all-MiniLM-L6-v28-pair_score

This is a sentence-transformers model finetuned from KhaledReda/all-MiniLM-L6-v27-pair_score on the pairs_with_scores_v24 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: KhaledReda/all-MiniLM-L6-v27-pair_score
• Maximum Sequence Length: 256 tokens
• Output Dimensionality: 384 dimensions
• Similarity Function: Cosine Similarity
• Training Dataset:
  • pairs_with_scores_v24
• 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 = [
    'face mask',
    'magnesium almonds',
    'table sofa',
]
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, 0.7862, 0.8200],
#         [0.7862, 1.0000, 0.7879],
#         [0.8200, 0.7879, 1.0000]])

Training Details

Training Dataset

pairs_with_scores_v24

• Dataset: pairs_with_scores_v24 at f2ef4cb
• Size: 90,150,263 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: 5.96 tokens max: 36 tokens	min: 3 tokens mean: 6.25 tokens max: 59 tokens	min: 0.0 mean: 0.52 max: 1.0

• Samples:

  sentence1	sentence2	score
  maximo	wooden carved frame mirror	0.2128479033708572
  protein hot chocolate	versatile scooter shell	0.5091056823730468
  groovy classic dog pate liver	frozen spicy chicken strips	0.4272572100162506

• Loss: CoSENTLoss with these parameters:

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

Evaluation Dataset

pairs_with_scores_v24

• Dataset: pairs_with_scores_v24 at f2ef4cb
• Size: 453,017 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: 6.14 tokens max: 40 tokens	min: 3 tokens mean: 6.31 tokens max: 55 tokens	min: 0.0 mean: 0.52 max: 0.93

• Samples:

  sentence1	sentence2	score
  open shirt	milk hot chocolate	0.3352220058441162
  adjust waist joggers	flexible fit pants	0.8284404277801513
  synthetic sneaker	round toe shoes	0.7508501410484314

