072	-
0.2777	82200	4.8408	-
0.2780	82300	4.8833	-
0.2784	82400	4.8858	-
0.2787	82500	4.7899	-
0.2791	82600	4.8407	-
0.2794	82700	4.8408	-
0.2797	82800	4.8483	-
0.2801	82900	4.8374	-
0.2804	83000	4.8225	-
0.2807	83100	4.865	-
0.2811	83200	4.8429	-
0.2814	83300	4.897	-
0.2818	83400	4.9233	-
0.2821	83500	4.8291	-
0.2824	83600	4.8229	-
0.2828	83700	4.7985	-
0.2831	83800	4.9004	-
0.2835	83900	4.9049	-
0.2838	84000	4.8724	-
0.2841	84100	4.8195	-
0.2845	84200	4.7831	-
0.2848	84300	4.7885	-
0.2851	84400	4.8864	-
0.2855	84500	4.8668	-
0.2858	84600	4.8301	-
0.2862	84700	4.9238	-
0.2865	84800	4.8212	-
0.2868	84900	4.7935	-
0.2872	85000	4.8198	-
0.2875	85100	4.8165	-
0.2878	85200	4.8578	-
0.2882	85300	4.8953	-
0.2885	85400	4.7093	-
0.2889	85500	4.9052	-
0.2892	85600	4.8578	-
0.2895	85700	4.8389	-
0.2899	85800	4.8274	-
0.2902	85900	4.7641	-
0.2905	86000	4.765	-
0.2909	86100	4.7944	-
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0.4527	134000	4.8497	-
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0.4571	135300	4.7955	-
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0.4578	135500	4.7923	-
0.4581	135600	4.8161	-
0.4585	135700	4.7095	-
0.4588	135800	4.6835	-
0.4591	135900	4.7729	-
0.4595	136000	4.7836	-
0.4598	136100	4.7744	-
0.4601	136200	4.751	-
0.4605	136300	4.724	-
0.4608	136400	4.7315	-
0.4612	136500	4.6854	-
0.4615	136600	4.7644	-
0.4618	136700	4.6637	-
0.4622	136800	4.7639	-
0.4625	136900	4.6893	-
0.4628	137000	4.6992	-
0.4632	137100	4.7812	-
0.4635	137200	4.6695	-
0.4639	137300	4.6704	-
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0.4669	138200	4.7775	-
0.4672	138300	4.6602	-
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0.4679	138500	4.7543	-
0.4683	138600	4.6303	-
0.4686	138700	4.8106	-
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0.4693	138900	4.884	-
0.4696	139000	4.6839	-
0.4699	139100	4.7111	-
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0.4706	139300	4.6728	-
0.4710	139400	4.7015	-
0.4713	139500	4.6443	-
0.4716	139600	4.724	-
0.4720	139700	4.7221	-
0.4723	139800	4.5826	-
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0.4737	140200	4.7445	-
0.4740	140300	4.7233	-
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0.4750	140600	4.6838	-
0.4753	140700	4.8154	-
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0.4760	140900	4.7108	-
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0.4770	141200	4.6665	-
0.4774	141300	4.7833	-
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0.4781	141500	4.6586	-
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0.4797	142000	4.6844	-
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0.4811	142400	4.6704	-
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0.4831	143000	4.7454	-
0.4835	143100	4.7122	-
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0.4841	143300	4.6896	-
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0.4848	143500	4.7223	-
0.4851	143600	4.7106	-
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0.4862	143900	4.7906	-
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0.4872	144200	4.7414	-
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0.4882	144500	4.698	-
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0.4892	144800	4.6632	-
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0.4899	145000	4.6944	-
