Redis fine-tuned CrossEncoder model for semantic caching on LangCache

This is a Cross Encoder model finetuned from ibm-granite/granite-embedding-reranker-english-r2 on the LangCache Sentence Pairs (subsets=['all'], train+val=True) dataset using the sentence-transformers library. It computes scores for pairs of texts, which can be used for sentence pair classification.

Model Details

Model Description

Model Type: Cross Encoder
Base model: ibm-granite/granite-embedding-reranker-english-r2
Maximum Sequence Length: 8192 tokens
Number of Output Labels: 1 label
Training Dataset:
- LangCache Sentence Pairs (subsets=['all'], train+val=True)
Language: en
License: apache-2.0

Model Sources

Documentation: Sentence Transformers Documentation
Documentation: Cross Encoder Documentation
Repository: Sentence Transformers on GitHub
Hugging Face: Cross Encoders on Hugging Face

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 CrossEncoder

# Download from the 🤗 Hub
model = CrossEncoder("redis/langcache-reranker-v2-granite-bce-eps0.5")
# Get scores for pairs of texts
pairs = [
    ['The newer Punts are still very much in existence today and race in the same fleets as the older boats .', 'The newer punts are still very much in existence today and run in the same fleets as the older boats .'],
    ['Turner Valley , was at the Turner Valley Bar N Ranch Airport , southwest of the Turner Valley Bar N Ranch , Alberta , Canada .', 'Turner Valley Bar N Ranch Airport , , was located at Turner Valley Bar N Ranch , southwest of Turner Valley , Alberta , Canada .'],
    ['After losing his second election , he resigned as opposition leader and was replaced by Geoff Pearsall .', 'Max Bingham resigned as opposition leader after losing his second election , and was replaced by Geoff Pearsall .'],
    ['She married Peter Haygarth on 29 May 1964 in Durban . Her second marriage , to Robin Osborne , took place in 1977 .', 'She married Robin Osborne on May 29 , 1964 in Durban , and her second marriage with Peter Haygarth took place in 1977 .'],
    ['In 2005 she moved to Norway , settled in Geilo and worked as a rafting guide , in 2006 she started mountain biking - races .', 'In 2005 , she moved to Geilo , settling in Norway and worked as a rafting guide . She started mountain bike races in 2006 .'],
]
scores = model.predict(pairs)
print(scores.shape)
# (5,)

# Or rank different texts based on similarity to a single text
ranks = model.rank(
    'The newer Punts are still very much in existence today and race in the same fleets as the older boats .',
    [
        'The newer punts are still very much in existence today and run in the same fleets as the older boats .',
        'Turner Valley Bar N Ranch Airport , , was located at Turner Valley Bar N Ranch , southwest of Turner Valley , Alberta , Canada .',
        'Max Bingham resigned as opposition leader after losing his second election , and was replaced by Geoff Pearsall .',
        'She married Robin Osborne on May 29 , 1964 in Durban , and her second marriage with Peter Haygarth took place in 1977 .',
        'In 2005 , she moved to Geilo , settling in Norway and worked as a rafting guide . She started mountain bike races in 2006 .',
    ]
)
# [{'corpus_id': ..., 'score': ...}, {'corpus_id': ..., 'score': ...}, ...]

Evaluation

Metrics

Cross Encoder Classification

Dataset: test_cls
Evaluated with CrossEncoderClassificationEvaluator

Metric	Value
accuracy	0.7486
accuracy_threshold	0.0952
f1	0.754
f1_threshold	0.0781
precision	0.649
recall	0.8996
average_precision	0.7395

Cross Encoder Reranking

Datasets: NanoQuoraRetrieval_R25, NanoMSMARCO_R25 and NanoNQ_R25

Evaluated with CrossEncoderRerankingEvaluator with these parameters:

{
    "at_k": 1,
    "always_rerank_positives": true
}

Metric	NanoQuoraRetrieval_R25	NanoMSMARCO_R25	NanoNQ_R25
map	0.6478 (-0.1827)	0.3689 (-0.1189)	0.5243 (+0.1043)
mrr@1	0.5000 (-0.3000)	0.2000 (-0.1400)	0.4000 (+0.1600)
ndcg@1	0.5100 (-0.2900)	0.2000 (-0.1400)	0.4000 (+0.1600)

Cross Encoder Nano BEIR

Dataset: NanoBEIR_R25_mean

Evaluated with CrossEncoderNanoBEIREvaluator with these parameters:

{
    "dataset_names": [
        "QuoraRetrieval",
        "MSMARCO",
        "NQ"
    ],
    "rerank_k": 25,
    "at_k": 1,
    "always_rerank_positives": true
}

Metric	Value
map	0.5136 (-0.0658)
mrr@1	0.3667 (-0.0933)
ndcg@1	0.3700 (-0.0900)

Training Details

Training Dataset

LangCache Sentence Pairs (subsets=['all'], train+val=True)

Dataset: LangCache Sentence Pairs (subsets=['all'], train+val=True)
Size: 40,015,318 training samples
Columns: sentence1, sentence2, and label

Approximate statistics based on the first 1000 samples:

	sentence1	sentence2	label
type	string	string	float
details	min: 27 characters mean: 110.99 characters max: 199 characters	min: 29 characters mean: 110.74 characters max: 191 characters	min: 0.25 mean: 0.49 max: 0.75

Samples:

sentence1	sentence2	label
`The film was remade in Telugu with the same name in 1981 by Chandra Mohan , Jayasudha , Chakravarthy and S. P. Balasubrahmanyam starring K. Vasu .`	`The film was written in Telugu with the same name in 1981 by Chandra Mohan , Jayasudha , Chakravarthy and S. P. Balasubrahmanyam with K. Vasu .`	`0.75`
`The Cauchy stress tensor has therefore the following form`	`Therefore , the cauchy tensor has the following form`	`0.75`
`John Jairo Culma , sometimes spelled as Jhon Jairo Culma ( born 17 March 1981 ) is a Colombian footballer .`	`John Jairo Culma , sometimes known as Jhon Jairo Culma ( born March 17 , 1981 ) , is a Colombian footballer .`	`0.75`

Loss: BinaryCrossEntropyLoss with these parameters:

{
    "activation_fn": "torch.nn.modules.linear.Identity",
    "pos_weight": 0.1028856709599495
}

Evaluation Dataset

LangCache Sentence Pairs (split=test)

Dataset: LangCache Sentence Pairs (split=test)
Size: 74,265 evaluation samples
Columns: sentence1, sentence2, and label

Approximate statistics based on the first 1000 samples:

	sentence1	sentence2	label
type	string	string	int
details	min: 27 characters mean: 112.72 characters max: 197 characters	min: 27 characters mean: 112.54 characters max: 198 characters	0: ~50.30% 1: ~49.70%

Samples:

sentence1	sentence2	label
`The newer Punts are still very much in existence today and race in the same fleets as the older boats .`	`The newer punts are still very much in existence today and run in the same fleets as the older boats .`	`1`
`Turner Valley , was at the Turner Valley Bar N Ranch Airport , southwest of the Turner Valley Bar N Ranch , Alberta , Canada .`	`Turner Valley Bar N Ranch Airport , , was located at Turner Valley Bar N Ranch , southwest of Turner Valley , Alberta , Canada .`	`0`
`After losing his second election , he resigned as opposition leader and was replaced by Geoff Pearsall .`	`Max Bingham resigned as opposition leader after losing his second election , and was replaced by Geoff Pearsall .`	`1`

Loss: BinaryCrossEntropyLoss with these parameters:

{
    "activation_fn": "torch.nn.modules.linear.Identity",
    "pos_weight": 0.1028856709599495
}

Training Hyperparameters

Non-Default Hyperparameters

eval_strategy: steps
per_device_train_batch_size: 48
per_device_eval_batch_size: 48
learning_rate: 0.0002
weight_decay: 0.001
num_train_epochs: 5
warmup_ratio: 0.1
load_best_model_at_end: True
optim: adamw_torch
ddp_find_unused_parameters: False
push_to_hub: True
hub_model_id: redis/langcache-reranker-v2-granite-bce-eps0.5
eval_on_start: True
batch_sampler: no_duplicates

All Hyperparameters

Click to expand

overwrite_output_dir: False
do_predict: False
eval_strategy: steps
prediction_loss_only: True
per_device_train_batch_size: 48
per_device_eval_batch_size: 48
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: 0.0002
weight_decay: 0.001
adam_beta1: 0.9
adam_beta2: 0.999
adam_epsilon: 1e-08
max_grad_norm: 1.0
num_train_epochs: 5
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: False
fp16_opt_level: O1
half_precision_backend: auto
bf16_full_eval: False
fp16_full_eval: False
tf32: None
local_rank: 0
ddp_backend: None
tpu_num_cores: None
tpu_metrics_debug: False
debug: []
dataloader_drop_last: True
dataloader_num_workers: 0
dataloader_prefetch_factor: None
past_index: -1
disable_tqdm: False
remove_unused_columns: True
label_names: None
load_best_model_at_end: True
ignore_data_skip: False
fsdp: []
fsdp_min_num_params: 0
fsdp_config: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}
fsdp_transformer_layer_cls_to_wrap: None
accelerator_config: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None}
parallelism_config: 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: False
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: True
resume_from_checkpoint: None
hub_model_id: redis/langcache-reranker-v2-granite-bce-eps0.5
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: True
use_liger_kernel: False
liger_kernel_config: None
eval_use_gather_object: False
average_tokens_across_devices: True
prompts: None
batch_sampler: no_duplicates
multi_dataset_batch_sampler: proportional
router_mapping: {}
learning_rate_mapping: {}