• 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: 128
• per_device_eval_batch_size: 128
• 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: 128
• per_device_eval_batch_size: 128
• 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
0.0001	100	13.6845	-
0.0003	200	13.5407	-
0.0004	300	13.5713	-
0.0006	400	13.7795	-
0.0007	500	13.737	-
0.0009	600	13.4321	-
0.0010	700	13.6847	-
0.0011	800	13.3631	-
0.0013	900	13.3435	-
0.0014	1000	13.0554	-
0.0016	1100	13.184	-
0.0017	1200	13.0853	-
0.0018	1300	13.0038	-
0.0020	1400	12.7156	-
0.0021	1500	12.5229	-
0.0023	1600	12.4858	-
0.0024	1700	12.3413	-
0.0026	1800	12.1404	-
0.0027	1900	12.0615	-
0.0028	2000	11.8075	-
0.0030	2100	11.7816	-
0.0031	2200	11.5723	-
0.0033	2300	11.2727	-
0.0034	2400	11.1729	-
0.0035	2500	10.9039	-
0.0037	2600	10.7491	-
0.0038	2700	10.668	-
0.0040	2800	10.2775	-
0.0041	2900	10.0851	-
0.0043	3000	10.0136	-
0.0044	3100	9.731	-
0.0045	3200	9.6113	-
0.0047	3300	9.4206	-
0.0048	3400	9.3276	-
0.0050	3500	9.2041	-
0.0051	3600	9.0767	-
0.0053	3700	8.9961	-
0.0054	3800	8.921	-
0.0055	3900	8.8818	-
0.0057	4000	8.843	-
0.0058	4100	8.8115	-
0.0060	4200	8.7784	-
0.0061	4300	8.7597	-
0.0062	4400	8.7487	-
0.0064	4500	8.7447	-
0.0065	4600	8.7324	-
0.0067	4700	8.7221	-
0.0068	4800	8.7057	-
0.0070	4900	8.7029	-
0.0071	5000	8.696	-
0.0072	5100	8.6836	-
0.0074	5200	8.6896	-
0.0075	5300	8.6843	-
0.0077	5400	8.6644	-
0.0078	5500	8.6633	-
0.0080	5600	8.6615	-
0.0081	5700	8.6509	-
0.0082	5800	8.6498	-
0.0084	5900	8.6497	-
0.0085	6000	8.6464	-
0.0087	6100	8.6553	-
0.0088	6200	8.6475	-
0.0089	6300	8.6337	-
0.0091	6400	8.6271	-
0.0092	6500	8.6425	-
0.0094	6600	8.6258	-
0.0095	6700	8.6274	-
0.0097	6800	8.624	-
0.0098	6900	8.6155	-
0.0099	7000	8.6016	-
0.0101	7100	8.6137	-
0.0102	7200	8.6162	-
0.0104	7300	8.5989	-
0.0105	7400	8.6091	-
0.0106	7500	8.5917	-
0.0108	7600	8.5878	-
0.0109	7700	8.6026	-
0.0111	7800	8.6037	-
0.0112	7900	8.5887	-
0.0114	8000	8.5822	-
0.0115	8100	8.5994	-
0.0116	8200	8.5928	-
0.0118	8300	8.5847	-
0.0119	8400	8.5817	-
0.0121	8500	8.5769	-
0.0122	8600	8.5739	-
0.0124	8700	8.5682	-
0.0125	8800	8.5764	-
0.0126	8900	8.5716	-
0.0128	9000	8.5734	-
0.0129	9100	8.5602	-
0.0131	9200	8.5666	-
0.0132	9300	8.5676	-
0.0133	9400	8.5539	-
0.0135	9500	8.5584	-
0.0136	9600	8.5625	-
0.0138	9700	8.5633	-
0.0139	9800	8.5569	-
0.0141	9900	8.5588	-
0.0142	10000	8.5492	-
0.0143	10100	8.5489	-
0.0145	10200	8.5533	-
0.0146	10300	8.5459	-
0.0148	10400	8.541	-
0.0149	10500	8.5465	-
0.0151	10600	8.5439	-
0.0152	10700	8.5361	-
0.0153	10800	8.5345	-
0.0155	10900	8.5415	-
0.0156	11000	8.5272	-
0.0158	11100	8.5396	-
0.0159	11200	8.54	-
0.0160	11300	8.5311	-
0.0162	11400	8.5247	-
0.0163	11500	8.536	-
0.0165	11600	8.5379	-
0.0166	11700	8.5207	-
0.0168	11800	8.5289	-
0.0169	11900	8.529	-
0.0170	12000	8.5312	-
0.0172	12100	8.5319	-
0.0173	12200	8.5045	-
0.0175	12300	8.5086	-
0.0176	12400	8.5204	-
0.0177	12500	8.5147	-
0.0179	12600	8.5055	-
0.0180	12700	8.5206	-
0.0182	12800	8.5115	-
0.0183	12900	8.5149	-
0.0185	13000	8.507	-
0.0186	13100	8.5105	-
0.0187	13200	8.5059	-
0.0189	13300	8.4994	-
0.0190	13400	8.502	-
0.0192	13500	8.5065	-
0.0193	13600	8.5037	-
0.0195	13700	8.5036	-
0.0196	13800	8.5066	-
0.0197	13900	8.5055	-
0.0199	14000	8.5038	-
0.0200	14100	8.5127	-
0.0202	14200	8.4901	-
0.0203	14300	8.5071	-
0.0204	14400	8.4974	-
0.0206	14500	8.5047	-
0.0207	14600	8.4872	-
0.0209	14700	8.5028	-
0.0210	14800	8.496	-
0.0212	14900	8.4758	-
0.0213	15000	8.4964	-
0.0214	15100	8.4856	-
0.0216	15200	8.4804	-
0.0217	15300	8.4864	-
0.0219	15400	8.4868	-
0.0220	15500	8.484	-
0.0221	15600	8.4805	-
0.0223	15700	8.4722	-
0.0224	15800	8.4849	-
0.0226	15900	8.4804	-
0.0227	16000	8.4861	-
0.0229	16100	8.4813	-
0.0230	16200	8.4827	-
0.0231	16300	8.485	-
0.0233	16400	8.4758	-
0.0234	16500	8.4723	-
0.0236	16600	8.4759	-
0.0237	16700	8.4954	-
0.0239	16800	8.4777	-
0.0240	16900	8.4726	-
0.0241	17000	8.4716	-
0.0243	17100	8.4581	-
0.0244	17200	8.4789	-
0.0246	17300	8.4792	-
0.0247	17400	8.4773	-
0.0248	17500	8.4569	-
0.0250	17600	8.4658	-
0.0251	17700	8.4767	-
0.0253	17800	8.4739	-
0.0254	17900	8.456	-
0.0256	18000	8.4576	-
0.0257	18100	8.4525	-
0.0258	18200	8.4718	-
0.0260	18300	8.4605	-
0.0261	18400	8.463	-
0.0263	18500	8.449	-
0.0264	18600	8.4646	-
0.0266	18700	8.4524	-
0.0267	18800	8.4681	-
0.0268	18900	8.4532	-
0.0270	19000	8.4489	-
0.0271	19100	8.4598	-
0.0273	19200	8.4484	-
0.0274	19300	8.4532	-
0.0275	19400	8.456	-
0.0277	19500	8.4328	-
0.0278	19600	8.4372	-
0.0280	19700	8.4648	-
0.0281	19800	8.4469	-
0.0283	19900	8.4484	-
0.0284	20000	8.4357	-
0.0285	20100	8.4593	-
0.0287	20200	8.4558	-
0.0288	20300	8.4451	-
0.0290	20400	8.4427	-
0.0291	20500	8.4301	-
0.0292	20600	8.4484	-
0.0294	20700	8.4469	-
0.0295	20800	8.4366	-
0.0297	20900	8.4375	-
0.0298	21000	8.4341	-
0.0300	21100	8.4279	-
0.0301	21200	8.4468	-
0.0302	21300	8.4241	-
0.0304	21400	8.4334	-
0.0305	21500	8.4317	-
0.0307	21600	8.4242	-
0.0308	21700	8.4398	-
0.0310	21800	8.4314	-
0.0311	21900	8.4329	-
0.0312	22000	8.437	-
0.0314	22100	8.4209	-
0.0315	22200	8.434	-
0.0317	22300	8.427	-
0.0318	22400	8.4127	-
0.0319	22500	8.4398	-
0.0321	22600	8.4255	-
0.0322	22700	8.4081	-
0.0324	22800	8.4239	-
0.0325	22900	8.4246	-
0.0327	23000	8.427	-
0.0328	23100	8.4225	-
0.0329	23200	8.4307	-
0.0331	23300	8.4115	-
0.0332	23400	8.4222	-
0.0334	23500	8.4131	-
0.0335	23600	8.4274	-
0.0337	23700	8.4332	-
0.0338	23800	8.4063	-
0.0339	23900	8.4088	-
0.0341	24000	8.4099	-
0.0342	24100	8.4165	-
0.0344	24200	8.4261	-
0.0345	24300	8.4109	-
0.0346	24400	8.4246	-
0.0348	24500	8.413	-
0.0349	24600	8.4194	-
0.0351	24700	8.4051	-
0.0352	24800	8.3999	-
0.0354	24900	8.4294	-
0.0355	25000	8.4064	-
0.0356	25100	8.4028	-
0.0358	25200	8.4085	-
0.0359	25300	8.406	-
0.0361	25400	8.4227	-
0.0362	25500	8.4279	-
0.0363	25600	8.3973	-
0.0365	25700	8.403	-
0.0366	25800	8.3956	-
0.0368	25900	8.4125	-
0.0369	26000	8.4036	-
0.0371	26100	8.4175	-
0.0372	26200	8.4117	-
0.0373	26300	8.4014	-
0.0375	26400	8.3988	-
0.0376	26500	8.4018	-
0.0378	26600	8.4039	-
0.0379	26700	8.3948	-
0.0381	26800	8.393	-