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0.4919	145600	4.6715	-
0.4922	145700	4.6927	-
0.4926	145800	4.7019	-
0.4929	145900	4.6687	-
0.4933	146000	4.7311	-
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0.4943	146300	4.6594	-
0.4946	146400	4.674	-
0.4949	146500	4.6295	-
0.4953	146600	4.7388	-
0.4956	146700	4.7162	-
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0.4966	147000	4.6773	-
0.4970	147100	4.7562	-
0.4973	147200	4.6998	-
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0.4987	147600	4.7344	-
0.4990	147700	4.7014	-
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0.5000	148000	4.6944	-
0.5003	148100	4.7577	-
0.5007	148200	4.7891	-
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0.5020	148600	4.7433	-
0.5024	148700	4.6152	-
0.5027	148800	4.7571	-
0.5031	148900	4.6796	-
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0.5041	149200	4.8069	-
0.5044	149300	4.7195	-
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0.5051	149500	4.6431	-
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0.5061	149800	4.6615	-
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0.5078	150300	4.6797	-
0.5081	150400	4.7033	-
0.5085	150500	4.8781	-
0.5088	150600	4.6808	-
0.5091	150700	4.7395	-
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0.5101	151000	4.6796	-
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0.5145	152300	4.6838	-
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0.5183	153400	4.8271	-
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0.5210	154200	4.6795	-
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0.5220	154500	4.7647	-
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0.5230	154800	4.6482	-
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0.5260	155700	4.8037	-
0.5264	155800	4.6777	-
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0.5270	156000	4.7203	-
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0.5281	156300	4.7317	-
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0.5291	156600	4.7314	-
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0.5297	156800	4.6351	-
0.5301	156900	4.7522	-
0.5304	157000	4.7046	-
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0.5314	157300	4.7506	-
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0.5331	157800	4.7169	-
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0.5362	158700	4.701	-
0.5365	158800	4.6056	-
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0.5372	159000	4.6513	-
0.5375	159100	4.669	-
0.5379	159200	4.7366	-
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0.5389	159500	4.72	-
0.5392	159600	4.6308	-
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0.5399	159800	4.6884	-
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0.5412	160200	4.6639	-
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0.5422	160500	4.7935	-
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0.5460	161600	4.7046	-
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0.5480	162200	4.6746	-
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0.5490	162500	4.6045	-
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0.5500	162800	4.7468	-
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0.5544	164100	4.6418	-
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0.5561	164600	4.7379	-
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0.5598	165700	4.5861	-
