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+---
+base_model: cointegrated/rubert-tiny2
+datasets: []
+language: []
+library_name: sentence-transformers
+metrics:
+- cosine_accuracy@1
+- cosine_accuracy@3
+- cosine_accuracy@5
+- cosine_precision@1
+- cosine_precision@3
+- cosine_precision@5
+- cosine_precision@10
+- cosine_recall@1
+- cosine_recall@3
+- cosine_recall@5
+- cosine_recall@10
+- cosine_ndcg@10
+- cosine_mrr@10
+- cosine_map@100
+- dot_accuracy@1
+- dot_accuracy@3
+- dot_accuracy@5
+- dot_precision@1
+- dot_precision@3
+- dot_precision@5
+- dot_precision@10
+- dot_recall@1
+- dot_recall@3
+- dot_recall@5
+- dot_recall@10
+- dot_ndcg@10
+- dot_mrr@10
+- dot_map@100
+pipeline_tag: sentence-similarity
+tags:
+- sentence-transformers
+- sentence-similarity
+- feature-extraction
+- generated_from_trainer
+- dataset_size:1630
+- loss:MultipleNegativesRankingLoss
+widget:
+- source_sentence: Сотруднику не войти в ЛК
+ sentences:
+ - 'При проблемах со входом в личный кабинет, прежде чем создавать заявку в поддержку,
+ убедитесь, что заходите в ЛК на сайте https://company-x5.ru, указываете актуальные
+ и верные логин и пароль. Если Вам неизвестен логин, обратитесь к руководителю
+ (ДМ), он сможет посмотреть Ваш логин и сбросить пароль в веб-табеле. Для самостоятельного
+ сброса пароля позвоните с вашего мобильного телефона на +7 (XXX) XXX XX XX, наберите
+ добавочный номер 10100, нажмите * и подтвердите сброс пароля, нажав #. Обновленный
+ пароль отправляется по SMS.'
+ - Рекомендуем уточнить наличие вакансий в регионе, куда планируется переезд. Обратиться
+ к руководителю для формирования заявки в рамках процесса «Перевод» с заполнением
+ атрибутов заявки.
+ - 'Оформление отпуска без сохранения заработной платы возможно 2 способами: 1. в
+ разделе "Отпуска" в левом меню Личного кабинета сотрудника (https://company-x5.ru/vacations/plan?vp_page=1
+ ); 2. в разделе "Заявки", группа "Отпуск", плитка "Отпуск без сохранения ЗП".
+ (https://company-x5.ru/requests/tiles/my/)'
+- source_sentence: Как внести данные об автомобиле?
+ sentences:
+ - У Вас согласована Заявка на удаленную работу. График на удаленную работу ранее
+ Вами не создавался. Вам необходимо зайти в личный кабинет, открыть вкладку "Удаленная
+ работа" и создать себе график (от 1 до 6 месяцев). После создания, график перейдет
+ к руководителю на согласование. А после согласования к Вам на подписание. После
+ того, как процесс завершится, информирование прекратится.
+ - Для внесения данных по личному автомобилю обратитесь, пожалуйста, к своему руководителю
+ для создания заявки по теме "Изменение режима характера работы", подтема "Установка
+ РХР и топливной карты". В комментариях опишите ситуацию и приложите ПТС, СТС,
+ страховой полис и водительское удостоверение.
+ - Выплата производится в случае утраты или повреждения жизненно необходимого недвижимого
+ имущества работника, вследствие стихийных бедствий, пожара, кражи и т.д.;
+- source_sentence: не получается оформить внутреннего совместителя
+ sentences:
+ - Создайте, пожалуйста, обращение в ИТ поддержку на портале support
+ - Вам необходимо обратиться в специалистам HR для того, чтобы они удалили мероприятие
+ "работа на дому" и доп.соглашение, тогда статус текущей заявки станет «Не актуально»
+ и появится возможность создать новую.
+ - Оформление заявки н�� прием внутреннего совместителя производится руководителем
+ магазина/отдела/РЦ, в который трудоустраивается сотрудник. При положительном решении
+ он создает заявку по теме "Прием совместителей". Инструкция и шаблоны доступны
+ по ссылке https://company-x5.ru/cms/zayavkaskillaz
+- source_sentence: Пропал календарь
+ sentences:
+ - 'При проблемах со входом в личный кабинет, прежде чем создавать заявку в поддержку,
+ убедитесь, что заходите в ЛК на сайте https://company-x5.ru, указываете актуальные
+ и верные логин и пароль. Если Вам неизвестен логин, обратитесь к руководителю
+ (ДМ), он сможет посмотреть Ваш логин и сбросить пароль в веб-табеле. Для самостоятельного
+ сброса пароля позвоните с вашего мобильного телефона на +7 (XXX) XXX XX XX, наберите
+ добавочный номер 10100, нажмите * и подтвердите сброс пароля, нажав #. Обновленный
+ пароль отправляется по SMS.'
+ - Доступ к программе "карьера" появляется спустя 4 месяца после трудоутстройства
+ в компанию. Если по прошествии 4х месяцев раздел по-прежнему недоступен, обратитесь
+ в поддержку
+ - Вкладка "график работы" недоступна сотрудникам с организационным присвоением "Офис"
+ и на данный момент доступна только сотрудникам розницы.
+- source_sentence: когда я получу деньги за отпуск
+ sentences:
+ - Создайте, пожалуйста, обращение в ИТ поддержку на портале support
+ - Для изменения процента занятости сотруднику создайте, пожалуйста, заявку на сотрудника
+ по теме "Изменение режима, характера работы"
+ - Отпускные начисляются не позднее чем за три рабочих дня до даты начала отпуска.