0.0382	26900	8.3907	-
0.0383	27000	8.4045	-
0.0385	27100	8.4138	-
0.0386	27200	8.4089	-
0.0388	27300	8.4004	-
0.0389	27400	8.3705	-
0.0390	27500	8.3717	-
0.0392	27600	8.3931	-
0.0393	27700	8.3874	-
0.0395	27800	8.3893	-
0.0396	27900	8.3887	-
0.0398	28000	8.4059	-
0.0399	28100	8.3926	-
0.0400	28200	8.3973	-
0.0402	28300	8.4043	-
0.0403	28400	8.3757	-
0.0405	28500	8.3834	-
0.0406	28600	8.3921	-
0.0407	28700	8.3792	-
0.0409	28800	8.3752	-
0.0410	28900	8.3633	-
0.0412	29000	8.4024	-
0.0413	29100	8.3933	-
0.0415	29200	8.3812	-
0.0416	29300	8.3864	-
0.0417	29400	8.3882	-
0.0419	29500	8.3773	-
0.0420	29600	8.3841	-
0.0422	29700	8.3797	-
0.0423	29800	8.3769	-
0.0425	29900	8.3817	-
0.0426	30000	8.3825	-
0.0427	30100	8.3848	-
0.0429	30200	8.3885	-
0.0430	30300	8.3713	-
0.0432	30400	8.3794	-
0.0433	30500	8.3664	-
0.0434	30600	8.3804	-
0.0436	30700	8.3589	-
0.0437	30800	8.3769	-
0.0439	30900	8.3668	-
0.0440	31000	8.3779	-
0.0442	31100	8.3711	-
0.0443	31200	8.3707	-
0.0444	31300	8.3627	-
0.0446	31400	8.3564	-
0.0447	31500	8.3781	-
0.0449	31600	8.3664	-
0.0450	31700	8.3757	-
0.0452	31800	8.3715	-
0.0453	31900	8.3743	-
0.0454	32000	8.3828	-
0.0456	32100	8.3777	-
0.0457	32200	8.3581	-
0.0459	32300	8.3562	-
0.0460	32400	8.3676	-
0.0461	32500	8.366	-
0.0463	32600	8.367	-
0.0464	32700	8.3635	-
0.0466	32800	8.3723	-
0.0467	32900	8.36	-
0.0469	33000	8.3737	-
0.0470	33100	8.3709	-
0.0471	33200	8.3645	-
0.0473	33300	8.366	-
0.0474	33400	8.3689	-
0.0476	33500	8.3558	-
0.0477	33600	8.341	-
0.0478	33700	8.3642	-
0.0480	33800	8.3571	-
0.0481	33900	8.3582	-
0.0483	34000	8.3687	-
0.0484	34100	8.3745	-
0.0486	34200	8.3706	-
0.0487	34300	8.3439	-
0.0488	34400	8.3462	-
0.0490	34500	8.3439	-
0.0491	34600	8.378	-
0.0493	34700	8.3563	-
0.0494	34800	8.3457	-
0.0496	34900	8.3516	-
0.0497	35000	8.3435	-
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0.1224	86200	8.1552	-
0.1225	86300	8.1607	-
0.1227	86400	8.1557	-
0.1228	86500	8.1719	-
0.1230	86600	8.1579	-
0.1231	86700	8.1595	-
0.1232	86800	8.139	-
0.1234	86900	8.1533	-
0.1235	87000	8.1506	-
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0.1238	87200	8.1462	-
0.1240	87300	8.134	-
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0.1242	87500	8.1701	-
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0.1245	87700	8.1593	-
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0.1249	88000	8.1562	-
0.1251	88100	8.1551	-
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0.1255	88400	8.1923	-
0.1257	88500	8.1801	-
0.1258	88600	8.1708	-
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0.1261	88800	8.1942	-
0.1262	88900	8.1618	-
0.1264	89000	8.1594	-
0.1265	89100	8.1784	-
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0.1271	89500	8.1263	-
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0.1275	89800	8.148	-
0.1276	89900	8.1595	-
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0.1281	90200	8.153	-
0.1282	90300	8.1745	-
0.1284	90400	8.1624	-
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0.1292	91000	8.1361	-
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0.1296	91300	8.1674	-
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0.1299	91500	8.1335	-
0.1301	91600	8.1674	-
0.1302	91700	8.1493	-
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0.1305	91900	8.1521	-
0.1306	92000	8.1425	-
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0.1313	92500	8.1357	-
0.1315	92600	8.1573	-
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0.1318	92800	8.158	-
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0.1322	93100	8.158	-
0.1323	93200	8.1336	-
0.1325	93300	8.1728	-
0.1326	93400	8.156	-
0.1328	93500	8.1651	-
0.1329	93600	8.1535	-
0.1330	93700	8.1679	-
0.1332	93800	8.1225	-
0.1333	93900	8.1162	-
0.1335	94000	8.1221	-
0.1336	94100	8.1999	-
0.1338	94200	8.137	-
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0.1340	94400	8.1501	-
0.1342	94500	8.1222	-
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0.1345	94700	8.1263	-
0.1346	94800	8.1516	-
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0.1349	95000	8.1232	-
0.1350	95100	8.1338	-
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0.1356	95500	8.096	-
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0.1360	95800	8.1425	-
0.1362	95900	8.1361	-
0.1363	96000	8.157	-
0.1364	96100	8.1425	-
0.1366	96200	8.1261	-
0.1367	96300	8.1555	-
0.1369	96400	8.1642	-
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0.1372	96600	8.136	-
0.1373	96700	8.1516	-
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0.1376	96900	8.1355	-
0.1377	97000	8.1169	-
0.1379	97100	8.1071	-
0.1380	97200	8.1154	-
0.1382	97300	8.1262	-
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0.1384	97500	8.1632	-
0.1386	97600	8.1466	-
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0.1389	97800	8.1122	-
0.1390	97900	8.1278	-
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0.1393	98100	8.1752	-
0.1394	98200	8.1407	-
0.1396	98300	8.1445	-
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0.1399	98500	8.1566	-
0.1400	98600	8.1109	-
0.1401	98700	8.0988	-
0.1403	98800	8.1634	-
0.1404	98900	8.0862	-
0.1406	99000	8.1061	-
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0.1413	99500	8.1202	-
0.1414	99600	8.1912	-
0.1416	99700	8.1693	-
0.1417	99800	8.1253	-
0.1418	99900	8.1116	-
0.1420	100000	8.1106	-
0.1421	100100	8.1409	-
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0.1430	100700	8.1387	-
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0.1433	100900	8.123	-
0.1434	101000	8.1955	-
0.1435	101100	8.172	-
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0.1444	101700	8.1531	-
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0.1448	102000	8.1089	-
0.1450	102100	8.1311	-
0.1451	102200	8.1459	-
0.1453	102300	8.1468	-
0.1454	102400	8.1285	-
0.1455	102500	8.1383	-
0.1457	102600	8.108	-
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0.1462	103000	8.1567	-
0.1464	103100	8.1013	-
0.1465	103200	8.1389	-
0.1467	103300	8.1135	-
0.1468	103400	8.1617	-
0.1470	103500	8.1514	-
0.1471	103600	8.1134	-