0.5601	165800	4.6545	-
0.5605	165900	4.7388	-
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0.5612	166100	4.6553	-
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0.5632	166700	4.6993	-
0.5635	166800	4.7092	-
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0.5699	168700	4.7395	-
0.5703	168800	4.6949	-
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0.5770	170800	4.6347	-
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0.5828	172500	4.6596	-
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0.5862	173500	4.6076	-
0.5865	173600	4.7478	-
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0.5872	173800	4.6594	-
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0.5960	176400	4.6301	-
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0.6000	177600	4.657	-
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0.6020	178200	4.7506	-
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0.6041	178800	4.8092	-
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0.6047	179000	4.6565	-
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0.6068	179600	4.6688	-
0.6071	179700	4.6643	-
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0.6081	180000	4.6667	-
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0.6088	180200	4.6038	-
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0.6098	180500	4.6707	-
0.6101	180600	4.6743	-
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0.6210	183800	4.691	-
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0.6216	184000	4.6506	-
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0.6240	184700	4.7039	-
0.6243	184800	4.667	-
0.6247	184900	4.7222	-
0.6250	185000	4.6671	-
0.6254	185100	4.6702	-
0.6257	185200	4.6873	-
0.6260	185300	4.6785	-
0.6264	185400	4.6393	-
0.6267	185500	4.7059	-
0.6270	185600	4.676	-
0.6274	185700	4.6765	-
0.6277	185800	4.6249	-
0.6281	185900	4.6901	-
0.6284	186000	4.6554	-
0.6287	186100	4.6876	-
0.6291	186200	4.6714	-
0.6294	186300	4.7065	-
0.6297	186400	4.6572	-
0.6301	186500	4.6669	-
0.6304	186600	4.6027	-
0.6308	186700	4.6617	-
0.6311	186800	4.6518	-
0.6314	186900	4.6979	-
0.6318	187000	4.6411	-
0.6321	187100	4.7108	-
0.6324	187200	4.6817	-
0.6328	187300	4.6116	-
0.6331	187400	4.6677	-
0.6335	187500	4.6177	-
0.6338	187600	4.7113	-
0.6341	187700	4.6839	-
0.6345	187800	4.6725	-
0.6348	187900	4.6614	-
0.6352	188000	4.5772	-
0.6355	188100	4.6979	-
0.6358	188200	4.6254	-
0.6362	188300	4.6939	-
0.6365	188400	4.65	-
0.6368	188500	4.6666	-
0.6372	188600	4.6809	-
0.6375	188700	4.6512	-
0.6379	188800	4.7251	-
0.6382	188900	4.65	-
0.6385	189000	4.6214	-
0.6389	189100	4.6703	-
0.6392	189200	4.5938	-
0.6395	189300	4.6532	-
0.6399	189400	4.7226	-
0.6402	189500	4.6983	-
0.6406	189600	4.663	-
0.6409	189700	4.7063	-
0.6412	189800	4.5957	-
0.6416	189900	4.7002	-
0.6419	190000	4.7104	-
0.6422	190100	4.6746	-
0.6426	190200	4.6445	-
0.6429	190300	4.6054	-
0.6433	190400	4.6656	-
0.6436	190500	4.561	-
0.6439	190600	4.7579	-
0.6443	190700	4.6431	-
0.6446	190800	4.7412	-
0.6449	190900	4.661	-
0.6453	191000	4.7368	-
0.6456	191100	4.629	-
0.6460	191200	4.6131	-
0.6463	191300	4.6785	-
0.6466	191400	4.5914	-
0.6470	191500	4.6606	-
0.6473	191600	4.5756	-
0.6477	191700	4.7797	-
0.6480	191800	4.6121	-
0.6483	191900	4.6868	-
0.6487	192000	4.6266	-
0.6490	192100	4.6889	-