+model-index:
+- name: SentenceTransformer based on cointegrated/rubert-tiny2
+ results:
+ - task:
+ type: information-retrieval
+ name: Information Retrieval
+ dataset:
+ name: test
+ type: test
+ metrics:
+ - type: cosine_accuracy@1
+ value: 0.7760736196319018
+ name: Cosine Accuracy@1
+ - type: cosine_accuracy@3
+ value: 0.9337423312883436
+ name: Cosine Accuracy@3
+ - type: cosine_accuracy@5
+ value: 0.9674846625766871
+ name: Cosine Accuracy@5
+ - type: cosine_precision@1
+ value: 0.7760736196319018
+ name: Cosine Precision@1
+ - type: cosine_precision@3
+ value: 0.3112474437627812
+ name: Cosine Precision@3
+ - type: cosine_precision@5
+ value: 0.19349693251533742
+ name: Cosine Precision@5
+ - type: cosine_precision@10
+ value: 0.09852760736196317
+ name: Cosine Precision@10
+ - type: cosine_recall@1
+ value: 0.7760736196319018
+ name: Cosine Recall@1
+ - type: cosine_recall@3
+ value: 0.9337423312883436
+ name: Cosine Recall@3
+ - type: cosine_recall@5
+ value: 0.9674846625766871
+ name: Cosine Recall@5
+ - type: cosine_recall@10
+ value: 0.9852760736196319
+ name: Cosine Recall@10
+ - type: cosine_ndcg@10
+ value: 0.8898589364073973
+ name: Cosine Ndcg@10
+ - type: cosine_mrr@10
+ value: 0.85816851689551
+ name: Cosine Mrr@10
+ - type: cosine_map@100
+ value: 0.8590198622778252
+ name: Cosine Map@100
+ - type: dot_accuracy@1
+ value: 0.7760736196319018
+ name: Dot Accuracy@1
+ - type: dot_accuracy@3
+ value: 0.9337423312883436
+ name: Dot Accuracy@3
+ - type: dot_accuracy@5
+ value: 0.9674846625766871
+ name: Dot Accuracy@5
+ - type: dot_precision@1
+ value: 0.7760736196319018
+ name: Dot Precision@1
+ - type: dot_precision@3
+ value: 0.3112474437627812
+ name: Dot Precision@3
+ - type: dot_precision@5
+ value: 0.19349693251533742
+ name: Dot Precision@5
+ - type: dot_precision@10
+ value: 0.09852760736196317
+ name: Dot Precision@10
+ - type: dot_recall@1
+ value: 0.7760736196319018
+ name: Dot Recall@1
+ - type: dot_recall@3
+ value: 0.9337423312883436
+ name: Dot Recall@3
+ - type: dot_recall@5
+ value: 0.9674846625766871
+ name: Dot Recall@5
+ - type: dot_recall@10
+ value: 0.9852760736196319
+ name: Dot Recall@10
+ - type: dot_ndcg@10
+ value: 0.8898589364073973
+ name: Dot Ndcg@10
+ - type: dot_mrr@10
+ value: 0.85816851689551
+ name: Dot Mrr@10
+ - type: dot_map@100
+ value: 0.8590198622778252
+ name: Dot Map@100
+ - type: cosine_accuracy@1
+ value: 0.9895705521472392
+ name: Cosine Accuracy@1
+ - type: cosine_accuracy@3
+ value: 1.0
+ name: Cosine Accuracy@3
+ - type: cosine_accuracy@5
+ value: 1.0
+ name: Cosine Accuracy@5
+ - type: cosine_precision@1
+ value: 0.9895705521472392
+ name: Cosine Precision@1
+ - type: cosine_precision@3
+ value: 0.33333333333333326
+ name: Cosine Precision@3
+ - type: cosine_precision@5
+ value: 0.2
+ name: Cosine Precision@5
+ - type: cosine_precision@10
+ value: 0.1
+ name: Cosine Precision@10
+ - type: cosine_recall@1
+ value: 0.9895705521472392
+ name: Cosine Recall@1
+ - type: cosine_recall@3
+ value: 1.0
+ name: Cosine Recall@3
+ - type: cosine_recall@5
+ value: 1.0
+ name: Cosine Recall@5
+ - type: cosine_recall@10
+ value: 1.0
+ name: Cosine Recall@10
+ - type: cosine_ndcg@10
+ value: 0.996150801110868
+ name: Cosine Ndcg@10
+ - type: cosine_mrr@10
+ value: 0.9947852760736197
+ name: Cosine Mrr@10
+ - type: cosine_map@100
+ value: 0.9947852760736197
+ name: Cosine Map@100
+ - type: dot_accuracy@1
+ value: 0.9895705521472392
+ name: Dot Accuracy@1
+ - type: dot_accuracy@3
+ value: 1.0
+ name: Dot Accuracy@3
+ - type: dot_accuracy@5
+ value: 1.0
+ name: Dot Accuracy@5
+ - type: dot_precision@1
+ value: 0.9895705521472392
+ name: Dot Precision@1
+ - type: dot_precision@3
+ value: 0.33333333333333326
+ name: Dot Precision@3
+ - type: dot_precision@5
+ value: 0.2
+ name: Dot Precision@5
+ - type: dot_precision@10
+ value: 0.1
+ name: Dot Precision@10
+ - type: dot_recall@1
+ value: 0.9895705521472392
+ name: Dot Recall@1
+ - type: dot_recall@3
+ value: 1.0
+ name: Dot Recall@3
+ - type: dot_recall@5
+ value: 1.0
+ name: Dot Recall@5
+ - type: dot_recall@10
+ value: 1.0
+ name: Dot Recall@10
+ - type: dot_ndcg@10
+ value: 0.996150801110868
+ name: Dot Ndcg@10
+ - type: dot_mrr@10
+ value: 0.9947852760736197
+ name: Dot Mrr@10
+ - type: dot_map@100
+ value: 0.9947852760736197
+ name: Dot Map@100
+---
+
+# SentenceTransformer based on cointegrated/rubert-tiny2
+
+This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [cointegrated/rubert-tiny2](https://huggingface.co/cointegrated/rubert-tiny2). It maps sentences & paragraphs to a 312-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:** [cointegrated/rubert-tiny2](https://huggingface.co/cointegrated/rubert-tiny2)
+- **Maximum Sequence Length:** 2048 tokens
+- **Output Dimensionality:** 312 tokens
+- **Similarity Function:** Cosine Similarity
+
+
+
+
+### Model Sources
+
+- **Documentation:** [Sentence Transformers Documentation](https://sbert.net)
+- **Repository:** [Sentence Transformers on GitHub](https://github.com/UKPLab/sentence-transformers)
+- **Hugging Face:** [Sentence Transformers on Hugging Face](https://huggingface.co/models?library=sentence-transformers)
+
+### Full Model Architecture
+
+```
+SentenceTransformer(
+ (0): Transformer({'max_seq_length': 2048, 'do_lower_case': False}) with Transformer model: BertModel
+ (1): Pooling({'word_embedding_dimension': 312, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
+ (2): Normalize()
+)
+```
+
+## Usage
+
+### Direct Usage (Sentence Transformers)
+
+First install the Sentence Transformers library:
+
+```bash
+pip install -U sentence-transformers
+```
+
+Then you can load this model and run inference.