0.1472	103700	8.1118	-
0.1474	103800	8.159	-
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0.1478	104100	8.1053	-
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0.1481	104300	8.1264	-
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0.1485	104600	8.1123	-
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0.1488	104800	8.151	-
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0.1491	105000	8.1778	-
0.1492	105100	8.0977	-
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0.1495	105300	8.1301	-
0.1497	105400	8.1215	-
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0.1501	105700	8.1194	-
0.1502	105800	8.1001	-
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0.1512	106500	8.1013	-
0.1514	106600	8.1389	-
0.1515	106700	8.1056	-
0.1516	106800	8.0871	-
0.1518	106900	8.1574	-
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0.1524	107300	8.1517	-
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0.1526	107500	8.0955	-
0.1528	107600	8.1323	-
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0.1533	108000	8.1307	-
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0.1538	108300	8.1207	-
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0.1541	108500	8.1035	-
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0.1543	108700	8.112	-
0.1545	108800	8.1032	-
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0.1550	109200	8.121	-
0.1552	109300	8.1018	-
0.1553	109400	8.0997	-
0.1555	109500	8.1199	-
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0.1559	109800	8.1105	-
0.1560	109900	8.1098	-
0.1562	110000	8.1332	-
0.1563	110100	8.1302	-
0.1565	110200	8.1277	-
0.1566	110300	8.125	-
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0.1570	110600	8.1415	-
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0.1575	110900	8.1054	-
0.1576	111000	8.1207	-
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0.1579	111200	8.1103	-
0.1580	111300	8.1112	-
0.1582	111400	8.1132	-
0.1583	111500	8.1362	-
0.1585	111600	8.0954	-
0.1586	111700	8.1454	-
0.1587	111800	8.1131	-
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0.1590	112000	8.1326	-
0.1592	112100	8.1232	-
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0.1594	112300	8.1207	-
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0.1599	112600	8.1245	-
0.1600	112700	8.107	-
0.1602	112800	8.0936	-
0.1603	112900	8.095	-
0.1604	113000	8.1245	-
0.1606	113100	8.0988	-
0.1607	113200	8.1008	-
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0.1610	113400	8.0949	-
0.1612	113500	8.0914	-
0.1613	113600	8.1037	-
0.1614	113700	8.1029	-
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0.1617	113900	8.0647	-
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0.1627	114600	8.1007	-
0.1629	114700	8.1135	-
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0.1633	115000	8.128	-
0.1634	115100	8.1222	-
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0.1640	115500	8.0983	-
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0.1644	115800	8.0987	-
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0.1650	116200	8.089	-
0.1651	116300	8.1281	-
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0.1656	116600	8.0716	-
0.1657	116700	8.1304	-
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0.1660	116900	8.1557	-
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0.1664	117200	8.1043	-
0.1665	117300	8.1058	-
0.1667	117400	8.11	-
0.1668	117500	8.1484	-
0.1670	117600	8.1233	-
0.1671	117700	8.1314	-
0.1673	117800	8.0809	-
0.1674	117900	8.0885	-
0.1675	118000	8.13	-
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0.1680	118300	8.086	-
0.1681	118400	8.1082	-
0.1683	118500	8.1311	-
0.1684	118600	8.093	-
0.1685	118700	8.1	-
0.1687	118800	8.0868	-
0.1688	118900	8.1124	-
0.1690	119000	8.1037	-
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0.1694	119300	8.1156	-
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0.1700	119700	8.1093	-
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0.1702	119900	8.133	-
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0.1707	120200	8.0863	-
0.1708	120300	8.0982	-
0.1710	120400	8.1125	-
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0.1712	120600	8.0934	-
0.1714	120700	8.0688	-
0.1715	120800	8.1291	-
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0.1719	121100	8.0587	-
0.1721	121200	8.1078	-
0.1722	121300	8.0764	-
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0.1725	121500	8.0884	-
0.1727	121600	8.101	-
0.1728	121700	8.1214	-
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0.1731	121900	8.1118	-
0.1732	122000	8.0923	-
0.1734	122100	8.1221	-
0.1735	122200	8.0858	-
0.1736	122300	8.1071	-
0.1738	122400	8.0876	-
0.1739	122500	8.0893	-
0.1741	122600	8.0975	-
0.1742	122700	8.0927	-
0.1744	122800	8.098	-
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0.1746	123000	8.0875	-
0.1748	123100	8.0791	-
0.1749	123200	8.0915	-
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0.1752	123400	8.1213	-
0.1754	123500	8.1123	-
0.1755	123600	8.0985	-
0.1756	123700	8.0704	-
0.1758	123800	8.1014	-
0.1759	123900	8.0957	-
0.1761	124000	8.0963	-
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0.1765	124300	8.0968	-
0.1766	124400	8.1223	-
0.1768	124500	8.0915	-
0.1769	124600	8.091	-
0.1771	124700	8.1085	-
0.1772	124800	8.0494	-
0.1773	124900	8.0655	-
0.1775	125000	8.0624	-
0.1776	125100	8.1172	-
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0.1779	125300	8.1004	-
0.1780	125400	8.0987	-
0.1782	125500	8.0694	-
0.1783	125600	8.0907	-
0.1785	125700	8.0603	-
0.1786	125800	8.1399	-
0.1788	125900	8.0994	-
0.1789	126000	8.089	-
0.1790	126100	8.1004	-
0.1792	126200	8.0813	-
0.1793	126300	8.0904	-
0.1795	126400	8.1033	-
0.1796	126500	8.1186	-
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0.1799	126700	8.0628	-
0.1800	126800	8.083	-
0.1802	126900	8.0849	-
0.1803	127000	8.083	-
0.1805	127100	8.0846	-
0.1806	127200	8.1037	-
0.1807	127300	8.0981	-
0.1809	127400	8.0627	-
0.1810	127500	8.1088	-
0.1812	127600	8.1191	-
0.1813	127700	8.0525	-
0.1815	127800	8.0527	-