0.6493	192200	4.6566	-
0.6497	192300	4.6248	-
0.6500	192400	4.6098	-
0.6504	192500	4.6675	-
0.6507	192600	4.6891	-
0.6510	192700	4.6184	-
0.6514	192800	4.6093	-
0.6517	192900	4.6766	-
0.6520	193000	4.5773	-
0.6524	193100	4.6591	-
0.6527	193200	4.7481	-
0.6531	193300	4.6256	-
0.6534	193400	4.6511	-
0.6537	193500	4.6891	-
0.6541	193600	4.6556	-
0.6544	193700	4.6749	-
0.6547	193800	4.675	-
0.6551	193900	4.6678	-
0.6554	194000	4.5453	-
0.6558	194100	4.6272	-
0.6561	194200	4.5856	-
0.6564	194300	4.6846	-
0.6568	194400	4.6062	-
0.6571	194500	4.6386	-
0.6574	194600	4.7001	-
0.6578	194700	4.6966	-
0.6581	194800	4.6919	-
0.6585	194900	4.5803	-
0.6588	195000	4.6551	-
0.6591	195100	4.6499	-
0.6595	195200	4.6821	-
0.6598	195300	4.6868	-
0.6602	195400	4.619	-
0.6605	195500	4.7671	-
0.6608	195600	4.6564	-
0.6612	195700	4.6239	-
0.6615	195800	4.6407	-
0.6618	195900	4.6056	-
0.6622	196000	4.6464	-
0.6625	196100	4.7235	-
0.6629	196200	4.7211	-
0.6632	196300	4.6475	-
0.6635	196400	4.6311	-
0.6639	196500	4.7162	-
0.6642	196600	4.6896	-
0.6645	196700	4.6401	-
0.6649	196800	4.7735	-
0.6652	196900	4.6211	-
0.6656	197000	4.6301	-
0.6659	197100	4.7239	-
0.6662	197200	4.6734	-
0.6666	197300	4.6558	-
0.6669	197400	4.5721	-
0.6672	197500	4.6804	-
0.6676	197600	4.6266	-
0.6679	197700	4.6908	-
0.6683	197800	4.633	-
0.6686	197900	4.6401	-
0.6689	198000	4.7082	-
0.6693	198100	4.6086	-
0.6696	198200	4.6743	-
0.6699	198300	4.6685	-
0.6703	198400	4.6242	-
0.6706	198500	4.623	-
0.6710	198600	4.6207	-
0.6713	198700	4.6485	-
0.6716	198800	4.62	-
0.6720	198900	4.6605	-
0.6723	199000	4.6116	-
0.6727	199100	4.5975	-
0.6730	199200	4.7411	-
0.6733	199300	4.7502	-
0.6737	199400	4.6544	-
0.6740	199500	4.643	-
0.6743	199600	4.6182	-
0.6747	199700	4.5569	-
0.6750	199800	4.6494	-
0.6754	199900	4.5972	-
0.6757	200000	4.6037	4.5804
0.6760	200100	4.6539	-
0.6764	200200	4.6243	-
0.6767	200300	4.6918	-
0.6770	200400	4.6751	-
0.6774	200500	4.7557	-
0.6777	200600	4.7255	-
0.6781	200700	4.624	-
0.6784	200800	4.6623	-
0.6787	200900	4.6663	-
0.6791	201000	4.6898	-
0.6794	201100	4.5559	-
0.6797	201200	4.6779	-
0.6801	201300	4.7504	-
0.6804	201400	4.6132	-
0.6808	201500	4.6373	-
0.6811	201600	4.7183	-
0.6814	201700	4.7015	-
0.6818	201800	4.5986	-
0.6821	201900	4.6804	-
0.6824	202000	4.6249	-
0.6828	202100	4.6387	-
0.6831	202200	4.6591	-
0.6835	202300	4.5611	-
0.6838	202400	4.7111	-
0.6841	202500	4.6015	-
0.6845	202600	4.6682	-
0.6848	202700	4.6468	-
0.6852	202800	4.6664	-
0.6855	202900	4.589	-
0.6858	203000	4.7717	-
0.6862	203100	4.6542	-
0.6865	203200	4.7438	-
0.6868	203300	4.6261	-
0.6872	203400	4.6238	-
0.6875	203500	4.6817	-
0.6879	203600	4.5846	-
0.6882	203700	4.6583	-
0.6885	203800	4.6171	-
0.6889	203900	4.5854	-
0.6892	204000	4.5745	-
0.6895	204100	4.6627	-
0.6899	204200	4.6322	-
0.6902	204300	4.5383	-
0.6906	204400	4.5127	-
0.6909	204500	4.6428	-
0.6912	204600	4.7206	-
0.6916	204700	4.76	-
0.6919	204800	4.6241	-
0.6922	204900	4.6365	-
0.6926	205000	4.6757	-
0.6929	205100	4.6773	-
0.6933	205200	4.6548	-
0.6936	205300	4.6325	-
0.6939	205400	4.702	-
0.6943	205500	4.64	-
0.6946	205600	4.6663	-
0.6949	205700	4.664	-
0.6953	205800	4.6865	-
0.6956	205900	4.5985	-
0.6960	206000	4.6796	-
0.6963	206100	4.7169	-
0.6966	206200	4.6239	-
0.6970	206300	4.7006	-
0.6973	206400	4.5942	-
0.6977	206500	4.6937	-
0.6980	206600	4.7372	-