+```python
+from sentence_transformers import SentenceTransformer
+
+# Download from the 🤗 Hub
+model = SentenceTransformer("WpythonW/RUbert-tiny_custom_test_2")
+# Run inference
+sentences = [
+ 'когда я получу деньги за отпуск',
+ 'Отпускные начисляются не позднее чем за три рабочих дня до даты начала отпуска.',
+ 'Создайте, пожалуйста, обращение в ИТ поддержку на портале support',
+]
+embeddings = model.encode(sentences)
+print(embeddings.shape)
+# [3, 312]
+
+# Get the similarity scores for the embeddings
+similarities = model.similarity(embeddings, embeddings)
+print(similarities.shape)
+# [3, 3]
+```
+
+
+
+
+
+
+
+## Evaluation
+
+### Metrics
+
+#### Information Retrieval
+* Dataset: `test`
+* Evaluated with [InformationRetrievalEvaluator](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.InformationRetrievalEvaluator)
+
+| Metric | Value |
+|:--------------------|:----------|
+| cosine_accuracy@1 | 0.7761 |
+| cosine_accuracy@3 | 0.9337 |
+| cosine_accuracy@5 | 0.9675 |
+| cosine_precision@1 | 0.7761 |
+| cosine_precision@3 | 0.3112 |
+| cosine_precision@5 | 0.1935 |
+| cosine_precision@10 | 0.0985 |
+| cosine_recall@1 | 0.7761 |
+| cosine_recall@3 | 0.9337 |
+| cosine_recall@5 | 0.9675 |
+| cosine_recall@10 | 0.9853 |
+| cosine_ndcg@10 | 0.8899 |
+| cosine_mrr@10 | 0.8582 |
+| **cosine_map@100** | **0.859** |
+| dot_accuracy@1 | 0.7761 |
+| dot_accuracy@3 | 0.9337 |
+| dot_accuracy@5 | 0.9675 |
+| dot_precision@1 | 0.7761 |
+| dot_precision@3 | 0.3112 |
+| dot_precision@5 | 0.1935 |
+| dot_precision@10 | 0.0985 |
+| dot_recall@1 | 0.7761 |
+| dot_recall@3 | 0.9337 |
+| dot_recall@5 | 0.9675 |
+| dot_recall@10 | 0.9853 |
+| dot_ndcg@10 | 0.8899 |
+| dot_mrr@10 | 0.8582 |
+| dot_map@100 | 0.859 |
+
+#### Information Retrieval
+* Dataset: `test`
+* Evaluated with [InformationRetrievalEvaluator](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.InformationRetrievalEvaluator)
+
+| Metric | Value |
+|:--------------------|:-----------|
+| cosine_accuracy@1 | 0.9896 |
+| cosine_accuracy@3 | 1.0 |
+| cosine_accuracy@5 | 1.0 |
+| cosine_precision@1 | 0.9896 |
+| cosine_precision@3 | 0.3333 |
+| cosine_precision@5 | 0.2 |
+| cosine_precision@10 | 0.1 |
+| cosine_recall@1 | 0.9896 |
+| cosine_recall@3 | 1.0 |
+| cosine_recall@5 | 1.0 |
+| cosine_recall@10 | 1.0 |
+| cosine_ndcg@10 | 0.9962 |
+| cosine_mrr@10 | 0.9948 |
+| **cosine_map@100** | **0.9948** |
+| dot_accuracy@1 | 0.9896 |
+| dot_accuracy@3 | 1.0 |
+| dot_accuracy@5 | 1.0 |
+| dot_precision@1 | 0.9896 |
+| dot_precision@3 | 0.3333 |
+| dot_precision@5 | 0.2 |
+| dot_precision@10 | 0.1 |
+| dot_recall@1 | 0.9896 |
+| dot_recall@3 | 1.0 |
+| dot_recall@5 | 1.0 |
+| dot_recall@10 | 1.0 |
+| dot_ndcg@10 | 0.9962 |
+| dot_mrr@10 | 0.9948 |
+| dot_map@100 | 0.9948 |
+
+
+
+
+
+## Training Details
+
+### Training Dataset
+
+#### Unnamed Dataset
+
+
+* Size: 1,630 training samples
+* Columns: sentence_0 and sentence_1
+* Approximate statistics based on the first 1000 samples:
+ | | sentence_0 | sentence_1 |
+ |:--------|:---------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|
+ | type | string | string |
+ | details | - min: 3 tokens
- mean: 12.4 tokens
- max: 74 tokens
| - min: 7 tokens
- mean: 61.91 tokens
- max: 371 tokens
|
+* Samples:
+ | sentence_0 | sentence_1 |
+ |:-------------------------------------------------------------------------------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------------------------------------------------------------------------|
+ | Не отображается вкладка премия в ЛК. В консультации написали, что личный кабинет не передан на обслуживание в сервисную функцию HR Поддержку X5 | Создайте, пожалуйста, обращение в ИТ поддержку на портале support |