0.1816	127900	8.0813	-
0.1817	128000	8.0821	-
0.1819	128100	8.0718	-
0.1820	128200	8.0784	-
0.1822	128300	8.1121	-
0.1823	128400	8.0802	-
0.1825	128500	8.1512	-
0.1826	128600	8.0566	-
0.1827	128700	8.0836	-
0.1829	128800	8.0885	-
0.1830	128900	8.0341	-
0.1832	129000	8.1085	-
0.1833	129100	8.0714	-
0.1834	129200	8.0962	-
0.1836	129300	8.0707	-
0.1837	129400	8.0707	-
0.1839	129500	8.103	-
0.1840	129600	8.0585	-
0.1842	129700	8.0999	-
0.1843	129800	8.0856	-
0.1844	129900	8.1258	-
0.1846	130000	8.1224	-
0.1847	130100	8.0922	-
0.1849	130200	8.1071	-
0.1850	130300	8.0535	-
0.1851	130400	8.1024	-
0.1853	130500	8.1137	-
0.1854	130600	8.068	-
0.1856	130700	8.0757	-
0.1857	130800	8.0809	-
0.1859	130900	8.0326	-
0.1860	131000	8.0881	-
0.1861	131100	8.1074	-
0.1863	131200	8.1027	-
0.1864	131300	8.0879	-
0.1866	131400	8.0666	-
0.1867	131500	8.0728	-
0.1869	131600	8.1844	-
0.1870	131700	8.0872	-
0.1871	131800	8.0637	-
0.1873	131900	8.0954	-
0.1874	132000	8.1164	-
0.1876	132100	8.1226	-
0.1877	132200	8.0757	-
0.1878	132300	8.0619	-
0.1880	132400	8.1146	-
0.1881	132500	8.1301	-
0.1883	132600	8.0624	-
0.1884	132700	8.0547	-
0.1886	132800	8.0619	-
0.1887	132900	8.1206	-
0.1888	133000	8.088	-
0.1890	133100	8.0492	-
0.1891	133200	8.0734	-
0.1893	133300	8.0966	-
0.1894	133400	8.0925	-
0.1896	133500	8.0862	-
0.1897	133600	8.1271	-
0.1898	133700	8.0621	-
0.1900	133800	8.119	-
0.1901	133900	8.1024	-
0.1903	134000	8.0925	-
0.1904	134100	8.072	-
0.1905	134200	8.0995	-
0.1907	134300	8.084	-
0.1908	134400	8.0485	-
0.1910	134500	8.1317	-
0.1911	134600	8.0709	-
0.1913	134700	8.0511	-
0.1914	134800	8.0659	-
0.1915	134900	8.0247	-
0.1917	135000	8.1337	-
0.1918	135100	8.095	-
0.1920	135200	8.0348	-
0.1921	135300	8.1255	-
0.1922	135400	8.1016	-
0.1924	135500	8.0885	-
0.1925	135600	8.0912	-
0.1927	135700	8.0522	-
0.1928	135800	8.1182	-
0.1930	135900	8.0679	-
0.1931	136000	8.1553	-
0.1932	136100	8.0836	-
0.1934	136200	8.0635	-
0.1935	136300	8.085	-
0.1937	136400	8.0448	-
0.1938	136500	8.0905	-
0.1940	136600	8.0668	-
0.1941	136700	8.0922	-
0.1942	136800	8.0891	-
0.1944	136900	8.0849	-
0.1945	137000	8.0958	-
0.1947	137100	8.0695	-
0.1948	137200	8.0858	-
0.1949	137300	8.0495	-
0.1951	137400	8.0728	-
0.1952	137500	8.0675	-
0.1954	137600	8.1316	-
0.1955	137700	8.0572	-
0.1957	137800	8.0425	-
0.1958	137900	8.1082	-
0.1959	138000	8.107	-
0.1961	138100	8.0931	-
0.1962	138200	8.1343	-
0.1964	138300	8.0579	-
0.1965	138400	8.0764	-
0.1966	138500	8.0653	-
0.1968	138600	8.0845	-
0.1969	138700	8.0867	-
0.1971	138800	8.0802	-
0.1972	138900	8.102	-
0.1974	139000	8.0611	-
0.1975	139100	8.1037	-
0.1976	139200	8.0493	-
0.1978	139300	8.0574	-
0.1979	139400	8.0525	-
0.1981	139500	8.0455	-
0.1982	139600	8.0678	-
0.1984	139700	8.0922	-
0.1985	139800	8.0803	-
0.1986	139900	8.0671	-
0.1988	140000	8.0584	-
0.1989	140100	8.0344	-
0.1991	140200	8.0647	-
0.1992	140300	8.1002	-
0.1993	140400	8.0654	-
0.1995	140500	8.0906	-
0.1996	140600	8.0755	-
0.1998	140700	8.0564	-
0.1999	140800	8.1508	-
0.2001	140900	8.0426	-
0.2002	141000	8.0527	-
0.2003	141100	8.0864	-
0.2005	141200	8.0815	-
0.2006	141300	8.1045	-
0.2008	141400	8.095	-
0.2009	141500	8.0643	-
0.2011	141600	8.0231	-
0.2012	141700	8.0782	-
0.2013	141800	8.0825	-
0.2015	141900	8.0942	-
0.2016	142000	8.0481	-
0.2018	142100	8.0384	-
0.2019	142200	8.0579	-
0.2020	142300	8.0779	-
0.2022	142400	8.1207	-
0.2023	142500	8.0381	-
0.2025	142600	8.0573	-
0.2026	142700	8.0898	-
0.2028	142800	8.0459	-
0.2029	142900	8.052	-
0.2030	143000	8.0616	-
0.2032	143100	8.0655	-
0.2033	143200	8.0438	-
0.2035	143300	8.0545	-
0.2036	143400	8.0647	-
0.2037	143500	8.0179	-
0.2039	143600	8.0549	-
0.2040	143700	8.0598	-
0.2042	143800	8.0763	-
0.2043	143900	8.0512	-
0.2045	144000	8.1413	-
0.2046	144100	8.0285	-
0.2047	144200	8.0617	-
0.2049	144300	8.0881	-
0.2050	144400	8.0353	-
0.2052	144500	8.1046	-
0.2053	144600	8.096	-
0.2055	144700	8.0701	-
0.2056	144800	8.0961	-
0.2057	144900	8.096	-
0.2059	145000	8.0792	-
0.2060	145100	8.0627	-
0.2062	145200	8.0558	-
0.2063	145300	8.0623	-
0.2064	145400	8.0432	-
0.2066	145500	8.0694	-
0.2067	145600	8.085	-
0.2069	145700	8.074	-
0.2070	145800	8.0375	-
0.2072	145900	8.0715	-
0.2073	146000	8.0441	-
0.2074	146100	8.122	-
0.2076	146200	8.0691	-
0.2077	146300	8.0665	-
0.2079	146400	8.0461	-
0.2080	146500	8.0375	-
0.2082	146600	8.0312	-
0.2083	146700	8.0959	-
0.2084	146800	8.0597	-
0.2086	146900	8.067	-
0.2087	147000	8.0444	-
0.2089	147100	8.0713	-
0.2090	147200	8.055	-
0.2091	147300	8.0301	-
0.2093	147400	8.0832	-
0.2094	147500	8.0174	-
0.2096	147600	8.0531	-
0.2097	147700	8.0789	-
0.2099	147800	8.0647	-
0.2100	147900	8.0789	-
0.2101	148000	8.0608	-
0.2103	148100	8.143	-
0.2104	148200	8.1068	-
0.2106	148300	8.0643	-
0.2107	148400	8.1077	-
0.2108	148500	8.0712	-
0.2110	148600	8.0618	-
0.2111	148700	8.0558	-
0.2113	148800	8.0337	-
0.2114	148900	8.0719	-
0.2116	149000	8.0565	-
0.2117	149100	8.0225	-
0.2118	149200	8.0345	-
0.2120	149300	8.0891	-
0.2121	149400	8.0739	-
0.2123	149500	8.052	-
0.2124	149600	8.0708	-
0.2126	149700	8.0402	-
0.2127	149800	8.0735	-
0.2128	149900	8.0732	-
0.2130	150000	8.0752	-
0.2131	150100	8.0579	-
0.2133	150200	8.0506	-
0.2134	150300	8.0434	-
0.2135	150400	8.1115	-
0.2137	150500	8.0135	-
0.2138	150600	8.0642	-
0.2140	150700	8.0578	-
0.2141	150800	8.0392	-
0.2143	150900	8.0722	-
0.2144	151000	8.0409	-
0.2145	151100	8.0611	-
0.2147	151200	8.0501	-
0.2148	151300	8.0786	-
0.2150	151400	8.1079	-
0.2151	151500	8.1075	-
0.2152	151600	8.0524	-
0.2154	151700	8.0714	-
0.2155	151800	8.0863	-
0.2157	151900	8.0884	-
0.2158	152000	8.0692	-
0.2160	152100	8.0304	-
0.2161	152200	8.0875	-
0.2162	152300	8.0761	-
0.2164	152400	8.0851	-
0.2165	152500	8.0298	-
0.2167	152600	8.0821	-
0.2168	152700	8.1055	-
0.2170	152800	8.0383	-
0.2171	152900	8.0556	-
0.2172	153000	8.0247	-
0.2174	153100	8.0754	-
0.2175	153200	8.0936	-
0.2177	153300	8.0881	-
0.2178	153400	8.0654	-
0.2179	153500	8.0364	-
0.2181	153600	8.059	-
0.2182	153700	8.0123	-
0.2184	153800	8.02	-
0.2185	153900	8.0977	-
0.2187	154000	8.0155	-
0.2188	154100	8.0544	-