0.6983	206700	4.6236	-
0.6987	206800	4.6329	-
0.6990	206900	4.7235	-
0.6993	207000	4.5949	-
0.6997	207100	4.6743	-
0.7000	207200	4.5565	-
0.7004	207300	4.5708	-
0.7007	207400	4.6195	-
0.7010	207500	4.6248	-
0.7014	207600	4.6835	-
0.7017	207700	4.5655	-
0.7020	207800	4.5928	-
0.7024	207900	4.6106	-
0.7027	208000	4.5974	-
0.7031	208100	4.6228	-
0.7034	208200	4.6159	-
0.7037	208300	4.6518	-
0.7041	208400	4.7231	-
0.7044	208500	4.5966	-
0.7047	208600	4.5124	-
0.7051	208700	4.6594	-
0.7054	208800	4.6825	-
0.7058	208900	4.5726	-
0.7061	209000	4.6167	-
0.7064	209100	4.6394	-
0.7068	209200	4.7166	-
0.7071	209300	4.6863	-
0.7074	209400	4.7215	-
0.7078	209500	4.6055	-
0.7081	209600	4.6544	-
0.7085	209700	4.5987	-
0.7088	209800	4.6753	-
0.7091	209900	4.6066	-
0.7095	210000	4.6382	-
0.7098	210100	4.5916	-
0.7102	210200	4.6123	-
0.7105	210300	4.6636	-
0.7108	210400	4.6439	-
0.7112	210500	4.6226	-
0.7115	210600	4.6727	-
0.7118	210700	4.7274	-
0.7122	210800	4.5984	-
0.7125	210900	4.6477	-
0.7129	211000	4.64	-
0.7132	211100	4.6815	-
0.7135	211200	4.675	-
0.7139	211300	4.5718	-
0.7142	211400	4.6904	-
0.7145	211500	4.6715	-
0.7149	211600	4.7033	-
0.7152	211700	4.6818	-
0.7156	211800	4.7371	-
0.7159	211900	4.655	-
0.7162	212000	4.6279	-
0.7166	212100	4.7222	-
0.7169	212200	4.6239	-
0.7172	212300	4.6193	-
0.7176	212400	4.6009	-
0.7179	212500	4.6173	-
0.7183	212600	4.6154	-
0.7186	212700	4.6433	-
0.7189	212800	4.6439	-
0.7193	212900	4.5957	-
0.7196	213000	4.6455	-
0.7199	213100	4.5805	-
0.7203	213200	4.6963	-
0.7206	213300	4.5329	-
0.7210	213400	4.6601	-
0.7213	213500	4.5894	-
0.7216	213600	4.8046	-
0.7220	213700	4.7427	-
0.7223	213800	4.7097	-
0.7227	213900	4.6546	-
0.7230	214000	4.5736	-
0.7233	214100	4.6021	-
0.7237	214200	4.6402	-
0.7240	214300	4.5504	-
0.7243	214400	4.5843	-
0.7247	214500	4.6045	-
0.7250	214600	4.7333	-
0.7254	214700	4.6959	-
0.7257	214800	4.5134	-
0.7260	214900	4.728	-
0.7264	215000	4.6241	-
0.7267	215100	4.6747	-
0.7270	215200	4.6681	-
0.7274	215300	4.622	-
0.7277	215400	4.6669	-
0.7281	215500	4.5575	-
0.7284	215600	4.523	-
0.7287	215700	4.6242	-
0.7291	215800	4.6411	-
0.7294	215900	4.6326	-
0.7297	216000	4.6214	-
0.7301	216100	4.5598	-
0.7304	216200	4.6492	-
0.7308	216300	4.6688	-
0.7311	216400	4.6199	-
0.7314	216500	4.5592	-
0.7318	216600	4.6537	-
0.7321	216700	4.604	-
0.7324	216800	4.6516	-
0.7328	216900	4.5904	-
0.7331	217000	4.6891	-
0.7335	217100	4.7161	-
0.7338	217200	4.6833	-
0.7341	217300	4.5865	-
0.7345	217400	4.5641	-
0.7348	217500	4.7499	-
0.7352	217600	4.6742	-
0.7355	217700	4.6315	-
0.7358	217800	4.7007	-
0.7362	217900	4.6217	-
0.7365	218000	4.6192	-
0.7368	218100	4.5966	-
0.7372	218200	4.6803	-
0.7375	218300	4.7183	-
0.7379	218400	4.6618	-
0.7382	218500	4.6156	-
0.7385	218600	4.6882	-
0.7389	218700	4.6845	-
0.7392	218800	4.7828	-
0.7395	218900	4.6553	-
0.7399	219000	4.6999	-
0.7402	219100	4.6564	-
0.7406	219200	4.5762	-
0.7409	219300	4.6706	-
0.7412	219400	4.565	-
0.7416	219500	4.6427	-
0.7419	219600	4.6527	-
0.7422	219700	4.6282	-
0.7426	219800	4.6044	-
0.7429	219900	4.5578	-
0.7433	220000	4.6157	-
0.7436	220100	4.6018	-
0.7439	220200	4.5898	-
0.7443	220300	4.5915	-
0.7446	220400	4.6314	-
0.7450	220500	4.6481	-
0.7453	220600	4.6798	-
0.7456	220700	4.6027	-
0.7460	220800	4.5924	-
0.7463	220900	4.638	-
0.7466	221000	4.6618	-
0.7470	221100	4.672	-