+ | как пересмотреть зарплату? | По данному вопросу Вы можете обратиться в кадровую службу, создав заявку "Консультация по HR вопросам" |
+ | поменять телефон сотруднику | Кнопка "изменить номер" телефона находится в личном разделе в ЛК. Если доступа к ЛК нет, для смены номера телефона, обратитесь в поддержку |
+* Loss: [MultipleNegativesRankingLoss](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#multiplenegativesrankingloss) with these parameters:
+ ```json
+ {
+ "scale": 20.0,
+ "similarity_fct": "cos_sim"
+ }
+ ```
+
+### Training Hyperparameters
+#### Non-Default Hyperparameters
+
+- `eval_strategy`: steps
+- `per_device_train_batch_size`: 512
+- `per_device_eval_batch_size`: 512
+- `num_train_epochs`: 1200
+- `multi_dataset_batch_sampler`: round_robin
+
+#### All Hyperparameters
+Click to expand
+
+- `overwrite_output_dir`: False
+- `do_predict`: False
+- `eval_strategy`: steps
+- `prediction_loss_only`: True
+- `per_device_train_batch_size`: 512
+- `per_device_eval_batch_size`: 512
+- `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`: 5e-05
+- `weight_decay`: 0.0
+- `adam_beta1`: 0.9
+- `adam_beta2`: 0.999
+- `adam_epsilon`: 1e-08
+- `max_grad_norm`: 1
+- `num_train_epochs`: 1200
+- `max_steps`: -1
+- `lr_scheduler_type`: linear
+- `lr_scheduler_kwargs`: {}
+- `warmup_ratio`: 0.0
+- `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`: False
+- `dataloader_num_workers`: 0
+- `dataloader_prefetch_factor`: None
+- `past_index`: -1
+- `disable_tqdm`: False
+- `remove_unused_columns`: True
+- `label_names`: None
+- `load_best_model_at_end`: False
+- `ignore_data_skip`: False
+- `fsdp`: []
+- `fsdp_min_num_params`: 0
+- `fsdp_config`: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}
+- `fsdp_transformer_layer_cls_to_wrap`: None
+- `accelerator_config`: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None}
+- `deepspeed`: None
+- `label_smoothing_factor`: 0.0
+- `optim`: adamw_torch
+- `optim_args`: None
+- `adafactor`: False
+- `group_by_length`: False
+- `length_column_name`: length
+- `ddp_find_unused_parameters`: None
+- `ddp_bucket_cap_mb`: None
+- `ddp_broadcast_buffers`: False
+- `dataloader_pin_memory`: True
+- `dataloader_persistent_workers`: False
+- `skip_memory_metrics`: True
+- `use_legacy_prediction_loop`: False
+- `push_to_hub`: False
+- `resume_from_checkpoint`: None
+- `hub_model_id`: None
+- `hub_strategy`: every_save
+- `hub_private_repo`: False
+- `hub_always_push`: False
+- `gradient_checkpointing`: False
+- `gradient_checkpointing_kwargs`: None
+- `include_inputs_for_metrics`: False
+- `eval_do_concat_batches`: True
+- `fp16_backend`: auto
+- `push_to_hub_model_id`: None
+- `push_to_hub_organization`: None
+- `mp_parameters`:
+- `auto_find_batch_size`: False
+- `full_determinism`: False
+- `torchdynamo`: None
+- `ray_scope`: last
+- `ddp_timeout`: 1800
+- `torch_compile`: False
+- `torch_compile_backend`: None
+- `torch_compile_mode`: None
+- `dispatch_batches`: None
+- `split_batches`: None
+- `include_tokens_per_second`: False
+- `include_num_input_tokens_seen`: False
+- `neftune_noise_alpha`: None
+- `optim_target_modules`: None
+- `batch_eval_metrics`: False
+- `eval_on_start`: False
+- `eval_use_gather_object`: False
+- `batch_sampler`: batch_sampler
+- `multi_dataset_batch_sampler`: round_robin
+
+Click to expand
+
+| Epoch | Step | Training Loss | test_cosine_map@100 |
+|:------:|:----:|:-------------:|:-------------------:|
+| 1.0 | 4 | - | 0.1922 |
+| 2.0 | 8 | - | 0.1922 |
+| 3.0 | 12 | - | 0.1925 |
+| 4.0 | 16 | - | 0.1927 |
+| 5.0 | 20 | - | 0.1929 |
+| 6.0 | 24 | - | 0.1931 |
+| 7.0 | 28 | - | 0.1934 |
+| 8.0 | 32 | - | 0.1942 |
+| 9.0 | 36 | - | 0.1951 |