0.2189	154200	8.0746	-
0.2191	154300	8.0752	-
0.2192	154400	8.0554	-
0.2194	154500	8.032	-
0.2195	154600	8.1062	-
0.2197	154700	8.055	-
0.2198	154800	8.0307	-
0.2199	154900	8.0628	-
0.2201	155000	8.0391	-
0.2202	155100	8.0452	-
0.2204	155200	8.0565	-
0.2205	155300	8.0235	-
0.2206	155400	8.0643	-
0.2208	155500	8.13	-
0.2209	155600	8.0228	-
0.2211	155700	7.9928	-
0.2212	155800	8.04	-
0.2214	155900	8.0463	-
0.2215	156000	8.0806	-
0.2216	156100	8.0391	-
0.2218	156200	8.0361	-
0.2219	156300	8.0423	-
0.2221	156400	8.0571	-
0.2222	156500	8.0326	-
0.2223	156600	8.0582	-
0.2225	156700	8.0644	-
0.2226	156800	8.0147	-
0.2228	156900	8.0431	-
0.2229	157000	8.0549	-
0.2231	157100	8.1073	-
0.2232	157200	8.0889	-
0.2233	157300	8.0138	-
0.2235	157400	8.0548	-
0.2236	157500	8.0887	-
0.2238	157600	8.0593	-
0.2239	157700	8.086	-
0.2241	157800	8.0856	-
0.2242	157900	8.0573	-
0.2243	158000	8.0462	-
0.2245	158100	8.0548	-
0.2246	158200	8.0197	-
0.2248	158300	8.0525	-
0.2249	158400	8.0228	-
0.2250	158500	8.0698	-
0.2252	158600	8.0501	-
0.2253	158700	8.0638	-
0.2255	158800	8.0328	-
0.2256	158900	8.0449	-
0.2258	159000	8.0369	-
0.2259	159100	8.0576	-
0.2260	159200	8.1297	-
0.2262	159300	8.1047	-
0.2263	159400	8.055	-
0.2265	159500	8.0355	-
0.2266	159600	8.061	-
0.2268	159700	8.072	-
0.2269	159800	8.0461	-
0.2270	159900	8.0634	-
0.2272	160000	8.0813	-
0.2273	160100	8.0719	-
0.2275	160200	8.0639	-
0.2276	160300	8.0603	-
0.2277	160400	8.0666	-
0.2279	160500	8.0623	-
0.2280	160600	8.0237	-
0.2282	160700	8.0159	-
0.2283	160800	8.0667	-
0.2285	160900	8.1107	-
0.2286	161000	8.014	-
0.2287	161100	8.0384	-
0.2289	161200	8.0647	-
0.2290	161300	8.0655	-
0.2292	161400	8.1057	-
0.2293	161500	8.0732	-
0.2294	161600	8.0328	-
0.2296	161700	8.0444	-
0.2297	161800	8.0494	-
0.2299	161900	8.049	-
0.2300	162000	8.0465	-
0.2302	162100	8.026	-
0.2303	162200	8.0517	-
0.2304	162300	8.0122	-
0.2306	162400	8.0389	-
0.2307	162500	8.0952	-
0.2309	162600	8.0452	-
0.2310	162700	8.0535	-
0.2312	162800	8.0782	-
0.2313	162900	8.0281	-
0.2314	163000	8.0598	-
0.2316	163100	8.027	-
0.2317	163200	8.0453	-
0.2319	163300	8.0424	-
0.2320	163400	8.0923	-
0.2321	163500	8.0511	-
0.2323	163600	8.0453	-
0.2324	163700	8.045	-
0.2326	163800	8.0848	-
0.2327	163900	8.0649	-
0.2329	164000	8.0348	-
0.2330	164100	8.0545	-
0.2331	164200	8.0192	-
0.2333	164300	8.0674	-
0.2334	164400	8.0619	-
0.2336	164500	8.0334	-
0.2337	164600	8.092	-
0.2338	164700	8.0928	-
0.2340	164800	8.1137	-
0.2341	164900	8.0435	-
0.2343	165000	8.0541	-
0.2344	165100	7.9976	-
0.2346	165200	8.0346	-
0.2347	165300	8.0468	-
0.2348	165400	8.0238	-
0.2350	165500	8.0652	-
0.2351	165600	8.0862	-
0.2353	165700	8.0556	-
0.2354	165800	8.0941	-
0.2356	165900	8.0091	-
0.2357	166000	8.0798	-
0.2358	166100	8.0792	-
0.2360	166200	8.025	-
0.2361	166300	8.0799	-
0.2363	166400	8.0263	-
0.2364	166500	8.1019	-
0.2365	166600	8.0339	-
0.2367	166700	8.0945	-
0.2368	166800	8.0296	-
0.2370	166900	8.0571	-
0.2371	167000	8.1255	-
0.2373	167100	8.0534	-
0.2374	167200	8.0191	-
0.2375	167300	8.0982	-
0.2377	167400	8.0385	-
0.2378	167500	8.0677	-
0.2380	167600	8.0676	-
0.2381	167700	8.105	-
0.2383	167800	8.05	-
0.2384	167900	8.0113	-
0.2385	168000	8.0419	-
0.2387	168100	8.0243	-
0.2388	168200	8.0913	-
0.2390	168300	8.0987	-
0.2391	168400	8.0798	-
0.2392	168500	8.0766	-
0.2394	168600	8.0545	-
0.2395	168700	8.0585	-
0.2397	168800	8.0196	-
0.2398	168900	8.0696	-
0.2400	169000	8.0207	-
0.2401	169100	8.0481	-
0.2402	169200	8.0758	-
0.2404	169300	8.104	-
0.2405	169400	8.0216	-
0.2407	169500	8.0401	-
0.2408	169600	8.0781	-
0.2409	169700	8.0272	-
0.2411	169800	8.0313	-
0.2412	169900	8.0622	-
0.2414	170000	8.0088	-
0.2415	170100	8.0802	-
0.2417	170200	7.9864	-
0.2418	170300	8.0671	-
0.2419	170400	8.0904	-
0.2421	170500	8.0456	-
0.2422	170600	8.0217	-
0.2424	170700	8.029	-
0.2425	170800	8.0329	-
0.2427	170900	8.0507	-
0.2428	171000	8.0188	-
0.2429	171100	8.087	-
0.2431	171200	8.0848	-
0.2432	171300	8.0583	-
0.2434	171400	8.0634	-
0.2435	171500	8.0851	-
0.2436	171600	7.9877	-
0.2438	171700	8.0603	-
0.2439	171800	8.0156	-
0.2441	171900	8.0623	-
0.2442	172000	8.0313	-
0.2444	172100	8.033	-
0.2445	172200	8.0188	-
0.2446	172300	8.0613	-
0.2448	172400	8.0134	-
0.2449	172500	8.0422	-
0.2451	172600	8.0372	-
0.2452	172700	8.0413	-
0.2454	172800	8.0488	-
0.2455	172900	8.0478	-
0.2456	173000	8.0447	-
0.2458	173100	8.0566	-
0.2459	173200	8.0755	-
0.2461	173300	8.0111	-
0.2462	173400	8.0734	-
0.2463	173500	8.0348	-
0.2465	173600	8.0389	-
0.2466	173700	8.0415	-
0.2468	173800	8.0523	-
0.2469	173900	8.0511	-
0.2471	174000	8.0368	-
0.2472	174100	8.0526	-
0.2473	174200	8.0157	-
0.2475	174300	8.0438	-
0.2476	174400	8.0633	-
0.2478	174500	8.025	-
0.2479	174600	8.0912	-
0.2480	174700	8.0512	-
0.2482	174800	8.0447	-
0.2483	174900	8.0703	-
0.2485	175000	8.0497	-
0.2486	175100	8.0206	-
0.2488	175200	8.0993	-
0.2489	175300	8.0639	-
0.2490	175400	8.0078	-
0.2492	175500	8.0887	-
0.2493	175600	8.0337	-
0.2495	175700	8.0077	-
0.2496	175800	8.0306	-
0.2498	175900	8.0651	-
0.2499	176000	7.9862	-
0.2500	176100	8.0566	-
0.2502	176200	8.0744	-
0.2503	176300	8.0635	-
0.2505	176400	8.0209	-
0.2506	176500	8.0031	-
0.2507	176600	8.0822	-
0.2509	176700	8.0072	-
0.2510	176800	8.019	-
0.2512	176900	8.0267	-
0.2513	177000	8.0293	-
0.2515	177100	8.0595	-
0.2516	177200	8.054	-
0.2517	177300	8.0659	-
0.2519	177400	8.0733	-
0.2520	177500	8.0525	-
0.2522	177600	8.0008	-
0.2523	177700	8.0589	-
0.2524	177800	8.0789	-
0.2526	177900	8.0564	-
0.2527	178000	8.0469	-
0.2529	178100	8.0533	-
0.2530	178200	8.05	-
0.2532	178300	8.0236	-
0.2533	178400	8.009	-
0.2534	178500	8.053	-
0.2536	178600	8.0846	-
0.2537	178700	7.9981	-
0.2539	178800	8.0475	-
0.2540	178900	8.0209	-
0.2542	179000	8.0002	-
0.2543	179100	8.0565	-
0.2544	179200	8.0131	-
0.2546	179300	8.0406	-
0.2547	179400	8.0041	-
0.2549	179500	7.9935	-
0.2550	179600	8.073	-
0.2551	179700	8.0482	-
0.2553	179800	8.0324	-
0.2554	179900	8.1098	-
0.2556	180000	8.0046	-
0.2557	180100	8.0528	-
0.2559	180200	8.0346	-
0.2560	180300	8.0122	-
0.2561	180400	8.0136	-
0.2563	180500	8.0094	-