Training Logs

Click to expand

Epoch	Step	Training Loss	Validation Loss	test_cls_average_precision	NanoQuoraRetrieval_R25_ndcg@1	NanoMSMARCO_R25_ndcg@1	NanoNQ_R25_ndcg@1	NanoBEIR_R25_mean_ndcg@1
0	0	-	13.2186	0.4714	0.0634 (-0.7366)	0.0513 (-0.2887)	0.0635 (-0.1765)	0.0594 (-0.4006)
0.0048	1000	7.9252	-	-	-	-	-	-
0.0096	2000	7.1177	-	-	-	-	-	-
0.0144	3000	5.1202	-	-	-	-	-	-
0.0192	4000	1.832	-	-	-	-	-	-
0.0240	5000	0.6324	-	-	-	-	-	-
0.0288	6000	0.3679	-	-	-	-	-	-
0.0336	7000	0.2218	-	-	-	-	-	-
0.0384	8000	0.1899	-	-	-	-	-	-
0.0432	9000	0.1877	-	-	-	-	-	-
0.0480	10000	0.1865	-	-	-	-	-	-
0.0528	11000	0.1855	-	-	-	-	-	-
0.0576	12000	0.1847	-	-	-	-	-	-
0.0624	13000	0.1841	-	-	-	-	-	-
0.0672	14000	0.1837	-	-	-	-	-	-
0.0720	15000	0.1832	-	-	-	-	-	-
0.0768	16000	0.1828	-	-	-	-	-	-
0.0816	17000	0.1825	-	-	-	-	-	-
0.0864	18000	0.1822	-	-	-	-	-	-
0.0912	19000	0.1819	-	-	-	-	-	-
0.0960	20000	0.1817	0.1721	0.5585	0.3000 (-0.5000)	0.3900 (+0.0500)	0.5500 (+0.3100)	0.4133 (-0.0467)
0.1008	21000	0.1814	-	-	-	-	-	-
0.1056	22000	0.1813	-	-	-	-	-	-
0.1104	23000	0.1811	-	-	-	-	-	-
0.1152	24000	0.1809	-	-	-	-	-	-
0.1200	25000	0.1808	-	-	-	-	-	-
0.1248	26000	0.1805	-	-	-	-	-	-
0.1296	27000	0.1805	-	-	-	-	-	-
0.1343	28000	0.1802	-	-	-	-	-	-
0.1391	29000	0.1801	-	-	-	-	-	-
0.1439	30000	0.18	-	-	-	-	-	-
0.1487	31000	0.1799	-	-	-	-	-	-
0.1535	32000	0.1798	-	-	-	-	-	-
0.1583	33000	0.1796	-	-	-	-	-	-
0.1631	34000	0.1796	-	-	-	-	-	-
0.1679	35000	0.1794	-	-	-	-	-	-
0.1727	36000	0.1794	-	-	-	-	-	-
0.1775	37000	0.1792	-	-	-	-	-	-
0.1823	38000	0.1791	-	-	-	-	-	-
0.1871	39000	0.179	-	-	-	-	-	-
0.1919	40000	0.179	0.1659	0.5798	0.6000 (-0.2000)	0.3200 (-0.0200)	0.4767 (+0.2367)	0.4656 (+0.0056)
0.1967	41000	0.1789	-	-	-	-	-	-
0.2015	42000	0.1788	-	-	-	-	-	-
0.2063	43000	0.1787	-	-	-	-	-	-
0.2111	44000	0.1786	-	-	-	-	-	-
0.2159	45000	0.1785	-	-	-	-	-	-
0.2207	46000	0.1785	-	-	-	-	-	-
0.2255	47000	0.1784	-	-	-	-	-	-
0.2303	48000	0.1782	-	-	-	-	-	-
0.2351	49000	0.1781	-	-	-	-	-	-
0.2399	50000	0.178	-	-	-	-	-	-
0.2447	51000	0.1779	-	-	-	-	-	-
0.2495	52000	0.1777	-	-	-	-	-	-
0.2543	53000	0.1777	-	-	-	-	-	-
0.2591	54000	0.1775	-	-	-	-	-	-
0.2639	55000	0.1774	-	-	-	-	-	-
0.2687	56000	0.1773	-	-	-	-	-	-
0.2735	57000	0.1773	-	-	-	-	-	-
0.2783	58000	0.1771	-	-	-	-	-	-
0.2831	59000	0.1771	-	-	-	-	-	-
0.2879	60000	0.177	0.1599	0.6128	0.5300 (-0.2700)	0.1900 (-0.1500)	0.3400 (+0.1000)	0.3533 (-0.1067)
0.2927	61000	0.1769	-	-	-	-	-	-
0.2975	62000	0.1768	-	-	-	-	-	-
0.3023	63000	0.1768	-	-	-	-	-	-
0.3071	64000	0.1766	-	-	-	-	-	-
0.3119	65000	0.1765	-	-	-	-	-	-
0.3167	66000	0.1765	-	-	-	-	-	-
0.3215	67000	0.1764	-	-	-	-	-	-
0.3263	68000	0.1763	-	-	-	-	-	-
0.3311	69000	0.1762	-	-	-	-	-	-
0.3359	70000	0.176	-	-	-	-	-	-
0.3407	71000	0.1759	-	-	-	-	-	-
0.3455	72000	0.1758	-	-	-	-	-	-
0.3503	73000	0.1757	-	-	-	-	-	-
0.3551	74000	0.1756	-	-	-	-	-	-
0.3599	75000	0.1755	-	-	-	-	-	-
0.3647	76000	0.1754	-	-	-	-	-	-
0.3695	77000	0.1753	-	-	-	-	-	-
0.3743	78000	0.1752	-	-	-	-	-	-
0.3791	79000	0.1751	-	-	-	-	-	-
0.3839	80000	0.175	0.1535	0.6545	0.3800 (-0.4200)	0.2100 (-0.1300)	0.2600 (+0.0200)	0.2833 (-0.1767)
0.3887	81000	0.175	-	-	-	-	-	-
0.3934	82000	0.1749	-	-	-	-	-	-
0.3982	83000	0.1748	-	-	-	-	-	-
0.4030	84000	0.1748	-	-	-	-	-	-
0.4078	85000	0.1747	-	-	-	-	-	-
0.4126	86000	0.1747	-	-	-	-	-	-
0.4174	87000	0.1746	-	-	-	-	-	-
0.4222	88000	0.1746	-	-	-	-	-	-
0.4270	89000	0.1746	-	-	-	-	-	-
0.4318	90000	0.1745	-	-	-	-	-	-
0.4366	91000	0.1746	-	-	-	-	-	-
0.4414	92000	0.1746	-	-	-	-	-	-
0.4462	93000	0.1746	-	-	-	-	-	-
0.4510	94000	0.1744	-	-	-	-	-	-
0.4558	95000	0.1745	-	-	-	-	-	-
0.4606	96000	0.1745	-	-	-	-	-	-
0.4654	97000	0.1744	-	-	-	-	-	-
0.4702	98000	0.1744	-	-	-	-	-	-
0.4750	99000	0.1744	-	-	-	-	-	-
0.4798	100000	0.1745	0.1477	0.6925	0.5600 (-0.2400)	0.2000 (-0.1400)	0.2600 (+0.0200)	0.3400 (-0.1200)
0.4846	101000	0.1744	-	-	-	-	-	-
0.4894	102000	0.1744	-	-	-	-	-	-
0.4942	103000	0.1744	-	-	-	-	-	-
0.4990	104000	0.1743	-	-	-	-	-	-
0.5038	105000	0.1743	-	-	-	-	-	-
0.5086	106000	0.1743	-	-	-	-	-	-
0.5134	107000	0.1743	-	-	-	-	-	-
0.5182	108000	0.1743	-	-	-	-	-	-
0.5230	109000	0.1742	-	-	-	-	-	-
0.5278	110000	0.1743	-	-	-	-	-	-
0.5326	111000	0.1743	-	-	-	-	-	-
0.5374	112000	0.1742	-	-	-	-	-	-
0.5422	113000	0.1743	-	-	-	-	-	-
0.5470	114000	0.1742	-	-	-	-	-	-
0.5518	115000	0.1742	-	-	-	-	-	-
0.5566	116000	0.1742	-	-	-	-	-	-
0.5614	117000	0.1742	-	-	-	-	-	-
0.5662	118000	0.1742	-	-	-	-	-	-
0.5710	119000	0.1742	-	-	-	-	-	-
0.5758	120000	0.1741	0.1434	0.7063	0.5300 (-0.2700)	0.1600 (-0.1800)	0.2500 (+0.0100)	0.3133 (-0.1467)
0.5806	121000	0.1742	-	-	-	-	-	-
0.5854	122000	0.1742	-	-	-	-	-	-
0.5902	123000	0.1742	-	-	-	-	-	-
0.5950	124000	0.1741	-	-	-	-	-	-
0.5998	125000	0.1741	-	-	-	-	-	-
0.6046	126000	0.1742	-	-	-	-	-	-
0.6094	127000	0.1741	-	-	-	-	-	-
0.6142	128000	0.1742	-	-	-	-	-	-
0.6190	129000	0.1741	-	-	-	-	-	-
0.6238	130000	0.1741	-	-	-	-	-	-
0.6286	131000	0.1741	-	-	-	-	-	-
0.6334	132000	0.1741	-	-	-	-	-	-
0.6382	133000	0.174	-	-	-	-	-	-
0.6430	134000	0.1741	-	-	-	-	-	-
0.6478	135000	0.1741	-	-	-	-	-	-
0.6526	136000	0.1741	-	-	-	-	-	-
0.6573	137000	0.174	-	-	-	-	-	-
0.6621	138000	0.1741	-	-	-	-	-	-
0.6669	139000	0.174	-	-	-	-	-	-
0.6717	140000	0.1741	0.1425	0.7261	0.5300 (-0.2700)	0.1600 (-0.1800)	0.3300 (+0.0900)	0.3400 (-0.1200)
0.6765	141000	0.174	-	-	-	-	-	-
0.6813	142000	0.1741	-	-	-	-	-	-
0.6861	143000	0.174	-	-	-	-	-	-
0.6909	144000	0.174	-	-	-	-	-	-
0.6957	145000	0.174	-	-	-	-	-	-
0.7005	146000	0.1741	-	-	-	-	-	-
0.7053	147000	0.174	-	-	-	-	-	-