+| 10.0 | 40 | - | 0.1960 |
+| 11.0 | 44 | - | 0.1977 |
+| 12.0 | 48 | - | 0.1993 |
+| 13.0 | 52 | - | 0.2011 |
+| 14.0 | 56 | - | 0.2024 |
+| 15.0 | 60 | - | 0.2042 |
+| 16.0 | 64 | - | 0.2047 |
+| 17.0 | 68 | - | 0.2064 |
+| 18.0 | 72 | - | 0.2081 |
+| 19.0 | 76 | - | 0.2106 |
+| 20.0 | 80 | - | 0.2123 |
+| 21.0 | 84 | - | 0.2132 |
+| 22.0 | 88 | - | 0.2148 |
+| 23.0 | 92 | - | 0.2173 |
+| 24.0 | 96 | - | 0.2200 |
+| 25.0 | 100 | - | 0.2216 |
+| 26.0 | 104 | - | 0.2241 |
+| 27.0 | 108 | - | 0.2262 |
+| 28.0 | 112 | - | 0.2286 |
+| 29.0 | 116 | - | 0.2317 |
+| 30.0 | 120 | - | 0.2339 |
+| 31.0 | 124 | - | 0.2353 |
+| 32.0 | 128 | - | 0.2392 |
+| 33.0 | 132 | - | 0.2421 |
+| 34.0 | 136 | - | 0.2442 |
+| 35.0 | 140 | - | 0.2469 |
+| 36.0 | 144 | - | 0.2501 |
+| 37.0 | 148 | - | 0.2543 |
+| 38.0 | 152 | - | 0.2565 |
+| 39.0 | 156 | - | 0.2603 |
+| 40.0 | 160 | - | 0.2643 |
+| 41.0 | 164 | - | 0.2668 |
+| 42.0 | 168 | - | 0.2688 |
+| 43.0 | 172 | - | 0.2711 |
+| 44.0 | 176 | - | 0.2743 |
+| 45.0 | 180 | - | 0.2767 |
+| 46.0 | 184 | - | 0.2810 |
+| 47.0 | 188 | - | 0.2838 |
+| 48.0 | 192 | - | 0.2869 |
+| 49.0 | 196 | - | 0.2896 |
+| 50.0 | 200 | - | 0.2940 |
+| 51.0 | 204 | - | 0.2972 |
+| 52.0 | 208 | - | 0.3012 |
+| 53.0 | 212 | - | 0.3053 |
+| 54.0 | 216 | - | 0.3072 |
+| 55.0 | 220 | - | 0.3097 |
+| 56.0 | 224 | - | 0.3133 |
+| 57.0 | 228 | - | 0.3171 |
+| 58.0 | 232 | - | 0.3220 |
+| 59.0 | 236 | - | 0.3249 |
+| 60.0 | 240 | - | 0.3274 |
+| 61.0 | 244 | - | 0.3304 |
+| 62.0 | 248 | - | 0.3336 |
+| 63.0 | 252 | - | 0.3357 |
+| 64.0 | 256 | - | 0.3398 |
+| 65.0 | 260 | - | 0.3438 |
+| 66.0 | 264 | - | 0.3463 |
+| 67.0 | 268 | - | 0.3498 |
+| 68.0 | 272 | - | 0.3535 |
+| 69.0 | 276 | - | 0.3580 |
+| 70.0 | 280 | - | 0.3606 |
+| 71.0 | 284 | - | 0.3634 |
+| 72.0 | 288 | - | 0.3654 |
+| 73.0 | 292 | - | 0.3679 |
+| 74.0 | 296 | - | 0.3723 |
+| 75.0 | 300 | - | 0.3750 |
+| 76.0 | 304 | - | 0.3781 |
+| 77.0 | 308 | - | 0.3810 |
+| 78.0 | 312 | - | 0.3840 |
+| 79.0 | 316 | - | 0.3871 |
+| 80.0 | 320 | - | 0.3914 |
+| 81.0 | 324 | - | 0.3958 |
+| 82.0 | 328 | - | 0.3991 |
+| 83.0 | 332 | - | 0.4025 |
+| 84.0 | 336 | - | 0.4053 |
+| 85.0 | 340 | - | 0.4091 |
+| 86.0 | 344 | - | 0.4125 |
+| 87.0 | 348 | - | 0.4148 |
+| 88.0 | 352 | - | 0.4176 |
+| 89.0 | 356 | - | 0.4212 |
+| 90.0 | 360 | - | 0.4240 |
+| 91.0 | 364 | - | 0.4277 |
+| 92.0 | 368 | - | 0.4315 |
+| 93.0 | 372 | - | 0.4338 |
+| 94.0 | 376 | - | 0.4363 |
+| 95.0 | 380 | - | 0.4392 |
+| 96.0 | 384 | - | 0.4423 |
+| 97.0 | 388 | - | 0.4460 |
+| 98.0 | 392 | - | 0.4487 |
+| 99.0 | 396 | - | 0.4526 |
+| 100.0 | 400 | - | 0.4563 |
+| 101.0 | 404 | - | 0.4597 |
+| 102.0 | 408 | - | 0.4644 |
+| 103.0 | 412 | - | 0.4678 |
+| 104.0 | 416 | - | 0.4707 |
+| 105.0 | 420 | - | 0.4750 |
+| 106.0 | 424 | - | 0.4791 |
+| 107.0 | 428 | - | 0.4820 |
+| 108.0 | 432 | - | 0.4847 |
+| 109.0 | 436 | - | 0.4895 |
+| 110.0 | 440 | - | 0.4916 |
+| 111.0 | 444 | - | 0.4961 |
+| 112.0 | 448 | - | 0.4990 |
+| 113.0 | 452 | - | 0.5032 |
+| 114.0 | 456 | - | 0.5065 |
+| 115.0 | 460 | - | 0.5093 |
+| 116.0 | 464 | - | 0.5135 |
+| 117.0 | 468 | - | 0.5175 |
+| 118.0 | 472 | - | 0.5199 |
+| 119.0 | 476 | - | 0.5243 |
+| 120.0 | 480 | - | 0.5266 |
+| 121.0 | 484 | - | 0.5297 |
+| 122.0 | 488 | - | 0.5324 |
+| 123.0 | 492 | - | 0.5353 |
+| 124.0 | 496 | - | 0.5378 |
+| 125.0 | 500 | 4.6316 | 0.5404 |
+| 126.0 | 504 | - | 0.5449 |
+| 127.0 | 508 | - | 0.5473 |
+| 128.0 | 512 | - | 0.5500 |
+| 129.0 | 516 | - | 0.5535 |
+| 130.0 | 520 | - | 0.5553 |
+| 131.0 | 524 | - | 0.5570 |
+| 132.0 | 528 | - | 0.5597 |
+| 133.0 | 532 | - | 0.5625 |
+| 134.0 | 536 | - | 0.5660 |
+| 135.0 | 540 | - | 0.5693 |
+| 136.0 | 544 | - | 0.5713 |