0.2564	180600	7.9992	-
0.2566	180700	8.043	-
0.2567	180800	8.0029	-
0.2569	180900	8.0175	-
0.2570	181000	8.0273	-
0.2571	181100	8.0132	-
0.2573	181200	8.0187	-
0.2574	181300	8.0006	-
0.2576	181400	8.0447	-
0.2577	181500	8.0483	-
0.2578	181600	8.0158	-
0.2580	181700	8.0587	-
0.2581	181800	8.0218	-
0.2583	181900	8.0707	-
0.2584	182000	8.0379	-
0.2586	182100	7.997	-
0.2587	182200	8.0686	-
0.2588	182300	8.0124	-
0.2590	182400	8.0073	-
0.2591	182500	8.0182	-
0.2593	182600	8.0114	-
0.2594	182700	8.0888	-
0.2595	182800	7.9891	-
0.2597	182900	8.0197	-
0.2598	183000	8.0131	-
0.2600	183100	8.0255	-
0.2601	183200	8.0953	-
0.2603	183300	8.0539	-
0.2604	183400	8.0393	-
0.2605	183500	8.0615	-
0.2607	183600	8.0438	-
0.2608	183700	8.0375	-
0.2610	183800	8.0019	-
0.2611	183900	8.1	-
0.2613	184000	8.0044	-
0.2614	184100	8.021	-
0.2615	184200	8.002	-
0.2617	184300	7.999	-
0.2618	184400	8.0149	-
0.2620	184500	8.0633	-
0.2621	184600	8.0272	-
0.2622	184700	8.0458	-
0.2624	184800	8.0877	-
0.2625	184900	8.0671	-
0.2627	185000	8.0163	-
0.2628	185100	8.0477	-
0.2630	185200	8.0401	-
0.2631	185300	8.0227	-
0.2632	185400	8.1003	-
0.2634	185500	8.0817	-
0.2635	185600	8.1079	-
0.2637	185700	8.0311	-
0.2638	185800	8.0236	-
0.2640	185900	8.0375	-
0.2641	186000	8.0257	-
0.2642	186100	8.0098	-
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0.2645	186300	8.0335	-
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0.2648	186500	8.026	-
0.2649	186600	8.0428	-
0.2651	186700	7.9809	-
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0.2655	187000	8.0618	-
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0.2662	187500	7.9978	-
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0.2665	187700	8.0525	-
0.2666	187800	8.0101	-
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0.2669	188000	7.9922	-
0.2671	188100	8.0448	-
0.2672	188200	8.0489	-
0.2674	188300	8.0237	-
0.2675	188400	8.0976	-
0.2676	188500	8.0428	-
0.2678	188600	8.0488	-
0.2679	188700	8.0013	-
0.2681	188800	8.0194	-
0.2682	188900	7.9965	-
0.2684	189000	8.0937	-
0.2685	189100	8.0568	-
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0.2688	189300	8.0688	-
0.2689	189400	8.0257	-
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0.2692	189600	8.0235	-
0.2693	189700	8.0435	-
0.2695	189800	8.0061	-
0.2696	189900	8.0476	-
0.2698	190000	8.0318	-
0.2699	190100	8.0232	-
0.2701	190200	8.0784	-
0.2702	190300	7.9824	-
0.2703	190400	8.0691	-
0.2705	190500	8.0283	-
0.2706	190600	8.0648	-
0.2708	190700	8.0133	-
0.2709	190800	8.0046	-
0.2710	190900	8.0041	-
0.2712	191000	7.993	-
0.2713	191100	8.0091	-
0.2715	191200	8.0165	-
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0.2718	191400	8.0332	-
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0.2720	191600	8.0066	-
0.2722	191700	8.0759	-
0.2723	191800	7.9962	-
0.2725	191900	8.0104	-
0.2726	192000	8.0706	-
0.2728	192100	8.0833	-
0.2729	192200	8.0912	-
0.2730	192300	7.9966	-
0.2732	192400	8.0682	-
0.2733	192500	8.0626	-
0.2735	192600	8.0795	-
0.2736	192700	8.0733	-
0.2737	192800	8.0141	-
0.2739	192900	8.0516	-
0.2740	193000	7.9981	-
0.2742	193100	8.0823	-
0.2743	193200	8.0676	-
0.2745	193300	8.0152	-
0.2746	193400	8.0254	-
0.2747	193500	7.9897	-
0.2749	193600	8.007	-
0.2750	193700	8.0268	-
0.2752	193800	8.0344	-
0.2753	193900	8.03	-
0.2755	194000	8.0315	-
0.2756	194100	8.0269	-
0.2757	194200	8.0178	-
0.2759	194300	7.9916	-
0.2760	194400	8.0798	-
0.2762	194500	8.0037	-
0.2763	194600	8.0169	-
0.2764	194700	8.0116	-
0.2766	194800	8.0558	-
0.2767	194900	8.0664	-
0.2769	195000	8.0453	-
0.2770	195100	8.0716	-
0.2772	195200	7.9889	-
0.2773	195300	7.9995	-
0.2774	195400	8.0339	-
0.2776	195500	8.1067	-
0.2777	195600	8.0416	-
0.2779	195700	8.0261	-
0.2780	195800	8.0074	-
0.2781	195900	8.0326	-
0.2783	196000	8.0393	-
0.2784	196100	7.9918	-
0.2786	196200	8.0292	-
0.2787	196300	8.0677	-
0.2789	196400	8.1034	-
0.2790	196500	7.9842	-
0.2791	196600	8.0352	-
0.2793	196700	7.9884	-
0.2794	196800	8.045	-
0.2796	196900	8.0058	-
0.2797	197000	8.0672	-
0.2799	197100	8.0584	-
0.2800	197200	8.015	-
0.2801	197300	8.0632	-
0.2803	197400	8.0755	-
0.2804	197500	7.9964	-
0.2806	197600	8.0245	-
0.2807	197700	8.0259	-
0.2808	197800	8.0575	-
0.2810	197900	7.9958	-
0.2811	198000	7.9823	-
0.2813	198100	8.0424	-
0.2814	198200	8.0236	-
0.2816	198300	8.0505	-
0.2817	198400	7.9704	-
0.2818	198500	8.0025	-
0.2820	198600	7.9876	-
0.2821	198700	8.0283	-
0.2823	198800	8.0513	-
0.2824	198900	7.9896	-
0.2826	199000	8.0105	-
0.2827	199100	7.9861	-
0.2828	199200	8.0328	-
0.2830	199300	7.9818	-
0.2831	199400	7.9779	-
0.2833	199500	8.0531	-
0.2834	199600	8.0175	-
0.2835	199700	7.9877	-
0.2837	199800	8.0789	-
0.2838	199900	7.9864	-
0.2840	200000	8.0299	7.9722
0.2841	200100	8.0525	-
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0.2844	200300	8.0142	-
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0.2848	200600	8.07	-
0.2850	200700	8.0302	-
0.2851	200800	8.0862	-
0.2852	200900	7.9958	-
0.2854	201000	8.0119	-
0.2855	201100	7.9625	-
0.2857	201200	8.0548	-
0.2858	201300	8.0182	-
0.2860	201400	8.0464	-
0.2861	201500	7.9915	-
0.2862	201600	8.0301	-
0.2864	201700	7.9472	-
0.2865	201800	7.9913	-
0.2867	201900	8.036	-
0.2868	202000	7.9985	-
0.2870	202100	8.0047	-
0.2871	202200	8.0503	-
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0.2877	202600	8.0151	-
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0.2911	205000	8.0039	-
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0.2918	205500	7.9896	-
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0.2921	205700	8.0325	-
0.2922	205800	8.0386	-
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0.2925	206000	8.0878	-
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0.3122	219900	7.9863	-
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0.3202	225500	7.9996	-
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0.3209	226000	7.9871	-
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0.3250	228900	7.9993	-
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0.3260	229600	8.0366	-