0.7101	148000	0.174	-	-	-	-	-	-
0.7149	149000	0.174	-	-	-	-	-	-
0.7197	150000	0.174	-	-	-	-	-	-
0.7245	151000	0.174	-	-	-	-	-	-
0.7293	152000	0.174	-	-	-	-	-	-
0.7341	153000	0.174	-	-	-	-	-	-
0.7389	154000	0.174	-	-	-	-	-	-
0.7437	155000	0.174	-	-	-	-	-	-
0.7485	156000	0.174	-	-	-	-	-	-
0.7533	157000	0.1741	-	-	-	-	-	-
0.7581	158000	0.174	-	-	-	-	-	-
0.7629	159000	0.174	-	-	-	-	-	-
0.7677	160000	0.174	0.1412	0.7252	0.4800 (-0.3200)	0.1600 (-0.1800)	0.3067 (+0.0667)	0.3156 (-0.1444)
0.7725	161000	0.174	-	-	-	-	-	-
0.7773	162000	0.1739	-	-	-	-	-	-
0.7821	163000	0.174	-	-	-	-	-	-
0.7869	164000	0.1741	-	-	-	-	-	-
0.7917	165000	0.1739	-	-	-	-	-	-
0.7965	166000	0.174	-	-	-	-	-	-
0.8013	167000	0.174	-	-	-	-	-	-
0.8061	168000	0.174	-	-	-	-	-	-
0.8109	169000	0.174	-	-	-	-	-	-
0.8157	170000	0.1739	-	-	-	-	-	-
0.8205	171000	0.174	-	-	-	-	-	-
0.8253	172000	0.174	-	-	-	-	-	-
0.8301	173000	0.174	-	-	-	-	-	-
0.8349	174000	0.174	-	-	-	-	-	-
0.8397	175000	0.174	-	-	-	-	-	-
0.8445	176000	0.174	-	-	-	-	-	-
0.8493	177000	0.174	-	-	-	-	-	-
0.8541	178000	0.174	-	-	-	-	-	-
0.8589	179000	0.1739	-	-	-	-	-	-
0.8637	180000	0.1739	0.1403	0.7127	0.4000 (-0.4000)	0.1800 (-0.1600)	0.3700 (+0.1300)	0.3167 (-0.1433)
0.8685	181000	0.174	-	-	-	-	-	-
0.8733	182000	0.174	-	-	-	-	-	-
0.8781	183000	0.1739	-	-	-	-	-	-
0.8829	184000	0.174	-	-	-	-	-	-
0.8877	185000	0.174	-	-	-	-	-	-
0.8925	186000	0.174	-	-	-	-	-	-
0.8973	187000	0.1739	-	-	-	-	-	-
0.9021	188000	0.174	-	-	-	-	-	-
0.9069	189000	0.1739	-	-	-	-	-	-
0.9117	190000	0.174	-	-	-	-	-	-
0.9164	191000	0.174	-	-	-	-	-	-
0.9212	192000	0.174	-	-	-	-	-	-
0.9260	193000	0.174	-	-	-	-	-	-
0.9308	194000	0.174	-	-	-	-	-	-
0.9356	195000	0.1739	-	-	-	-	-	-
0.9404	196000	0.1739	-	-	-	-	-	-
0.9452	197000	0.1739	-	-	-	-	-	-
0.9500	198000	0.174	-	-	-	-	-	-
0.9548	199000	0.1739	-	-	-	-	-	-
0.9596	200000	0.1739	0.1405	0.7189	0.4100 (-0.3900)	0.1800 (-0.1600)	0.3700 (+0.1300)	0.3200 (-0.1400)
0.9644	201000	0.174	-	-	-	-	-	-
0.9692	202000	0.174	-	-	-	-	-	-
0.9740	203000	0.1739	-	-	-	-	-	-
0.9788	204000	0.174	-	-	-	-	-	-
0.9836	205000	0.1739	-	-	-	-	-	-
0.9884	206000	0.1739	-	-	-	-	-	-
0.9932	207000	0.1739	-	-	-	-	-	-
0.9980	208000	0.1738	-	-	-	-	-	-
1.0028	209000	0.1739	-	-	-	-	-	-
1.0076	210000	0.1739	-	-	-	-	-	-
1.0124	211000	0.1739	-	-	-	-	-	-
1.0172	212000	0.1739	-	-	-	-	-	-
1.0220	213000	0.1739	-	-	-	-	-	-
1.0268	214000	0.174	-	-	-	-	-	-
1.0316	215000	0.1739	-	-	-	-	-	-
1.0364	216000	0.1739	-	-	-	-	-	-
1.0412	217000	0.1739	-	-	-	-	-	-
1.0460	218000	0.1739	-	-	-	-	-	-
1.0508	219000	0.1739	-	-	-	-	-	-
1.0556	220000	0.174	0.1395	0.7357	0.5800 (-0.2200)	0.1800 (-0.1600)	0.3800 (+0.1400)	0.3800 (-0.0800)
1.0604	221000	0.1739	-	-	-	-	-	-
1.0652	222000	0.1738	-	-	-	-	-	-
1.0700	223000	0.1739	-	-	-	-	-	-
1.0748	224000	0.1739	-	-	-	-	-	-
1.0796	225000	0.1739	-	-	-	-	-	-
1.0844	226000	0.1739	-	-	-	-	-	-
1.0892	227000	0.1739	-	-	-	-	-	-
1.0940	228000	0.1738	-	-	-	-	-	-
1.0988	229000	0.1739	-	-	-	-	-	-
1.1036	230000	0.1739	-	-	-	-	-	-
1.1084	231000	0.1739	-	-	-	-	-	-
1.1132	232000	0.1739	-	-	-	-	-	-
1.1180	233000	0.1739	-	-	-	-	-	-
1.1228	234000	0.1739	-	-	-	-	-	-
1.1276	235000	0.1739	-	-	-	-	-	-
1.1324	236000	0.174	-	-	-	-	-	-
1.1372	237000	0.1739	-	-	-	-	-	-
1.1420	238000	0.1739	-	-	-	-	-	-
1.1468	239000	0.1739	-	-	-	-	-	-
1.1516	240000	0.1738	0.1394	0.7347	0.4200 (-0.3800)	0.1900 (-0.1500)	0.3600 (+0.1200)	0.3233 (-0.1367)
1.1564	241000	0.174	-	-	-	-	-	-
1.1612	242000	0.1739	-	-	-	-	-	-
1.1660	243000	0.1738	-	-	-	-	-	-
1.1708	244000	0.1739	-	-	-	-	-	-
1.1756	245000	0.1739	-	-	-	-	-	-
1.1803	246000	0.1738	-	-	-	-	-	-
1.1851	247000	0.1739	-	-	-	-	-	-
1.1899	248000	0.1739	-	-	-	-	-	-
1.1947	249000	0.1739	-	-	-	-	-	-
1.1995	250000	0.1739	-	-	-	-	-	-
1.2043	251000	0.1738	-	-	-	-	-	-
1.2091	252000	0.1739	-	-	-	-	-	-
1.2139	253000	0.1738	-	-	-	-	-	-
1.2187	254000	0.1739	-	-	-	-	-	-
1.2235	255000	0.1739	-	-	-	-	-	-
1.2283	256000	0.1739	-	-	-	-	-	-
1.2331	257000	0.1739	-	-	-	-	-	-
1.2379	258000	0.1739	-	-	-	-	-	-
1.2427	259000	0.1738	-	-	-	-	-	-
1.2475	260000	0.1738	0.1392	0.7325	0.4500 (-0.3500)	0.2000 (-0.1400)	0.3600 (+0.1200)	0.3367 (-0.1233)
1.2523	261000	0.174	-	-	-	-	-	-
1.2571	262000	0.1739	-	-	-	-	-	-
1.2619	263000	0.1739	-	-	-	-	-	-
1.2667	264000	0.1738	-	-	-	-	-	-
1.2715	265000	0.1739	-	-	-	-	-	-
1.2763	266000	0.1738	-	-	-	-	-	-
1.2811	267000	0.1739	-	-	-	-	-	-
1.2859	268000	0.1739	-	-	-	-	-	-
1.2907	269000	0.1739	-	-	-	-	-	-
1.2955	270000	0.1738	-	-	-	-	-	-
1.3003	271000	0.174	-	-	-	-	-	-
1.3051	272000	0.1739	-	-	-	-	-	-
1.3099	273000	0.1738	-	-	-	-	-	-
1.3147	274000	0.1739	-	-	-	-	-	-
1.3195	275000	0.1739	-	-	-	-	-	-
1.3243	276000	0.1739	-	-	-	-	-	-
1.3291	277000	0.1739	-	-	-	-	-	-
1.3339	278000	0.1738	-	-	-	-	-	-
1.3387	279000	0.1739	-	-	-	-	-	-
1.3435	280000	0.1738	0.1394	0.7343	0.4900 (-0.3100)	0.1600 (-0.1800)	0.4100 (+0.1700)	0.3533 (-0.1067)
1.3483	281000	0.1739	-	-	-	-	-	-
1.3531	282000	0.1739	-	-	-	-	-	-
1.3579	283000	0.1738	-	-	-	-	-	-
1.3627	284000	0.1739	-	-	-	-	-	-
1.3675	285000	0.1739	-	-	-	-	-	-
1.3723	286000	0.1738	-	-	-	-	-	-
1.3771	287000	0.1738	-	-	-	-	-	-
1.3819	288000	0.1739	-	-	-	-	-	-
1.3867	289000	0.1738	-	-	-	-	-	-
1.3915	290000	0.1738	-	-	-	-	-	-
1.3963	291000	0.1738	-	-	-	-	-	-
1.4011	292000	0.1738	-	-	-	-	-	-
1.4059	293000	0.1737	-	-	-	-	-	-
1.4107	294000	0.1738	-	-	-	-	-	-
1.4155	295000	0.1737	-	-	-	-	-	-
1.4203	296000	0.1738	-	-	-	-	-	-
1.4251	297000	0.1738	-	-	-	-	-	-
1.4299	298000	0.1738	-	-	-	-	-	-
1.4347	299000	0.1738	-	-	-	-	-	-