+| 137.0 | 548 | - | 0.5745 |
+| 138.0 | 552 | - | 0.5767 |
+| 139.0 | 556 | - | 0.5798 |
+| 140.0 | 560 | - | 0.5835 |
+| 141.0 | 564 | - | 0.5853 |
+| 142.0 | 568 | - | 0.5863 |
+| 143.0 | 572 | - | 0.5909 |
+| 144.0 | 576 | - | 0.5933 |
+| 145.0 | 580 | - | 0.5970 |
+| 146.0 | 584 | - | 0.5995 |
+| 147.0 | 588 | - | 0.6008 |
+| 148.0 | 592 | - | 0.6040 |
+| 149.0 | 596 | - | 0.6073 |
+| 150.0 | 600 | - | 0.6097 |
+| 151.0 | 604 | - | 0.6121 |
+| 152.0 | 608 | - | 0.6163 |
+| 153.0 | 612 | - | 0.6178 |
+| 154.0 | 616 | - | 0.6205 |
+| 155.0 | 620 | - | 0.6223 |
+| 156.0 | 624 | - | 0.6242 |
+| 157.0 | 628 | - | 0.6265 |
+| 158.0 | 632 | - | 0.6290 |
+| 159.0 | 636 | - | 0.6326 |
+| 160.0 | 640 | - | 0.6347 |
+| 161.0 | 644 | - | 0.6370 |
+| 162.0 | 648 | - | 0.6400 |
+| 163.0 | 652 | - | 0.6422 |
+| 164.0 | 656 | - | 0.6436 |
+| 165.0 | 660 | - | 0.6460 |
+| 166.0 | 664 | - | 0.6473 |
+| 167.0 | 668 | - | 0.6497 |
+| 168.0 | 672 | - | 0.6515 |
+| 169.0 | 676 | - | 0.6545 |
+| 170.0 | 680 | - | 0.6574 |
+| 171.0 | 684 | - | 0.6595 |
+| 172.0 | 688 | - | 0.6616 |
+| 173.0 | 692 | - | 0.6639 |
+| 174.0 | 696 | - | 0.6658 |
+| 175.0 | 700 | - | 0.6676 |
+| 176.0 | 704 | - | 0.6697 |
+| 177.0 | 708 | - | 0.6713 |
+| 178.0 | 712 | - | 0.6746 |
+| 179.0 | 716 | - | 0.6765 |
+| 180.0 | 720 | - | 0.6784 |
+| 181.0 | 724 | - | 0.6806 |
+| 182.0 | 728 | - | 0.6820 |
+| 183.0 | 732 | - | 0.6838 |
+| 184.0 | 736 | - | 0.6867 |
+| 185.0 | 740 | - | 0.6882 |
+| 186.0 | 744 | - | 0.6913 |
+| 187.0 | 748 | - | 0.6930 |
+| 188.0 | 752 | - | 0.6943 |
+| 189.0 | 756 | - | 0.6979 |
+| 190.0 | 760 | - | 0.6982 |
+| 191.0 | 764 | - | 0.7008 |
+| 192.0 | 768 | - | 0.7038 |
+| 193.0 | 772 | - | 0.7059 |
+| 194.0 | 776 | - | 0.7062 |
+| 195.0 | 780 | - | 0.7083 |
+| 196.0 | 784 | - | 0.7112 |
+| 197.0 | 788 | - | 0.7139 |
+| 198.0 | 792 | - | 0.7163 |
+| 199.0 | 796 | - | 0.7181 |
+| 200.0 | 800 | - | 0.7188 |
+| 201.0 | 804 | - | 0.7208 |
+| 202.0 | 808 | - | 0.7223 |
+| 203.0 | 812 | - | 0.7245 |
+| 204.0 | 816 | - | 0.7264 |
+| 205.0 | 820 | - | 0.7296 |
+| 206.0 | 824 | - | 0.7325 |
+| 207.0 | 828 | - | 0.7340 |
+| 208.0 | 832 | - | 0.7362 |
+| 209.0 | 836 | - | 0.7373 |
+| 210.0 | 840 | - | 0.7394 |
+| 211.0 | 844 | - | 0.7416 |
+| 212.0 | 848 | - | 0.7420 |
+| 213.0 | 852 | - | 0.7434 |
+| 214.0 | 856 | - | 0.7444 |
+| 215.0 | 860 | - | 0.7466 |
+| 216.0 | 864 | - | 0.7479 |
+| 217.0 | 868 | - | 0.7523 |
+| 218.0 | 872 | - | 0.7540 |
+| 219.0 | 876 | - | 0.7553 |
+| 220.0 | 880 | - | 0.7558 |
+| 221.0 | 884 | - | 0.7586 |
+| 222.0 | 888 | - | 0.7596 |
+| 223.0 | 892 | - | 0.7613 |
+| 224.0 | 896 | - | 0.7637 |
+| 225.0 | 900 | - | 0.7652 |
+| 226.0 | 904 | - | 0.7667 |
+| 227.0 | 908 | - | 0.7682 |
+| 228.0 | 912 | - | 0.7698 |
+| 229.0 | 916 | - | 0.7715 |
+| 230.0 | 920 | - | 0.7729 |
+| 231.0 | 924 | - | 0.7757 |
+| 232.0 | 928 | - | 0.7767 |
+| 233.0 | 932 | - | 0.7783 |
+| 234.0 | 936 | - | 0.7802 |
+| 235.0 | 940 | - | 0.7814 |
+| 236.0 | 944 | - | 0.7835 |
+| 237.0 | 948 | - | 0.7859 |
+| 238.0 | 952 | - | 0.7874 |
+| 239.0 | 956 | - | 0.7887 |
+| 240.0 | 960 | - | 0.7903 |
+| 241.0 | 964 | - | 0.7927 |
+| 242.0 | 968 | - | 0.7940 |
+| 243.0 | 972 | - | 0.7958 |
+| 244.0 | 976 | - | 0.7973 |
+| 245.0 | 980 | - | 0.7991 |
+| 246.0 | 984 | - | 0.8009 |
+| 247.0 | 988 | - | 0.8021 |
+| 248.0 | 992 | - | 0.8035 |
+| 249.0 | 996 | - | 0.8043 |
+| 250.0 | 1000 | 3.2323 | 0.8057 |
+| 251.0 | 1004 | - | 0.8071 |
+| 252.0 | 1008 | - | 0.8088 |
+| 253.0 | 1012 | - | 0.8104 |
+| 254.0 | 1016 | - | 0.8112 |
+| 255.0 | 1020 | - | 0.8123 |
+| 256.0 | 1024 | - | 0.8135 |
+| 257.0 | 1028 | - | 0.8154 |
+| 258.0 | 1032 | - | 0.8167 |
+| 259.0 | 1036 | - | 0.8174 |