0.7473	221200	4.6112	-
0.7477	221300	4.5848	-
0.7480	221400	4.5729	-
0.7483	221500	4.6826	-
0.7487	221600	4.5897	-
0.7490	221700	4.5578	-
0.7493	221800	4.6853	-
0.7497	221900	4.6699	-
0.7500	222000	4.7051	-
0.7504	222100	4.6029	-
0.7507	222200	4.5719	-
0.7510	222300	4.775	-
0.7514	222400	4.5979	-
0.7517	222500	4.6986	-
0.7520	222600	4.6515	-
0.7524	222700	4.613	-
0.7527	222800	4.6109	-
0.7531	222900	4.7493	-
0.7534	223000	4.7111	-
0.7537	223100	4.6356	-
0.7541	223200	4.6255	-
0.7544	223300	4.5987	-
0.7547	223400	4.5941	-
0.7551	223500	4.6613	-
0.7554	223600	4.6039	-
0.7558	223700	4.6423	-
0.7561	223800	4.7027	-
0.7564	223900	4.6111	-
0.7568	224000	4.5998	-
0.7571	224100	4.5895	-
0.7575	224200	4.6274	-
0.7578	224300	4.6138	-
0.7581	224400	4.4961	-
0.7585	224500	4.7239	-
0.7588	224600	4.6285	-
0.7591	224700	4.5718	-
0.7595	224800	4.6509	-
0.7598	224900	4.6357	-
0.7602	225000	4.6802	-
0.7605	225100	4.5804	-
0.7608	225200	4.7032	-
0.7612	225300	4.6631	-
0.7615	225400	4.625	-
0.7618	225500	4.5714	-
0.7622	225600	4.7166	-
0.7625	225700	4.543	-
0.7629	225800	4.6289	-
0.7632	225900	4.5626	-
0.7635	226000	4.6663	-
0.7639	226100	4.6967	-
0.7642	226200	4.5398	-
0.7645	226300	4.6467	-
0.7649	226400	4.5245	-
0.7652	226500	4.5999	-
0.7656	226600	4.751	-
0.7659	226700	4.5669	-
0.7662	226800	4.5648	-
0.7666	226900	4.7044	-
0.7669	227000	4.7227	-
0.7672	227100	4.681	-
0.7676	227200	4.6226	-
0.7679	227300	4.6115	-
0.7683	227400	4.5628	-
0.7686	227500	4.6109	-
0.7689	227600	4.704	-
0.7693	227700	4.6666	-
0.7696	227800	4.6159	-
0.7700	227900	4.5714	-
0.7703	228000	4.6994	-
0.7706	228100	4.674	-
0.7710	228200	4.7008	-
0.7713	228300	4.6058	-
0.7716	228400	4.6955	-
0.7720	228500	4.6254	-
0.7723	228600	4.5242	-
0.7727	228700	4.6018	-
0.7730	228800	4.6674	-
0.7733	228900	4.6551	-
0.7737	229000	4.5228	-
0.7740	229100	4.6108	-
0.7743	229200	4.5934	-
0.7747	229300	4.6229	-
0.7750	229400	4.6158	-
0.7754	229500	4.6586	-
0.7757	229600	4.534	-
0.7760	229700	4.5963	-
0.7764	229800	4.7194	-
0.7767	229900	4.6186	-
0.7770	230000	4.8805	-
0.7774	230100	4.63	-
0.7777	230200	4.7365	-
0.7781	230300	4.5724	-
0.7784	230400	4.5515	-
0.7787	230500	4.6472	-
0.7791	230600	4.6097	-
0.7794	230700	4.5165	-
0.7797	230800	4.6627	-
0.7801	230900	4.789	-
0.7804	231000	4.6284	-
0.7808	231100	4.6798	-
0.7811	231200	4.7489	-
0.7814	231300	4.6356	-
0.7818	231400	4.6074	-
0.7821	231500	4.6819	-
0.7825	231600	4.5683	-
0.7828	231700	4.6367	-
0.7831	231800	4.5847	-
0.7835	231900	4.634	-
0.7838	232000	4.6957	-
0.7841	232100	4.6328	-
0.7845	232200	4.6399	-
0.7848	232300	4.566	-
0.7852	232400	4.6884	-
0.7855	232500	4.5541	-
0.7858	232600	4.5546	-
0.7862	232700	4.6591	-
0.7865	232800	4.725	-
0.7868	232900	4.7127	-
0.7872	233000	4.6798	-
0.7875	233100	4.7058	-
0.7879	233200	4.5458	-
0.7882	233300	4.7082	-
0.7885	233400	4.6206	-
0.7889	233500	4.6633	-
0.7892	233600	4.7019	-
0.7895	233700	4.6532	-
0.7899	233800	4.6198	-
0.7902	233900	4.5592	-
0.7906	234000	4.5189	-
0.7909	234100	4.54	-
0.7912	234200	4.5296	-
0.7916	234300	4.6198	-
0.7919	234400	4.6321	-
0.7922	234500	4.5789	-
0.7926	234600	4.6352	-
0.7929	234700	4.6204	-
0.7933	234800	4.6504	-
0.7936	234900	4.5938	-
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0.7946	235200	4.6471	-
0.7950	235300	4.6646	-
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0.7960	235600	4.6472	-