1.4394	300000	0.1738	0.1395	0.7236	0.4000 (-0.4000)	0.1800 (-0.1600)	0.3900 (+0.1500)	0.3233 (-0.1367)
1.4442	301000	0.1739	-	-	-	-	-	-
1.4490	302000	0.1738	-	-	-	-	-	-
1.4538	303000	0.1737	-	-	-	-	-	-
1.4586	304000	0.1739	-	-	-	-	-	-
1.4634	305000	0.1738	-	-	-	-	-	-
1.4682	306000	0.1738	-	-	-	-	-	-
1.4730	307000	0.1738	-	-	-	-	-	-
1.4778	308000	0.1738	-	-	-	-	-	-
1.4826	309000	0.1738	-	-	-	-	-	-
1.4874	310000	0.1738	-	-	-	-	-	-
1.4922	311000	0.1738	-	-	-	-	-	-
1.4970	312000	0.1738	-	-	-	-	-	-
1.5018	313000	0.1738	-	-	-	-	-	-
1.5066	314000	0.1738	-	-	-	-	-	-
1.5114	315000	0.1738	-	-	-	-	-	-
1.5162	316000	0.1738	-	-	-	-	-	-
1.5210	317000	0.1737	-	-	-	-	-	-
1.5258	318000	0.1738	-	-	-	-	-	-
1.5306	319000	0.1739	-	-	-	-	-	-
1.5354	320000	0.1738	0.1388	0.7420	0.4800 (-0.3200)	0.1800 (-0.1600)	0.4000 (+0.1600)	0.3533 (-0.1067)
1.5402	321000	0.1738	-	-	-	-	-	-
1.5450	322000	0.1738	-	-	-	-	-	-
1.5498	323000	0.1738	-	-	-	-	-	-
1.5546	324000	0.1738	-	-	-	-	-	-
1.5594	325000	0.1738	-	-	-	-	-	-
1.5642	326000	0.1738	-	-	-	-	-	-
1.5690	327000	0.1738	-	-	-	-	-	-
1.5738	328000	0.1738	-	-	-	-	-	-
1.5786	329000	0.1738	-	-	-	-	-	-
1.5834	330000	0.1738	-	-	-	-	-	-
1.5882	331000	0.1738	-	-	-	-	-	-
1.5930	332000	0.1738	-	-	-	-	-	-
1.5978	333000	0.1738	-	-	-	-	-	-
1.6026	334000	0.1738	-	-	-	-	-	-
1.6074	335000	0.1738	-	-	-	-	-	-
1.6122	336000	0.1738	-	-	-	-	-	-
1.6170	337000	0.1739	-	-	-	-	-	-
1.6218	338000	0.1738	-	-	-	-	-	-
1.6266	339000	0.1738	-	-	-	-	-	-
1.6314	340000	0.1738	0.1388	0.7394	0.4900 (-0.3100)	0.1800 (-0.1600)	0.4000 (+0.1600)	0.3567 (-0.1033)
1.6362	341000	0.1737	-	-	-	-	-	-
1.6410	342000	0.1738	-	-	-	-	-	-
1.6458	343000	0.1737	-	-	-	-	-	-
1.6506	344000	0.1738	-	-	-	-	-	-
1.6554	345000	0.1738	-	-	-	-	-	-
1.6602	346000	0.1738	-	-	-	-	-	-
1.6650	347000	0.1737	-	-	-	-	-	-
1.6698	348000	0.1738	-	-	-	-	-	-
1.6746	349000	0.1738	-	-	-	-	-	-
1.6794	350000	0.1738	-	-	-	-	-	-
1.6842	351000	0.1738	-	-	-	-	-	-
1.6890	352000	0.1738	-	-	-	-	-	-
1.6938	353000	0.1737	-	-	-	-	-	-
1.6986	354000	0.1738	-	-	-	-	-	-
1.7033	355000	0.1738	-	-	-	-	-	-
1.7081	356000	0.1738	-	-	-	-	-	-
1.7129	357000	0.1738	-	-	-	-	-	-
1.7177	358000	0.1737	-	-	-	-	-	-
1.7225	359000	0.1738	-	-	-	-	-	-
1.7273	360000	0.1738	0.1386	0.7350	0.5067 (-0.2933)	0.2300 (-0.1100)	0.4200 (+0.1800)	0.3856 (-0.0744)
1.7321	361000	0.1738	-	-	-	-	-	-
1.7369	362000	0.1737	-	-	-	-	-	-
1.7417	363000	0.1738	-	-	-	-	-	-
1.7465	364000	0.1737	-	-	-	-	-	-
1.7513	365000	0.1738	-	-	-	-	-	-
1.7561	366000	0.1738	-	-	-	-	-	-
1.7609	367000	0.1737	-	-	-	-	-	-
1.7657	368000	0.1738	-	-	-	-	-	-
1.7705	369000	0.1738	-	-	-	-	-	-
1.7753	370000	0.1737	-	-	-	-	-	-
1.7801	371000	0.1738	-	-	-	-	-	-
1.7849	372000	0.1738	-	-	-	-	-	-
1.7897	373000	0.1738	-	-	-	-	-	-
1.7945	374000	0.1738	-	-	-	-	-	-
1.7993	375000	0.1737	-	-	-	-	-	-
1.8041	376000	0.1738	-	-	-	-	-	-
1.8089	377000	0.1738	-	-	-	-	-	-
1.8137	378000	0.1737	-	-	-	-	-	-
1.8185	379000	0.1738	-	-	-	-	-	-
1.8233	380000	0.1737	0.1384	0.7420	0.4700 (-0.3300)	0.2000 (-0.1400)	0.4100 (+0.1700)	0.3600 (-0.1000)
1.8281	381000	0.1738	-	-	-	-	-	-
1.8329	382000	0.1738	-	-	-	-	-	-
1.8377	383000	0.1738	-	-	-	-	-	-
1.8425	384000	0.1738	-	-	-	-	-	-
1.8473	385000	0.1739	-	-	-	-	-	-
1.8521	386000	0.1739	-	-	-	-	-	-
1.8569	387000	0.1737	-	-	-	-	-	-
1.8617	388000	0.1737	-	-	-	-	-	-
1.8665	389000	0.1737	-	-	-	-	-	-
1.8713	390000	0.1739	-	-	-	-	-	-
1.8761	391000	0.1738	-	-	-	-	-	-
1.8809	392000	0.1738	-	-	-	-	-	-
1.8857	393000	0.1739	-	-	-	-	-	-
1.8905	394000	0.1738	-	-	-	-	-	-
1.8953	395000	0.1738	-	-	-	-	-	-
1.9001	396000	0.1738	-	-	-	-	-	-
1.9049	397000	0.1739	-	-	-	-	-	-
1.9097	398000	0.1738	-	-	-	-	-	-
1.9145	399000	0.1738	-	-	-	-	-	-
1.9193	400000	0.1738	0.1389	0.7360	0.4600 (-0.3400)	0.2200 (-0.1200)	0.4200 (+0.1800)	0.3667 (-0.0933)
1.9241	401000	0.1739	-	-	-	-	-	-
1.9289	402000	0.1738	-	-	-	-	-	-
1.9337	403000	0.1738	-	-	-	-	-	-
1.9385	404000	0.1738	-	-	-	-	-	-
1.9433	405000	0.1738	-	-	-	-	-	-
1.9481	406000	0.1738	-	-	-	-	-	-
1.9529	407000	0.1737	-	-	-	-	-	-
1.9577	408000	0.1738	-	-	-	-	-	-
1.9624	409000	0.1738	-	-	-	-	-	-
1.9672	410000	0.1738	-	-	-	-	-	-
1.9720	411000	0.1738	-	-	-	-	-	-
1.9768	412000	0.1738	-	-	-	-	-	-
1.9816	413000	0.1738	-	-	-	-	-	-
1.9864	414000	0.1738	-	-	-	-	-	-
1.9912	415000	0.1738	-	-	-	-	-	-
1.9960	416000	0.1737	-	-	-	-	-	-
2.0008	417000	0.1737	-	-	-	-	-	-
2.0056	418000	0.1737	-	-	-	-	-	-
2.0104	419000	0.1738	-	-	-	-	-	-
2.0152	420000	0.1737	0.1384	0.7446	0.6100 (-0.1900)	0.2100 (-0.1300)	0.3800 (+0.1400)	0.4000 (-0.0600)
2.0200	421000	0.1738	-	-	-	-	-	-
2.0248	422000	0.1737	-	-	-	-	-	-
2.0296	423000	0.1738	-	-	-	-	-	-
2.0344	424000	0.1738	-	-	-	-	-	-
2.0392	425000	0.1738	-	-	-	-	-	-
2.0440	426000	0.1738	-	-	-	-	-	-
2.0488	427000	0.1738	-	-	-	-	-	-
2.0536	428000	0.1738	-	-	-	-	-	-
2.0584	429000	0.1739	-	-	-	-	-	-
2.0632	430000	0.1738	-	-	-	-	-	-
2.0680	431000	0.1737	-	-	-	-	-	-
2.0728	432000	0.1738	-	-	-	-	-	-
2.0776	433000	0.1738	-	-	-	-	-	-
2.0824	434000	0.1738	-	-	-	-	-	-
2.0872	435000	0.1738	-	-	-	-	-	-
2.0920	436000	0.1737	-	-	-	-	-	-
2.0968	437000	0.1738	-	-	-	-	-	-
2.1016	438000	0.1738	-	-	-	-	-	-
2.1064	439000	0.1738	-	-	-	-	-	-
2.1112	440000	0.1738	0.1388	0.7355	0.4700 (-0.3300)	0.2000 (-0.1400)	0.3900 (+0.1500)	0.3533 (-0.1067)
2.1160	441000	0.1739	-	-	-	-	-	-
2.1208	442000	0.1738	-	-	-	-	-	-
2.1256	443000	0.1738	-	-	-	-	-	-
2.1304	444000	0.1738	-	-	-	-	-	-
2.1352	445000	0.1738	-	-	-	-	-	-
2.1400	446000	0.1739	-	-	-	-	-	-
2.1448	447000	0.1737	-	-	-	-	-	-
2.1496	448000	0.1737	-	-	-	-	-	-
2.1544	449000	0.1738	-	-	-	-	-	-