+| 260.0 | 1040 | - | 0.8187 |
+| 261.0 | 1044 | - | 0.8187 |
+| 262.0 | 1048 | - | 0.8210 |
+| 263.0 | 1052 | - | 0.8216 |
+| 264.0 | 1056 | - | 0.8242 |
+| 265.0 | 1060 | - | 0.8260 |
+| 266.0 | 1064 | - | 0.8267 |
+| 267.0 | 1068 | - | 0.8278 |
+| 268.0 | 1072 | - | 0.8294 |
+| 269.0 | 1076 | - | 0.8309 |
+| 270.0 | 1080 | - | 0.8319 |
+| 271.0 | 1084 | - | 0.8325 |
+| 272.0 | 1088 | - | 0.8346 |
+| 273.0 | 1092 | - | 0.8353 |
+| 274.0 | 1096 | - | 0.8362 |
+| 275.0 | 1100 | - | 0.8373 |
+| 276.0 | 1104 | - | 0.8385 |
+| 277.0 | 1108 | - | 0.8392 |
+| 278.0 | 1112 | - | 0.8405 |
+| 279.0 | 1116 | - | 0.8431 |
+| 280.0 | 1120 | - | 0.8453 |
+| 281.0 | 1124 | - | 0.8464 |
+| 282.0 | 1128 | - | 0.8480 |
+| 283.0 | 1132 | - | 0.8476 |
+| 284.0 | 1136 | - | 0.8491 |
+| 285.0 | 1140 | - | 0.8509 |
+| 286.0 | 1144 | - | 0.8508 |
+| 287.0 | 1148 | - | 0.8513 |
+| 288.0 | 1152 | - | 0.8525 |
+| 289.0 | 1156 | - | 0.8534 |
+| 290.0 | 1160 | - | 0.8543 |
+| 291.0 | 1164 | - | 0.8554 |
+| 292.0 | 1168 | - | 0.8572 |
+| 293.0 | 1172 | - | 0.8590 |
+| 1.0 | 4 | - | 0.8591 |
+| 2.0 | 8 | - | 0.8591 |
+| 3.0 | 12 | - | 0.8591 |
+| 4.0 | 16 | - | 0.8591 |
+| 5.0 | 20 | - | 0.8591 |
+| 6.0 | 24 | - | 0.8591 |
+| 7.0 | 28 | - | 0.8592 |
+| 8.0 | 32 | - | 0.8592 |
+| 9.0 | 36 | - | 0.8589 |
+| 10.0 | 40 | - | 0.8593 |
+| 11.0 | 44 | - | 0.8587 |
+| 12.0 | 48 | - | 0.8590 |
+| 13.0 | 52 | - | 0.8591 |
+| 14.0 | 56 | - | 0.8591 |
+| 15.0 | 60 | - | 0.8593 |
+| 16.0 | 64 | - | 0.8593 |
+| 17.0 | 68 | - | 0.8595 |
+| 18.0 | 72 | - | 0.8598 |
+| 19.0 | 76 | - | 0.8602 |
+| 20.0 | 80 | - | 0.8606 |
+| 21.0 | 84 | - | 0.8614 |
+| 22.0 | 88 | - | 0.8617 |
+| 23.0 | 92 | - | 0.8617 |
+| 24.0 | 96 | - | 0.8621 |
+| 25.0 | 100 | - | 0.8622 |
+| 26.0 | 104 | - | 0.8626 |
+| 27.0 | 108 | - | 0.8626 |
+| 28.0 | 112 | - | 0.8626 |
+| 29.0 | 116 | - | 0.8629 |
+| 30.0 | 120 | - | 0.8629 |
+| 31.0 | 124 | - | 0.8629 |
+| 32.0 | 128 | - | 0.8629 |
+| 33.0 | 132 | - | 0.8628 |
+| 34.0 | 136 | - | 0.8625 |
+| 35.0 | 140 | - | 0.8626 |
+| 36.0 | 144 | - | 0.8628 |
+| 37.0 | 148 | - | 0.8628 |
+| 38.0 | 152 | - | 0.8630 |
+| 39.0 | 156 | - | 0.8635 |
+| 40.0 | 160 | - | 0.8635 |
+| 41.0 | 164 | - | 0.8642 |
+| 42.0 | 168 | - | 0.8646 |
+| 43.0 | 172 | - | 0.8649 |
+| 44.0 | 176 | - | 0.8654 |
+| 45.0 | 180 | - | 0.8658 |
+| 46.0 | 184 | - | 0.8662 |
+| 47.0 | 188 | - | 0.8666 |
+| 48.0 | 192 | - | 0.8676 |
+| 49.0 | 196 | - | 0.8676 |
+| 50.0 | 200 | - | 0.8677 |
+| 51.0 | 204 | - | 0.8681 |
+| 52.0 | 208 | - | 0.8680 |
+| 53.0 | 212 | - | 0.8677 |
+| 54.0 | 216 | - | 0.8682 |
+| 55.0 | 220 | - | 0.8683 |
+| 56.0 | 224 | - | 0.8687 |
+| 57.0 | 228 | - | 0.8687 |
+| 58.0 | 232 | - | 0.8687 |
+| 59.0 | 236 | - | 0.8689 |
+| 60.0 | 240 | - | 0.8690 |
+| 61.0 | 244 | - | 0.8697 |
+| 62.0 | 248 | - | 0.8700 |
+| 63.0 | 252 | - | 0.8706 |
+| 64.0 | 256 | - | 0.8706 |
+| 65.0 | 260 | - | 0.8709 |
+| 66.0 | 264 | - | 0.8711 |
+| 67.0 | 268 | - | 0.8711 |
+| 68.0 | 272 | - | 0.8716 |
+| 69.0 | 276 | - | 0.8717 |
+| 70.0 | 280 | - | 0.8728 |
+| 71.0 | 284 | - | 0.8728 |
+| 72.0 | 288 | - | 0.8729 |
+| 73.0 | 292 | - | 0.8732 |
+| 74.0 | 296 | - | 0.8734 |
+| 75.0 | 300 | - | 0.8741 |
+| 76.0 | 304 | - | 0.8736 |
+| 77.0 | 308 | - | 0.8739 |
+| 78.0 | 312 | - | 0.8742 |
+| 79.0 | 316 | - | 0.8743 |
+| 80.0 | 320 | - | 0.8744 |
+| 81.0 | 324 | - | 0.8749 |
+| 82.0 | 328 | - | 0.8750 |
+| 83.0 | 332 | - | 0.8760 |
+| 84.0 | 336 | - | 0.8758 |
+| 85.0 | 340 | - | 0.8765 |
+| 86.0 | 344 | - | 0.8771 |
+| 87.0 | 348 | - | 0.8771 |
+| 88.0 | 352 | - | 0.8768 |
+| 89.0 | 356 | - | 0.8778 |
+| 90.0 | 360 | - | 0.8778 |
+| 91.0 | 364 | - | 0.8784 |
+| 92.0 | 368 | - | 0.8793 |