0.7963	235700	4.6232	-
0.7966	235800	4.5407	-
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0.7980	236200	4.6611	-
0.7983	236300	4.6296	-
0.7987	236400	4.5847	-
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0.8000	236800	4.5793	-
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0.8020	237400	4.5835	-
0.8024	237500	4.5398	-
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0.8031	237700	4.7239	-
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0.8041	238000	4.5771	-
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0.8054	238400	4.6823	-
0.8058	238500	4.5902	-
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0.8064	238700	4.6177	-
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0.8088	239400	4.7141	-
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0.8095	239600	4.6137	-
0.8098	239700	4.6914	-
0.8102	239800	4.6226	-
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0.8216	243200	4.5681	-
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0.8230	243600	4.5444	-
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0.8260	244500	4.6637	-
0.8264	244600	4.6009	-
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0.8297	245600	4.5776	-
0.8301	245700	4.6508	-
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0.8325	246400	4.6271	-
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0.8395	248500	4.6555	-
0.8399	248600	4.6823	-
0.8402	248700	4.5934	-
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0.8412	249000	4.6307	-
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0.8422	249300	4.5516	-
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0.8433	249600	4.5281	-
0.8436	249700	4.5313	-
0.8439	249800	4.5585	-
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0.8460	250400	4.5532	-
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0.8470	250700	4.5463	-
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0.8477	250900	4.6094	-
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0.8531	252500	4.6388	-
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0.8571	253700	4.6189	-
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0.8615	255000	4.5275	-
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0.8635	255600	4.5218	-
0.8639	255700	4.6685	-
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0.8669	256600	4.5074	-
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0.8710	257800	4.6648	-
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0.8730	258400	4.5863	-
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0.8740	258700	4.6171	-
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0.8747	258900	4.5228	-
0.8750	259000	4.7338	-
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0.8760	259300	4.6178	-
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0.8770	259600	4.6	-
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0.9412	278600	4.616	-
0.9416	278700	4.5476	-
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0.9436	279300	4.6334	-
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0.9450	279700	4.5632	-
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0.9460	280000	4.5101	-
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0.9466	280200	4.6163	-
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0.9480	280600	4.5427	-