2.1592	450000	0.1738	-	-	-	-	-	-
2.1640	451000	0.1737	-	-	-	-	-	-
2.1688	452000	0.1738	-	-	-	-	-	-
2.1736	453000	0.1738	-	-	-	-	-	-
2.1784	454000	0.1738	-	-	-	-	-	-
2.1832	455000	0.1738	-	-	-	-	-	-
2.1880	456000	0.1738	-	-	-	-	-	-
2.1928	457000	0.1738	-	-	-	-	-	-
2.1976	458000	0.1739	-	-	-	-	-	-
2.2024	459000	0.1737	-	-	-	-	-	-
2.2072	460000	0.1738	0.1390	0.7377	0.5000 (-0.3000)	0.2000 (-0.1400)	0.4000 (+0.1600)	0.3667 (-0.0933)
2.2120	461000	0.1738	-	-	-	-	-	-
2.2168	462000	0.1738	-	-	-	-	-	-
2.2216	463000	0.1738	-	-	-	-	-	-
2.2263	464000	0.1739	-	-	-	-	-	-
2.2311	465000	0.1738	-	-	-	-	-	-
2.2359	466000	0.1739	-	-	-	-	-	-
2.2407	467000	0.1737	-	-	-	-	-	-
2.2455	468000	0.1738	-	-	-	-	-	-
2.2503	469000	0.1738	-	-	-	-	-	-
2.2551	470000	0.1738	-	-	-	-	-	-
2.2599	471000	0.1738	-	-	-	-	-	-
2.2647	472000	0.1738	-	-	-	-	-	-
2.2695	473000	0.1738	-	-	-	-	-	-
2.2743	474000	0.1738	-	-	-	-	-	-
2.2791	475000	0.1738	-	-	-	-	-	-
2.2839	476000	0.1739	-	-	-	-	-	-
2.2887	477000	0.1738	-	-	-	-	-	-
2.2935	478000	0.1738	-	-	-	-	-	-
2.2983	479000	0.1738	-	-	-	-	-	-
2.3031	480000	0.1739	0.1386	0.7417	0.5400 (-0.2600)	0.1900 (-0.1500)	0.4400 (+0.2000)	0.3900 (-0.0700)
2.3079	481000	0.1738	-	-	-	-	-	-
2.3127	482000	0.1738	-	-	-	-	-	-
2.3175	483000	0.1738	-	-	-	-	-	-
2.3223	484000	0.1738	-	-	-	-	-	-
2.3271	485000	0.1738	-	-	-	-	-	-
2.3319	486000	0.1738	-	-	-	-	-	-
2.3367	487000	0.1738	-	-	-	-	-	-
2.3415	488000	0.1737	-	-	-	-	-	-
2.3463	489000	0.1738	-	-	-	-	-	-
2.3511	490000	0.1738	-	-	-	-	-	-
2.3559	491000	0.1738	-	-	-	-	-	-
2.3607	492000	0.1738	-	-	-	-	-	-
2.3655	493000	0.1738	-	-	-	-	-	-
2.3703	494000	0.1738	-	-	-	-	-	-
2.3751	495000	0.1737	-	-	-	-	-	-
2.3799	496000	0.1738	-	-	-	-	-	-
2.3847	497000	0.1738	-	-	-	-	-	-
2.3895	498000	0.1737	-	-	-	-	-	-
2.3943	499000	0.1738	-	-	-	-	-	-
2.3991	500000	0.1737	0.1385	0.7404	0.5200 (-0.2800)	0.2000 (-0.1400)	0.4100 (+0.1700)	0.3767 (-0.0833)
2.4039	501000	0.1737	-	-	-	-	-	-
2.4087	502000	0.1738	-	-	-	-	-	-
2.4135	503000	0.1737	-	-	-	-	-	-
2.4183	504000	0.1738	-	-	-	-	-	-
2.4231	505000	0.1737	-	-	-	-	-	-
2.4279	506000	0.1738	-	-	-	-	-	-
2.4327	507000	0.1738	-	-	-	-	-	-
2.4375	508000	0.1737	-	-	-	-	-	-
2.4423	509000	0.1738	-	-	-	-	-	-
2.4471	510000	0.1738	-	-	-	-	-	-
2.4519	511000	0.1737	-	-	-	-	-	-
2.4567	512000	0.1738	-	-	-	-	-	-
2.4615	513000	0.1738	-	-	-	-	-	-
2.4663	514000	0.1737	-	-	-	-	-	-
2.4711	515000	0.1738	-	-	-	-	-	-
2.4759	516000	0.1738	-	-	-	-	-	-
2.4807	517000	0.1738	-	-	-	-	-	-
2.4854	518000	0.1738	-	-	-	-	-	-
2.4902	519000	0.1737	-	-	-	-	-	-
2.4950	520000	0.1738	0.1388	0.7382	0.5100 (-0.2900)	0.2000 (-0.1400)	0.4200 (+0.1800)	0.3767 (-0.0833)
2.4998	521000	0.1737	-	-	-	-	-	-
2.5046	522000	0.1738	-	-	-	-	-	-
2.5094	523000	0.1738	-	-	-	-	-	-
2.5142	524000	0.1738	-	-	-	-	-	-
2.5190	525000	0.1737	-	-	-	-	-	-
2.5238	526000	0.1737	-	-	-	-	-	-
2.5286	527000	0.1738	-	-	-	-	-	-
2.5334	528000	0.1737	-	-	-	-	-	-
2.5382	529000	0.1738	-	-	-	-	-	-
2.5430	530000	0.1738	-	-	-	-	-	-
2.5478	531000	0.1738	-	-	-	-	-	-
2.5526	532000	0.1738	-	-	-	-	-	-
2.5574	533000	0.1738	-	-	-	-	-	-
2.5622	534000	0.1738	-	-	-	-	-	-
2.5670	535000	0.1738	-	-	-	-	-	-
2.5718	536000	0.1738	-	-	-	-	-	-
2.5766	537000	0.1737	-	-	-	-	-	-
2.5814	538000	0.1738	-	-	-	-	-	-
2.5862	539000	0.1738	-	-	-	-	-	-
2.5910	540000	0.1738	0.1388	0.7373	0.5200 (-0.2800)	0.2100 (-0.1300)	0.4100 (+0.1700)	0.3800 (-0.0800)
2.5958	541000	0.1737	-	-	-	-	-	-
2.6006	542000	0.1737	-	-	-	-	-	-
2.6054	543000	0.1738	-	-	-	-	-	-
2.6102	544000	0.1738	-	-	-	-	-	-
2.6150	545000	0.1738	-	-	-	-	-	-
2.6198	546000	0.1739	-	-	-	-	-	-
2.6246	547000	0.1738	-	-	-	-	-	-
2.6294	548000	0.1738	-	-	-	-	-	-
2.6342	549000	0.1738	-	-	-	-	-	-
2.6390	550000	0.1737	-	-	-	-	-	-
2.6438	551000	0.1737	-	-	-	-	-	-
2.6486	552000	0.1738	-	-	-	-	-	-
2.6534	553000	0.1738	-	-	-	-	-	-
2.6582	554000	0.1737	-	-	-	-	-	-
2.6630	555000	0.1737	-	-	-	-	-	-
2.6678	556000	0.1738	-	-	-	-	-	-
2.6726	557000	0.1738	-	-	-	-	-	-
2.6774	558000	0.1738	-	-	-	-	-	-
2.6822	559000	0.1738	-	-	-	-	-	-
2.6870	560000	0.1737	0.1388	0.7335	0.4500 (-0.3500)	0.1900 (-0.1500)	0.3900 (+0.1500)	0.3433 (-0.1167)
2.6918	561000	0.1737	-	-	-	-	-	-
2.6966	562000	0.1738	-	-	-	-	-	-
2.7014	563000	0.1738	-	-	-	-	-	-
2.7062	564000	0.1737	-	-	-	-	-	-
2.7110	565000	0.1738	-	-	-	-	-	-
2.7158	566000	0.1737	-	-	-	-	-	-
2.7206	567000	0.1738	-	-	-	-	-	-
2.7254	568000	0.1737	-	-	-	-	-	-
2.7302	569000	0.1738	-	-	-	-	-	-
2.7350	570000	0.1737	-	-	-	-	-	-
2.7398	571000	0.1738	-	-	-	-	-	-
2.7446	572000	0.1737	-	-	-	-	-	-
2.7493	573000	0.1738	-	-	-	-	-	-
2.7541	574000	0.1738	-	-	-	-	-	-
2.7589	575000	0.1738	-	-	-	-	-	-
2.7637	576000	0.1738	-	-	-	-	-	-
2.7685	577000	0.1738	-	-	-	-	-	-
2.7733	578000	0.1738	-	-	-	-	-	-
2.7781	579000	0.1737	-	-	-	-	-	-
2.7829	580000	0.1738	0.1387	0.7400	0.5200 (-0.2800)	0.2100 (-0.1300)	0.4000 (+0.1600)	0.3767 (-0.0833)
2.7877	581000	0.1739	-	-	-	-	-	-
2.7925	582000	0.1737	-	-	-	-	-	-
2.7973	583000	0.1737	-	-	-	-	-	-
2.8021	584000	0.1738	-	-	-	-	-	-
2.8069	585000	0.1738	-	-	-	-	-	-
2.8117	586000	0.1738	-	-	-	-	-	-
2.8165	587000	0.1738	-	-	-	-	-	-
2.8213	588000	0.1738	-	-	-	-	-	-
2.8261	589000	0.1738	-	-	-	-	-	-
2.8309	590000	0.1738	-	-	-	-	-	-
2.8357	591000	0.1738	-	-	-	-	-	-
2.8405	592000	0.1738	-	-	-	-	-	-
2.8453	593000	0.1738	-	-	-	-	-	-
2.8501	594000	0.1739	-	-	-	-	-	-
2.8549	595000	0.1738	-	-	-	-	-	-
2.8597	596000	0.1737	-	-	-	-	-	-
2.8645	597000	0.1738	-	-	-	-	-	-
2.8693	598000	0.1738	-	-	-	-	-	-
2.8741	599000	0.1738	-	-	-	-	-	-
2.8789	600000	0.1738	0.1388	0.7398	0.5200 (-0.2800)	0.2000 (-0.1400)	0.3900 (+0.1500)	0.3700 (-0.0900)