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0.3266	230000	7.9986	-
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0.3270	230300	7.9872	-
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0.3280	231000	8.0061	-
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0.3294	232000	7.9558	-
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0.3297	232200	7.9896	-
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0.3300	232400	8.0275	-
0.3301	232500	8.0063	-
0.3303	232600	8.0316	-
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0.3308	233000	7.976	-
0.3310	233100	8.0352	-
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0.3313	233300	8.0005	-
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0.3315	233500	8.0273	-
0.3317	233600	7.968	-
0.3318	233700	8.0147	-
0.3320	233800	7.9609	-
0.3321	233900	8.0484	-
0.3322	234000	8.0005	-
0.3324	234100	8.0238	-
0.3325	234200	7.975	-
0.3327	234300	7.9798	-
0.3328	234400	8.0275	-
0.3330	234500	8.0158	-
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0.3342	235400	7.9786	-
0.3344	235500	7.9964	-
0.3345	235600	7.9589	-
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0.9706	683600	7.8748	-
0.9708	683700	7.9086	-
0.9709	683800	7.8787	-
0.9710	683900	7.896	-
0.9712	684000	7.8664	-
0.9713	684100	7.911	-
0.9715	684200	7.8215	-
0.9716	684300	7.9038	-
0.9717	684400	7.9475	-
0.9719	684500	7.8752	-
0.9720	684600	7.8689	-
0.9722	684700	7.8695	-
0.9723	684800	7.9456	-
0.9725	684900	7.9407	-
0.9726	685000	7.8291	-
0.9727	685100	7.8894	-
0.9729	685200	7.9631	-
0.9730	685300	7.9999	-
0.9732	685400	7.9299	-
0.9733	685500	7.8407	-
0.9735	685600	7.8875	-
0.9736	685700	7.9272	-
0.9737	685800	7.9329	-
0.9739	685900	7.8439	-
0.9740	686000	7.8901	-
0.9742	686100	7.9128	-
0.9743	686200	7.8689	-
0.9744	686300	7.895	-
0.9746	686400	7.8831	-
0.9747	686500	7.941	-
0.9749	686600	7.8689	-
0.9750	686700	7.9185	-
0.9752	686800	7.8587	-
0.9753	686900	7.9116	-
0.9754	687000	7.8609	-
0.9756	687100	7.8399	-
0.9757	687200	7.8702	-
0.9759	687300	7.834	-
0.9760	687400	7.9039	-
0.9761	687500	7.8847	-
0.9763	687600	7.9359	-
0.9764	687700	7.8645	-
0.9766	687800	7.8433	-
0.9767	687900	8.006	-
0.9769	688000	7.9496	-
0.9770	688100	7.8865	-
0.9771	688200	7.9411	-
0.9773	688300	7.8955	-
0.9774	688400	7.9026	-
0.9776	688500	7.9147	-
0.9777	688600	7.9612	-
0.9779	688700	7.8736	-
0.9780	688800	7.9144	-
0.9781	688900	7.933	-
0.9783	689000	7.9546	-
0.9784	689100	7.935	-
0.9786	689200	7.8816	-
0.9787	689300	7.9214	-
0.9788	689400	7.897	-
0.9790	689500	7.9072	-
0.9791	689600	7.9639	-
0.9793	689700	7.9287	-
0.9794	689800	7.9857	-
0.9796	689900	7.8385	-
0.9797	690000	7.8645	-
0.9798	690100	7.9819	-
0.9800	690200	7.8745	-
0.9801	690300	7.9319	-
0.9803	690400	7.8613	-
0.9804	690500	7.8884	-
0.9805	690600	7.8513	-
0.9807	690700	7.9666	-
0.9808	690800	7.8481	-
0.9810	690900	7.8751	-
0.9811	691000	7.8674	-
0.9813	691100	7.9029	-
0.9814	691200	7.8472	-
0.9815	691300	7.8511	-
0.9817	691400	7.8758	-
0.9818	691500	7.8554	-
0.9820	691600	7.9353	-
0.9821	691700	7.9124	-
0.9823	691800	7.9131	-
0.9824	691900	7.8698	-
0.9825	692000	7.9338	-
0.9827	692100	7.8691	-
0.9828	692200	7.9496	-
0.9830	692300	7.8652	-
0.9831	692400	7.8754	-
0.9832	692500	7.946	-
0.9834	692600	7.8718	-
0.9835	692700	7.9727	-
0.9837	692800	7.9316	-
0.9838	692900	7.981	-
0.9840	693000	7.8865	-
0.9841	693100	7.8596	-
0.9842	693200	7.8761	-
0.9844	693300	7.9413	-
0.9845	693400	7.8203	-
0.9847	693500	7.9137	-
0.9848	693600	7.9	-
0.9850	693700	7.9467	-
0.9851	693800	7.9704	-
0.9852	693900	7.8707	-
0.9854	694000	8.076	-
0.9855	694100	7.9276	-
0.9857	694200	7.8303	-
0.9858	694300	7.8584	-
0.9859	694400	7.8817	-
0.9861	694500	7.8709	-
0.9862	694600	7.8532	-
0.9864	694700	7.9172	-
0.9865	694800	7.8872	-
0.9867	694900	7.8688	-
0.9868	695000	7.94	-
0.9869	695100	7.8576	-
0.9871	695200	7.9237	-
0.9872	695300	7.918	-
0.9874	695400	7.8357	-
0.9875	695500	7.8614	-
0.9876	695600	7.8971	-
0.9878	695700	7.8969	-
0.9879	695800	7.91	-
0.9881	695900	7.9007	-
0.9882	696000	7.9333	-
0.9884	696100	7.8685	-
0.9885	696200	7.9076	-
0.9886	696300	7.8615	-
0.9888	696400	7.992	-
0.9889	696500	7.8641	-
0.9891	696600	7.9311	-
0.9892	696700	7.8543	-
0.9894	696800	7.884	-
0.9895	696900	7.9857	-
0.9896	697000	7.9036	-
0.9898	697100	7.9455	-
0.9899	697200	7.9253	-
0.9901	697300	7.9183	-
0.9902	697400	7.9221	-
0.9903	697500	7.9051	-
0.9905	697600	7.9178	-
0.9906	697700	7.8727	-
0.9908	697800	7.9285	-
0.9909	697900	8.008	-
0.9911	698000	7.9278	-
0.9912	698100	7.8455	-
0.9913	698200	7.9608	-
0.9915	698300	7.9326	-
0.9916	698400	7.9873	-
0.9918	698500	7.9229	-
0.9919	698600	7.8849	-
0.9921	698700	7.8621	-
0.9922	698800	7.8475	-
0.9923	698900	7.8359	-
0.9925	699000	7.8733	-
0.9926	699100	7.9273	-
0.9928	699200	7.8984	-
0.9929	699300	7.9499	-
0.9930	699400	7.8965	-
0.9932	699500	7.9294	-
0.9933	699600	7.8987	-
0.9935	699700	7.8353	-
0.9936	699800	7.9987	-
0.9938	699900	7.9538	-
0.9939	700000	7.9303	-
0.9940	700100	7.8976	-
0.9942	700200	7.9045	-
0.9943	700300	7.8877	-
0.9945	700400	7.8747	-
0.9946	700500	7.9726	-
0.9947	700600	7.92	-
0.9949	700700	7.8698	-
0.9950	700800	7.8678	-
0.9952	700900	7.918	-
0.9953	701000	7.9353	-
0.9955	701100	7.9002	-
0.9956	701200	7.9207	-
0.9957	701300	7.8689	-
0.9959	701400	7.9418	-
0.9960	701500	7.998	-
0.9962	701600	7.934	-
0.9963	701700	7.9285	-
0.9965	701800	7.8974	-
0.9966	701900	7.9537	-
0.9967	702000	7.8998	-
0.9969	702100	7.9277	-
0.9970	702200	7.9298	-
0.9972	702300	8.0086	-
0.9973	702400	7.926	-
0.9974	702500	7.9779	-
0.9976	702600	7.9171	-
0.9977	702700	7.87	-
0.9979	702800	7.9104	-
0.9980	702900	7.86	-
0.9982	703000	7.835	-
0.9983	703100	7.9287	-
0.9984	703200	7.8573	-
0.9986	703300	7.8572	-
0.9987	703400	7.9506	-
0.9989	703500	7.8956	-
0.9990	703600	7.8593	-
0.9991	703700	7.9712	-
0.9993	703800	7.8689	-
0.9994	703900	7.9835	-
0.9996	704000	7.8992	-
0.9997	704100	7.8822	-
0.9999	704200	7.959	-

Framework Versions

• Python: 3.12.3
• Sentence Transformers: 5.1.0
• Transformers: 4.55.4
• PyTorch: 2.6.0+cu124
• 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},
}