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0.9578	283500	4.6024	-
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0.9591	283900	4.545	-
0.9595	284000	4.6679	-
0.9598	284100	4.5411	-
0.9602	284200	4.5691	-
0.9605	284300	4.5573	-
0.9608	284400	4.6046	-
0.9612	284500	4.5787	-
0.9615	284600	4.6106	-
0.9618	284700	4.6582	-
0.9622	284800	4.6285	-
0.9625	284900	4.5427	-
0.9629	285000	4.6385	-
0.9632	285100	4.591	-
0.9635	285200	4.5427	-
0.9639	285300	4.7106	-
0.9642	285400	4.5715	-
0.9645	285500	4.6632	-
0.9649	285600	4.4489	-
0.9652	285700	4.6555	-
0.9656	285800	4.5644	-
0.9659	285900	4.6134	-
0.9662	286000	4.6278	-
0.9666	286100	4.4985	-
0.9669	286200	4.5912	-
0.9673	286300	4.6148	-
0.9676	286400	4.6037	-
0.9679	286500	4.5148	-
0.9683	286600	4.5728	-
0.9686	286700	4.6668	-
0.9689	286800	4.548	-
0.9693	286900	4.5618	-
0.9696	287000	4.5706	-
0.9700	287100	4.6879	-
0.9703	287200	4.6268	-
0.9706	287300	4.5686	-
0.9710	287400	4.5579	-
0.9713	287500	4.5167	-
0.9716	287600	4.5872	-
0.9720	287700	4.5615	-
0.9723	287800	4.5124	-
0.9727	287900	4.5364	-
0.9730	288000	4.6275	-
0.9733	288100	4.5796	-
0.9737	288200	4.5837	-
0.9740	288300	4.6221	-
0.9743	288400	4.4785	-
0.9747	288500	4.5931	-
0.9750	288600	4.6196	-
0.9754	288700	4.6085	-
0.9757	288800	4.562	-
0.9760	288900	4.5372	-
0.9764	289000	4.5923	-
0.9767	289100	4.6242	-
0.9771	289200	4.5519	-
0.9774	289300	4.5657	-
0.9777	289400	4.6461	-
0.9781	289500	4.5939	-
0.9784	289600	4.6173	-
0.9787	289700	4.5223	-
0.9791	289800	4.5939	-
0.9794	289900	4.5828	-
0.9798	290000	4.6153	-
0.9801	290100	4.5307	-
0.9804	290200	4.5851	-
0.9808	290300	4.5826	-
0.9811	290400	4.6566	-
0.9814	290500	4.6155	-
0.9818	290600	4.5753	-
0.9821	290700	4.6013	-
0.9825	290800	4.57	-
0.9828	290900	4.5716	-
0.9831	291000	4.5441	-
0.9835	291100	4.6055	-
0.9838	291200	4.5346	-
0.9841	291300	4.6043	-
0.9845	291400	4.6008	-
0.9848	291500	4.5522	-
0.9852	291600	4.5697	-
0.9855	291700	4.5735	-
0.9858	291800	4.4846	-
0.9862	291900	4.5534	-
0.9865	292000	4.5149	-
0.9868	292100	4.6863	-
0.9872	292200	4.5429	-
0.9875	292300	4.5801	-
0.9879	292400	4.6218	-
0.9882	292500	4.5223	-
0.9885	292600	4.8141	-
0.9889	292700	4.5514	-
0.9892	292800	4.6702	-
0.9896	292900	4.5066	-
0.9899	293000	4.562	-
0.9902	293100	4.5669	-
0.9906	293200	4.647	-
0.9909	293300	4.6539	-
0.9912	293400	4.6021	-
0.9916	293500	4.5839	-
0.9919	293600	4.6419	-
0.9923	293700	4.6565	-
0.9926	293800	4.6323	-
0.9929	293900	4.6155	-
0.9933	294000	4.5236	-
0.9936	294100	4.5199	-
0.9939	294200	4.531	-
0.9943	294300	4.7026	-
0.9946	294400	4.5589	-
0.9950	294500	4.6919	-
0.9953	294600	4.5258	-
0.9956	294700	4.6272	-
0.9960	294800	4.4767	-
0.9963	294900	4.5463	-
0.9966	295000	4.6066	-
0.9970	295100	4.5749	-
0.9973	295200	4.6817	-
0.9977	295300	4.5684	-
0.9980	295400	4.577	-
0.9983	295500	4.6233	-
0.9987	295600	4.5088	-
0.9990	295700	4.6556	-
0.9993	295800	4.6205	-
0.9997	295900	4.5743	-

Framework Versions

• Python: 3.12.3
• Sentence Transformers: 5.1.0
• Transformers: 4.55.4
• PyTorch: 2.5.1+cu121
• Accelerate: 1.10.1
• Datasets: 4.0.0
• Tokenizers: 0.21.4

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",
}

CoSENTLoss

@online{kexuefm-8847,
    title={CoSENT: A more efficient sentence vector scheme than Sentence-BERT},
    author={Su Jianlin},
    year={2022},
    month={Jan},
    url={https://kexue.fm/archives/8847},
}