2.8837	601000	0.1738	-	-	-	-	-	-
2.8885	602000	0.1738	-	-	-	-	-	-
2.8933	603000	0.1738	-	-	-	-	-	-
2.8981	604000	0.1738	-	-	-	-	-	-
2.9029	605000	0.1739	-	-	-	-	-	-
2.9077	606000	0.1738	-	-	-	-	-	-
2.9125	607000	0.1738	-	-	-	-	-	-
2.9173	608000	0.1738	-	-	-	-	-	-
2.9221	609000	0.1738	-	-	-	-	-	-
2.9269	610000	0.1738	-	-	-	-	-	-
2.9317	611000	0.1737	-	-	-	-	-	-
2.9365	612000	0.1738	-	-	-	-	-	-
2.9413	613000	0.1737	-	-	-	-	-	-
2.9461	614000	0.1738	-	-	-	-	-	-
2.9509	615000	0.1738	-	-	-	-	-	-
2.9557	616000	0.1738	-	-	-	-	-	-
2.9605	617000	0.1737	-	-	-	-	-	-
2.9653	618000	0.1738	-	-	-	-	-	-
2.9701	619000	0.1739	-	-	-	-	-	-
2.9749	620000	0.1738	0.1388	0.7415	0.5200 (-0.2800)	0.2100 (-0.1300)	0.4200 (+0.1800)	0.3833 (-0.0767)
2.9797	621000	0.1737	-	-	-	-	-	-
2.9845	622000	0.1738	-	-	-	-	-	-
2.9893	623000	0.1738	-	-	-	-	-	-
2.9941	624000	0.1738	-	-	-	-	-	-
2.9989	625000	0.1737	-	-	-	-	-	-
3.0037	626000	0.1737	-	-	-	-	-	-
3.0084	627000	0.1737	-	-	-	-	-	-
3.0132	628000	0.1738	-	-	-	-	-	-
3.0180	629000	0.1738	-	-	-	-	-	-
3.0228	630000	0.1737	-	-	-	-	-	-
3.0276	631000	0.1738	-	-	-	-	-	-
3.0324	632000	0.1738	-	-	-	-	-	-
3.0372	633000	0.1738	-	-	-	-	-	-
3.0420	634000	0.1738	-	-	-	-	-	-
3.0468	635000	0.1738	-	-	-	-	-	-
3.0516	636000	0.1738	-	-	-	-	-	-
3.0564	637000	0.1739	-	-	-	-	-	-
3.0612	638000	0.1738	-	-	-	-	-	-
3.0660	639000	0.1737	-	-	-	-	-	-
3.0708	640000	0.1738	0.1388	0.7392	0.5200 (-0.2800)	0.2000 (-0.1400)	0.4100 (+0.1700)	0.3767 (-0.0833)
3.0756	641000	0.1738	-	-	-	-	-	-
3.0804	642000	0.1738	-	-	-	-	-	-
3.0852	643000	0.1738	-	-	-	-	-	-
3.0900	644000	0.1738	-	-	-	-	-	-
3.0948	645000	0.1738	-	-	-	-	-	-
3.0996	646000	0.1738	-	-	-	-	-	-
3.1044	647000	0.1738	-	-	-	-	-	-
3.1092	648000	0.1739	-	-	-	-	-	-
3.1140	649000	0.1738	-	-	-	-	-	-
3.1188	650000	0.1739	-	-	-	-	-	-
3.1236	651000	0.1738	-	-	-	-	-	-
3.1284	652000	0.1738	-	-	-	-	-	-
3.1332	653000	0.1739	-	-	-	-	-	-
3.1380	654000	0.1739	-	-	-	-	-	-
3.1428	655000	0.1738	-	-	-	-	-	-
3.1476	656000	0.1737	-	-	-	-	-	-
3.1524	657000	0.1738	-	-	-	-	-	-
3.1572	658000	0.1738	-	-	-	-	-	-
3.1620	659000	0.1738	-	-	-	-	-	-
3.1668	660000	0.1738	0.1390	0.7394	0.5200 (-0.2800)	0.2000 (-0.1400)	0.4000 (+0.1600)	0.3733 (-0.0867)
3.1716	661000	0.1738	-	-	-	-	-	-
3.1764	662000	0.1738	-	-	-	-	-	-
3.1812	663000	0.1738	-	-	-	-	-	-
3.1860	664000	0.1738	-	-	-	-	-	-
3.1908	665000	0.1738	-	-	-	-	-	-
3.1956	666000	0.1738	-	-	-	-	-	-
3.2004	667000	0.1738	-	-	-	-	-	-
3.2052	668000	0.1738	-	-	-	-	-	-
3.2100	669000	0.1738	-	-	-	-	-	-
3.2148	670000	0.1738	-	-	-	-	-	-
3.2196	671000	0.1738	-	-	-	-	-	-
3.2244	672000	0.1739	-	-	-	-	-	-
3.2292	673000	0.1738	-	-	-	-	-	-
3.2340	674000	0.1738	-	-	-	-	-	-
3.2388	675000	0.1738	-	-	-	-	-	-
3.2436	676000	0.1738	-	-	-	-	-	-
3.2484	677000	0.1738	-	-	-	-	-	-
3.2532	678000	0.1739	-	-	-	-	-	-
3.2580	679000	0.1738	-	-	-	-	-	-
3.2628	680000	0.1738	0.1390	0.7391	0.5400 (-0.2600)	0.2000 (-0.1400)	0.4200 (+0.1800)	0.3867 (-0.0733)
3.2676	681000	0.1738	-	-	-	-	-	-
3.2723	682000	0.1738	-	-	-	-	-	-
3.2771	683000	0.1738	-	-	-	-	-	-
3.2819	684000	0.1738	-	-	-	-	-	-
3.2867	685000	0.1739	-	-	-	-	-	-
3.2915	686000	0.1738	-	-	-	-	-	-
3.2963	687000	0.1737	-	-	-	-	-	-
3.3011	688000	0.1739	-	-	-	-	-	-
3.3059	689000	0.1738	-	-	-	-	-	-
3.3107	690000	0.1738	-	-	-	-	-	-
3.3155	691000	0.1738	-	-	-	-	-	-
3.3203	692000	0.1739	-	-	-	-	-	-
3.3251	693000	0.1738	-	-	-	-	-	-
3.3299	694000	0.1739	-	-	-	-	-	-
3.3347	695000	0.1738	-	-	-	-	-	-
3.3395	696000	0.1738	-	-	-	-	-	-
3.3443	697000	0.1737	-	-	-	-	-	-
3.3491	698000	0.1739	-	-	-	-	-	-
3.3539	699000	0.1738	-	-	-	-	-	-
3.3587	700000	0.1738	0.1390	0.7394	0.5200 (-0.2800)	0.2000 (-0.1400)	0.4000 (+0.1600)	0.3733 (-0.0867)
3.3635	701000	0.1739	-	-	-	-	-	-
3.3683	702000	0.1738	-	-	-	-	-	-
3.3731	703000	0.1738	-	-	-	-	-	-
3.3779	704000	0.1737	-	-	-	-	-	-
3.3827	705000	0.1738	-	-	-	-	-	-
3.3875	706000	0.1738	-	-	-	-	-	-
3.3923	707000	0.1738	-	-	-	-	-	-
3.3971	708000	0.1737	-	-	-	-	-	-
3.4019	709000	0.1738	-	-	-	-	-	-
3.4067	710000	0.1737	-	-	-	-	-	-
3.4115	711000	0.1738	-	-	-	-	-	-
3.4163	712000	0.1737	-	-	-	-	-	-
3.4211	713000	0.1738	-	-	-	-	-	-
3.4259	714000	0.1737	-	-	-	-	-	-
3.4307	715000	0.1738	-	-	-	-	-	-
3.4355	716000	0.1737	-	-	-	-	-	-
3.4403	717000	0.1738	-	-	-	-	-	-
3.4451	718000	0.1738	-	-	-	-	-	-
3.4499	719000	0.1737	-	-	-	-	-	-
3.4547	720000	0.1737	0.1389	0.7397	0.5200 (-0.2800)	0.2000 (-0.1400)	0.3900 (+0.1500)	0.3700 (-0.0900)
3.4595	721000	0.1738	-	-	-	-	-	-
3.4643	722000	0.1738	-	-	-	-	-	-
3.4691	723000	0.1738	-	-	-	-	-	-
3.4739	724000	0.1737	-	-	-	-	-	-
3.4787	725000	0.1738	-	-	-	-	-	-
3.4835	726000	0.1738	-	-	-	-	-	-
3.4883	727000	0.1738	-	-	-	-	-	-
3.4931	728000	0.1738	-	-	-	-	-	-
3.4979	729000	0.1738	-	-	-	-	-	-
3.5027	730000	0.1738	-	-	-	-	-	-
3.5075	731000	0.1738	-	-	-	-	-	-
3.5123	732000	0.1738	-	-	-	-	-	-
3.5171	733000	0.1738	-	-	-	-	-	-
3.5219	734000	0.1737	-	-	-	-	-	-
3.5267	735000	0.1738	-	-	-	-	-	-
3.5314	736000	0.1738	-	-	-	-	-	-
3.5362	737000	0.1737	-	-	-	-	-	-
3.5410	738000	0.1738	-	-	-	-	-	-
3.5458	739000	0.1738	-	-	-	-	-	-
3.5506	740000	0.1738	0.1390	0.7397	0.5200 (-0.2800)	0.2000 (-0.1400)	0.4100 (+0.1700)	0.3767 (-0.0833)
3.5554	741000	0.1738	-	-	-	-	-	-
3.5602	742000	0.1737	-	-	-	-	-	-
3.5650	743000	0.1738	-	-	-	-	-	-
3.5698	744000	0.1738	-	-	-	-	-	-
3.5746	745000	0.1738	-	-	-	-	-	-
3.5794	746000	0.1738	-	-	-	-	-	-
3.5842	747000	0.1738	-	-	-	-	-	-
3.5890	748000	0.1738	-	-	-	-	-	-
3.5938	749000	0.1738	-	-	-	-	-	-
3.5986	750000	0.1738	-	-	-	-	-	-
3.6034	751000	0.1738	-	-	-	-	-	-
3.6082	752000	0.1738	-	-	-	-	-	-
3.6130	753000	0.1738	-	-	-	-	-	-
3.6178	754000	0.1738	-	-	-	-	-	-
3.6226	755000	0.1738	-	-	-	-	-	-
3.6274	756000	0.1738	-	-	-	-	-	-
3.6322	757000	0.1738	-	-	-	-	-	-
3.6370	758000	0.1737	-	-	-	-	-	-
3.6418	759000	0.1738	-	-	-	-	-	-
3.6466	760000	0.1737	0.1390	0.7403	0.5200 (-0.2800)	0.2000 (-0.1400)	0.3700 (+0.1300)	0.3633 (-0.0967)
3.6514	761000	0.1739	-	-	-	-	-	-
3.6562	762000	0.1738	-	-	-	-	-	-
3.6610	763000	0.1738	-	-	-	-	-	-
3.6658	764000	0.1737	-	-	-	-	-	-
3.6706	765000	0.1738	-	-	-	-	-	-
3.6754	766000	0.1738	-	-	-	-	-	-
3.6802	767000	0.1738	-	-	-	-	-	-
3.6850	768000	0.1738	-	-	-	-	-	-
3.6898	769000	0.1738	-	-	-	-	-	-
3.6946	770000	0.1737	-	-	-	-	-	-
3.6994	771000	0.1739	-	-	-	-	-	-
3.7042	772000	0.1738	-	-	-	-	-	-
3.7090	773000	0.1738	-	-	-	-	-	-
3.7138	774000	0.1738	-	-	-	-	-	-
3.7186	775000	0.1738	-	-	-	-	-	-
3.7234	776000	0.1738	-	-	-	-	-	-
3.7282	777000	0.1738	-	-	-	-	-	-
3.7330	778000	0.1738	-	-	-	-	-	-
3.7378	779000	0.1738	-	-	-	-	-	-
3.7426	780000	0.1738	0.1390	0.7393	0.5200 (-0.2800)	0.2100 (-0.1300)	0.4000 (+0.1600)	0.3767 (-0.0833)
3.7474	781000	0.1737	-	-	-	-	-	-
3.7522	782000	0.1738	-	-	-	-	-	-
3.7570	783000	0.1739	-	-	-	-	-	-
3.7618	784000	0.1738	-	-	-	-	-	-
3.7666	785000	0.1738	-	-	-	-	-	-
3.7714	786000	0.1738	-	-	-	-	-	-
3.7762	787000	0.1737	-	-	-	-	-	-
3.7810	788000	0.1739	-	-	-	-	-	-
3.7858	789000	0.1738	-	-	-	-	-	-
3.7906	790000	0.1738	-	-	-	-	-	-
3.7953	791000	0.1738	-	-	-	-	-	-
3.8001	792000	0.1738	-	-	-	-	-	-
3.8049	793000	0.1738	-	-	-	-	-	-
3.8097	794000	0.1738	-	-	-	-	-	-
3.8145	795000	0.1738	-	-	-	-	-	-
3.8193	796000	0.1739	-	-	-	-	-	-
3.8241	797000	0.1738	-	-	-	-	-	-
3.8289	798000	0.1738	-	-	-	-	-	-
3.8337	799000	0.1738	-	-	-	-	-	-
3.8385	800000	0.1739	0.1391	0.7387	0.5200 (-0.2800)	0.2000 (-0.1400)	0.3800 (+0.1400)	0.3667 (-0.0933)
3.8433	801000	0.1739	-	-	-	-	-	-
3.8481	802000	0.1738	-	-	-	-	-	-
3.8529	803000	0.1739	-	-	-	-	-	-
3.8577	804000	0.1737	-	-	-	-	-	-
3.8625	805000	0.1738	-	-	-	-	-	-
3.8673	806000	0.1738	-	-	-	-	-	-
3.8721	807000	0.1739	-	-	-	-	-	-
3.8769	808000	0.1738	-	-	-	-	-	-
3.8817	809000	0.1738	-	-	-	-	-	-
3.8865	810000	0.1739	-	-	-	-	-	-
3.8913	811000	0.1738	-	-	-	-	-	-
3.8961	812000	0.1738	-	-	-	-	-	-
3.9009	813000	0.1738	-	-	-	-	-	-
3.9057	814000	0.1739	-	-	-	-	-	-
3.9105	815000	0.1739	-	-	-	-	-	-
3.9153	816000	0.1738	-	-	-	-	-	-
3.9201	817000	0.1738	-	-	-	-	-	-
3.9249	818000	0.1739	-	-	-	-	-	-
3.9297	819000	0.1738	-	-	-	-	-	-
3.9345	820000	0.1738	0.1390	0.7392	0.5200 (-0.2800)	0.2100 (-0.1300)	0.3800 (+0.1400)	0.3700 (-0.0900)
3.9393	821000	0.1738	-	-	-	-	-	-
3.9441	822000	0.1738	-	-	-	-	-	-
3.9489	823000	0.1738	-	-	-	-	-	-
3.9537	824000	0.1738	-	-	-	-	-	-
3.9585	825000	0.1738	-	-	-	-	-	-
3.9633	826000	0.1738	-	-	-	-	-	-
3.9681	827000	0.1739	-	-	-	-	-	-
3.9729	828000	0.1738	-	-	-	-	-	-
3.9777	829000	0.1738	-	-	-	-	-	-
3.9825	830000	0.1738	-	-	-	-	-	-
3.9873	831000	0.1738	-	-	-	-	-	-
3.9921	832000	0.1739	-	-	-	-	-	-
3.9969	833000	0.1738	-	-	-	-	-	-
4.0017	834000	0.1738	-	-	-	-	-	-
4.0065	835000	0.1738	-	-	-	-	-	-
4.0113	836000	0.1738	-	-	-	-	-	-
4.0161	837000	0.1738	-	-	-	-	-	-
4.0209	838000	0.1738	-	-	-	-	-	-
4.0257	839000	0.1738	-	-	-	-	-	-
4.0305	840000	0.1738	0.1391	0.7393	0.5100 (-0.2900)	0.1900 (-0.1500)	0.3800 (+0.1400)	0.3600 (-0.1000)
4.0353	841000	0.1738	-	-	-	-	-	-
4.0401	842000	0.1738	-	-	-	-	-	-
4.0449	843000	0.1738	-	-	-	-	-	-
4.0497	844000	0.1738	-	-	-	-	-	-
4.0544	845000	0.1738	-	-	-	-	-	-
4.0592	846000	0.1739	-	-	-	-	-	-
4.0640	847000	0.1738	-	-	-	-	-	-
4.0688	848000	0.1738	-	-	-	-	-	-
4.0736	849000	0.1738	-	-	-	-	-	-
4.0784	850000	0.1738	-	-	-	-	-	-
4.0832	851000	0.1738	-	-	-	-	-	-
4.0880	852000	0.1739	-	-	-	-	-	-
4.0928	853000	0.1737	-	-	-	-	-	-
4.0976	854000	0.1738	-	-	-	-	-	-
4.1024	855000	0.1738	-	-	-	-	-	-
4.1072	856000	0.1739	-	-	-	-	-	-
4.1120	857000	0.1738	-	-	-	-	-	-
4.1168	858000	0.1739	-	-	-	-	-	-
4.1216	859000	0.1739	-	-	-	-	-	-
4.1264	860000	0.1739	0.1391	0.7392	0.5200 (-0.2800)	0.2200 (-0.1200)	0.4100 (+0.1700)	0.3833 (-0.0767)
4.1312	861000	0.1739	-	-	-	-	-	-
4.1360	862000	0.1739	-	-	-	-	-	-
4.1408	863000	0.1739	-	-	-	-	-	-
4.1456	864000	0.1738	-	-	-	-	-	-
4.1504	865000	0.1738	-	-	-	-	-	-
4.1552	866000	0.1739	-	-	-	-	-	-
4.1600	867000	0.1738	-	-	-	-	-	-
4.1648	868000	0.1738	-	-	-	-	-	-
4.1696	869000	0.1738	-	-	-	-	-	-
4.1744	870000	0.1738	-	-	-	-	-	-
4.1792	871000	0.1738	-	-	-	-	-	-
4.1840	872000	0.1738	-	-	-	-	-	-
4.1888	873000	0.1739	-	-	-	-	-	-
4.1936	874000	0.1738	-	-	-	-	-	-
4.1984	875000	0.1739	-	-	-	-	-	-
4.2032	876000	0.1738	-	-	-	-	-	-
4.2080	877000	0.1738	-	-	-	-	-	-
4.2128	878000	0.1738	-	-	-	-	-	-
4.2176	879000	0.1738	-	-	-	-	-	-
4.2224	880000	0.1739	0.1391	0.7389	0.5200 (-0.2800)	0.2200 (-0.1200)	0.4200 (+0.1800)	0.3867 (-0.0733)
4.2272	881000	0.1738	-	-	-	-	-	-
4.2320	882000	0.1738	-	-	-	-	-	-
4.2368	883000	0.1739	-	-	-	-	-	-
4.2416	884000	0.1738	-	-	-	-	-	-
4.2464	885000	0.1738	-	-	-	-	-	-
4.2512	886000	0.1739	-	-	-	-	-	-
4.2560	887000	0.1739	-	-	-	-	-	-
4.2608	888000	0.1739	-	-	-	-	-	-
4.2656	889000	0.1738	-	-	-	-	-	-
4.2704	890000	0.1739	-	-	-	-	-	-
4.2752	891000	0.1739	-	-	-	-	-	-
4.2800	892000	0.1738	-	-	-	-	-	-
4.2848	893000	0.1739	-	-	-	-	-	-
4.2896	894000	0.1739	-	-	-	-	-	-
4.2944	895000	0.1738	-	-	-	-	-	-
4.2992	896000	0.1739	-	-	-	-	-	-
4.3040	897000	0.1739	-	-	-	-	-	-
4.3088	898000	0.1738	-	-	-	-	-	-
4.3136	899000	0.1739	-	-	-	-	-	-
4.3183	900000	0.1738	0.1391	0.7393	0.5200 (-0.2800)	0.2100 (-0.1300)	0.4100 (+0.1700)	0.3800 (-0.0800)
4.3231	901000	0.1739	-	-	-	-	-	-
4.3279	902000	0.1738	-	-	-	-	-	-
4.3327	903000	0.1738	-	-	-	-	-	-
4.3375	904000	0.1738	-	-	-	-	-	-
4.3423	905000	0.1738	-	-	-	-	-	-
4.3471	906000	0.1738	-	-	-	-	-	-
4.3519	907000	0.1738	-	-	-	-	-	-
4.3567	908000	0.1738	-	-	-	-	-	-
4.3615	909000	0.1739	-	-	-	-	-	-
4.3663	910000	0.1738	-	-	-	-	-	-
4.3711	911000	0.1738	-	-	-	-	-	-
4.3759	912000	0.1737	-	-	-	-	-	-
4.3807	913000	0.1738	-	-	-	-	-	-
4.3855	914000	0.1738	-	-	-	-	-	-
4.3903	915000	0.1738	-	-	-	-	-	-
4.3951	916000	0.1738	-	-	-	-	-	-
4.3999	917000	0.1738	-	-	-	-	-	-
4.4047	918000	0.1737	-	-	-	-	-	-
4.4095	919000	0.1738	-	-	-	-	-	-
4.4143	920000	0.1737	0.1391	0.7394	0.5000 (-0.3000)	0.2000 (-0.1400)	0.3900 (+0.1500)	0.3633 (-0.0967)
4.4191	921000	0.1738	-	-	-	-	-	-
4.4239	922000	0.1738	-	-	-	-	-	-
4.4287	923000	0.1738	-	-	-	-	-	-
4.4335	924000	0.1737	-	-	-	-	-	-
4.4383	925000	0.1738	-	-	-	-	-	-
4.4431	926000	0.1739	-	-	-	-	-	-
4.4479	927000	0.1738	-	-	-	-	-	-
4.4527	928000	0.1737	-	-	-	-	-	-
4.4575	929000	0.1738	-	-	-	-	-	-
4.4623	930000	0.1738	-	-	-	-	-	-
4.4671	931000	0.1737	-	-	-	-	-	-
4.4719	932000	0.1738	-	-	-	-	-	-
4.4767	933000	0.1738	-	-	-	-	-	-
4.4815	934000	0.1738	-	-	-	-	-	-
4.4863	935000	0.1738	-	-	-	-	-	-
4.4911	936000	0.1738	-	-	-	-	-	-
4.4959	937000	0.1738	-	-	-	-	-	-
4.5007	938000	0.1738	-	-	-	-	-	-
4.5055	939000	0.1738	-	-	-	-	-	-
4.5103	940000	0.1738	0.1391	0.7391	0.5200 (-0.2800)	0.2100 (-0.1300)	0.4100 (+0.1700)	0.3800 (-0.0800)
4.5151	941000	0.1738	-	-	-	-	-	-
4.5199	942000	0.1738	-	-	-	-	-	-
4.5247	943000	0.1738	-	-	-	-	-	-
4.5295	944000	0.1739	-	-	-	-	-	-
4.5343	945000	0.1738	-	-	-	-	-	-
4.5391	946000	0.1738	-	-	-	-	-	-
4.5439	947000	0.1738	-	-	-	-	-	-
4.5487	948000	0.1738	-	-	-	-	-	-
4.5535	949000	0.1738	-	-	-	-	-	-
4.5583	950000	0.1738	-	-	-	-	-	-
4.5631	951000	0.1738	-	-	-	-	-	-
4.5679	952000	0.1738	-	-	-	-	-	-
4.5727	953000	0.1738	-	-	-	-	-	-
4.5774	954000	0.1738	-	-	-	-	-	-
4.5822	955000	0.1738	-	-	-	-	-	-
4.5870	956000	0.1739	-	-	-	-	-	-
4.5918	957000	0.1738	-	-	-	-	-	-
4.5966	958000	0.1737	-	-	-	-	-	-
4.6014	959000	0.1737	-	-	-	-	-	-
4.6062	960000	0.1738	0.1391	0.7394	0.5200 (-0.2800)	0.2100 (-0.1300)	0.3900 (+0.1500)	0.3733 (-0.0867)
4.6110	961000	0.1738	-	-	-	-	-	-
4.6158	962000	0.1739	-	-	-	-	-	-
4.6206	963000	0.1739	-	-	-	-	-	-
4.6254	964000	0.1738	-	-	-	-	-	-
4.6302	965000	0.1738	-	-	-	-	-	-
4.6350	966000	0.1738	-	-	-	-	-	-
4.6398	967000	0.1738	-	-	-	-	-	-
4.6446	968000	0.1738	-	-	-	-	-	-
4.6494	969000	0.1738	-	-	-	-	-	-
4.6542	970000	0.1738	-	-	-	-	-	-
4.6590	971000	0.1738	-	-	-	-	-	-
4.6638	972000	0.1738	-	-	-	-	-	-
4.6686	973000	0.1738	-	-	-	-	-	-
4.6734	974000	0.1738	-	-	-	-	-	-
4.6782	975000	0.1738	-	-	-	-	-	-
4.6830	976000	0.1738	-	-	-	-	-	-
4.6878	977000	0.1738	-	-	-	-	-	-
4.6926	978000	0.1738	-	-	-	-	-	-
4.6974	979000	0.1738	-	-	-	-	-	-
4.7022	980000	0.1739	0.1391	0.7395	0.5200 (-0.2800)	0.2000 (-0.1400)	0.4100 (+0.1700)	0.3767 (-0.0833)
4.7070	981000	0.1738	-	-	-	-	-	-
4.7118	982000	0.1739	-	-	-	-	-	-
4.7166	983000	0.1738	-	-	-	-	-	-
4.7214	984000	0.1738	-	-	-	-	-	-
4.7262	985000	0.1738	-	-	-	-	-	-
4.7310	986000	0.1738	-	-	-	-	-	-
4.7358	987000	0.1737	-	-	-	-	-	-
4.7406	988000	0.1738	-	-	-	-	-	-
4.7454	989000	0.1737	-	-	-	-	-	-
4.7502	990000	0.1739	-	-	-	-	-	-
4.7550	991000	0.1738	-	-	-	-	-	-
4.7598	992000	0.1738	-	-	-	-	-	-
4.7646	993000	0.1738	-	-	-	-	-	-
4.7694	994000	0.1738	-	-	-	-	-	-
4.7742	995000	0.1738	-	-	-	-	-	-
4.7790	996000	0.1738	-	-	-	-	-	-
4.7838	997000	0.1738	-	-	-	-	-	-
4.7886	998000	0.1738	-	-	-	-	-	-
4.7934	999000	0.1738	-	-	-	-	-	-
4.7982	1000000	0.1737	0.1391	0.7392	0.5400 (-0.2600)	0.2000 (-0.1400)	0.4000 (+0.1600)	0.3800 (-0.0800)
4.8030	1001000	0.1738	-	-	-	-	-	-
4.8078	1002000	0.1739	-	-	-	-	-	-
4.8126	1003000	0.1738	-	-	-	-	-	-
4.8174	1004000	0.1738	-	-	-	-	-	-
4.8222	1005000	0.1738	-	-	-	-	-	-
4.8270	1006000	0.1738	-	-	-	-	-	-
4.8318	1007000	0.1738	-	-	-	-	-	-
4.8366	1008000	0.1739	-	-	-	-	-	-
4.8413	1009000	0.1738	-	-	-	-	-	-
4.8461	1010000	0.1739	-	-	-	-	-	-
4.8509	1011000	0.1739	-	-	-	-	-	-
4.8557	1012000	0.1738	-	-	-	-	-	-
4.8605	1013000	0.1737	-	-	-	-	-	-
4.8653	1014000	0.1738	-	-	-	-	-	-
4.8701	1015000	0.1739	-	-	-	-	-	-
4.8749	1016000	0.1738	-	-	-	-	-	-
4.8797	1017000	0.1738	-	-	-	-	-	-
4.8845	1018000	0.1739	-	-	-	-	-	-
4.8893	1019000	0.1738	-	-	-	-	-	-
4.8941	1020000	0.1738	0.1391	0.7393	0.5300 (-0.2700)	0.2000 (-0.1400)	0.4000 (+0.1600)	0.3767 (-0.0833)
4.8989	1021000	0.1739	-	-	-	-	-	-
4.9037	1022000	0.1739	-	-	-	-	-	-
4.9085	1023000	0.1738	-	-	-	-	-	-
4.9133	1024000	0.1739	-	-	-	-	-	-
4.9181	1025000	0.1738	-	-	-	-	-	-
4.9229	1026000	0.1739	-	-	-	-	-	-
4.9277	1027000	0.1738	-	-	-	-	-	-
4.9325	1028000	0.1738	-	-	-	-	-	-
4.9373	1029000	0.1738	-	-	-	-	-	-
4.9421	1030000	0.1738	-	-	-	-	-	-
4.9469	1031000	0.1738	-	-	-	-	-	-
4.9517	1032000	0.1738	-	-	-	-	-	-
4.9565	1033000	0.1738	-	-	-	-	-	-
4.9613	1034000	0.1738	-	-	-	-	-	-
4.9661	1035000	0.1738	-	-	-	-	-	-
4.9709	1036000	0.1739	-	-	-	-	-	-
4.9757	1037000	0.1738	-	-	-	-	-	-
4.9805	1038000	0.1738	-	-	-	-	-	-
4.9853	1039000	0.1738	-	-	-	-	-	-
4.9901	1040000	0.1738	0.1391	0.7395	0.5100 (-0.2900)	0.2000 (-0.1400)	0.4000 (+0.1600)	0.3700 (-0.0900)
4.9949	1041000	0.1738	-	-	-	-	-	-
4.9997	1042000	0.1738	-	-	-	-	-	-

The bold row denotes the saved checkpoint.

Framework Versions

Python: 3.12.3
Sentence Transformers: 5.1.0
Transformers: 4.56.0
PyTorch: 2.8.0+cu128
Accelerate: 1.10.1
Datasets: 4.0.0
Tokenizers: 0.22.0

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",
}