+| 93.0 | 372 | - | 0.8795 |
+| 94.0 | 376 | - | 0.8796 |
+| 95.0 | 380 | - | 0.8801 |
+| 96.0 | 384 | - | 0.8803 |
+| 97.0 | 388 | - | 0.8806 |
+| 98.0 | 392 | - | 0.8811 |
+| 99.0 | 396 | - | 0.8815 |
+| 100.0 | 400 | - | 0.8814 |
+| 101.0 | 404 | - | 0.8822 |
+| 102.0 | 408 | - | 0.8829 |
+| 103.0 | 412 | - | 0.8827 |
+| 104.0 | 416 | - | 0.8827 |
+| 105.0 | 420 | - | 0.8838 |
+| 106.0 | 424 | - | 0.8836 |
+| 107.0 | 428 | - | 0.8841 |
+| 108.0 | 432 | - | 0.8848 |
+| 109.0 | 436 | - | 0.8853 |
+| 110.0 | 440 | - | 0.8857 |
+| 111.0 | 444 | - | 0.8858 |
+| 112.0 | 448 | - | 0.8863 |
+| 113.0 | 452 | - | 0.8868 |
+| 114.0 | 456 | - | 0.8877 |
+| 115.0 | 460 | - | 0.8887 |
+| 116.0 | 464 | - | 0.8887 |
+| 117.0 | 468 | - | 0.8883 |
+| 118.0 | 472 | - | 0.8883 |
+| 119.0 | 476 | - | 0.8887 |
+| 120.0 | 480 | - | 0.8888 |
+| 121.0 | 484 | - | 0.8902 |
+| 122.0 | 488 | - | 0.8900 |
+| 123.0 | 492 | - | 0.8906 |
+| 124.0 | 496 | - | 0.8908 |
+| 125.0 | 500 | 2.6383 | 0.8909 |
+| 126.0 | 504 | - | 0.8913 |
+| 127.0 | 508 | - | 0.8917 |
+| 128.0 | 512 | - | 0.8922 |
+| 129.0 | 516 | - | 0.8923 |
+| 130.0 | 520 | - | 0.8924 |
+| 131.0 | 524 | - | 0.8924 |
+| 132.0 | 528 | - | 0.8927 |
+| 133.0 | 532 | - | 0.8925 |
+| 134.0 | 536 | - | 0.8931 |
+| 135.0 | 540 | - | 0.8941 |
+| 136.0 | 544 | - | 0.8953 |
+| 137.0 | 548 | - | 0.8957 |
+| 138.0 | 552 | - | 0.8966 |
+| 139.0 | 556 | - | 0.8980 |
+| 140.0 | 560 | - | 0.8985 |
+| 141.0 | 564 | - | 0.8979 |
+| 142.0 | 568 | - | 0.8993 |
+| 143.0 | 572 | - | 0.8987 |
+| 144.0 | 576 | - | 0.8998 |
+| 145.0 | 580 | - | 0.8994 |
+| 146.0 | 584 | - | 0.9002 |
+| 147.0 | 588 | - | 0.9006 |
+| 148.0 | 592 | - | 0.9016 |
+| 149.0 | 596 | - | 0.9025 |
+| 150.0 | 600 | - | 0.9026 |
+| 151.0 | 604 | - | 0.9030 |
+| 152.0 | 608 | - | 0.9035 |
+| 153.0 | 612 | - | 0.9043 |
+| 154.0 | 616 | - | 0.9050 |
+| 155.0 | 620 | - | 0.9060 |
+| 156.0 | 624 | - | 0.9060 |
+| 157.0 | 628 | - | 0.9067 |
+| 158.0 | 632 | - | 0.9062 |
+| 159.0 | 636 | - | 0.9065 |
+| 160.0 | 640 | - | 0.9083 |
+| 161.0 | 644 | - | 0.9085 |
+| 162.0 | 648 | - | 0.9090 |
+| 163.0 | 652 | - | 0.9093 |
+| 164.0 | 656 | - | 0.9098 |
+| 165.0 | 660 | - | 0.9101 |
+| 166.0 | 664 | - | 0.9104 |
+| 167.0 | 668 | - | 0.9111 |
+| 168.0 | 672 | - | 0.9121 |
+| 169.0 | 676 | - | 0.9123 |
+| 170.0 | 680 | - | 0.9130 |
+| 171.0 | 684 | - | 0.9134 |
+| 172.0 | 688 | - | 0.9135 |
+| 173.0 | 692 | - | 0.9139 |
+| 174.0 | 696 | - | 0.9145 |
+| 175.0 | 700 | - | 0.9143 |
+| 176.0 | 704 | - | 0.9146 |
+| 177.0 | 708 | - | 0.9155 |
+| 178.0 | 712 | - | 0.9164 |
+| 179.0 | 716 | - | 0.9185 |
+| 180.0 | 720 | - | 0.9192 |
+| 181.0 | 724 | - | 0.9192 |
+| 182.0 | 728 | - | 0.9192 |
+| 183.0 | 732 | - | 0.9205 |
+| 184.0 | 736 | - | 0.9208 |
+| 185.0 | 740 | - | 0.9210 |
+| 186.0 | 744 | - | 0.9216 |
+| 187.0 | 748 | - | 0.9216 |
+| 188.0 | 752 | - | 0.9219 |
+| 189.0 | 756 | - | 0.9218 |
+| 190.0 | 760 | - | 0.9221 |
+| 191.0 | 764 | - | 0.9233 |
+| 192.0 | 768 | - | 0.9240 |
+| 193.0 | 772 | - | 0.9253 |
+| 194.0 | 776 | - | 0.9255 |
+| 195.0 | 780 | - | 0.9256 |
+| 196.0 | 784 | - | 0.9259 |
+| 197.0 | 788 | - | 0.9260 |
+| 198.0 | 792 | - | 0.9268 |
+| 199.0 | 796 | - | 0.9271 |
+| 200.0 | 800 | - | 0.9271 |
+| 201.0 | 804 | - | 0.9273 |
+| 202.0 | 808 | - | 0.9282 |
+| 203.0 | 812 | - | 0.9280 |
+| 204.0 | 816 | - | 0.9278 |
+| 205.0 | 820 | - | 0.9290 |
+| 206.0 | 824 | - | 0.9294 |
+| 207.0 | 828 | - | 0.9302 |
+| 208.0 | 832 | - | 0.9307 |
+| 209.0 | 836 | - | 0.9304 |
+| 210.0 | 840 | - | 0.9304 |
+| 211.0 | 844 | - | 0.9316 |
+| 212.0 | 848 | - | 0.9320 |
+| 213.0 | 852 | - | 0.9325 |
+| 214.0 | 856 | - | 0.9332 |
+| 215.0 | 860 | - | 0.9335 |
+| 216.0 | 864 | - | 0.9348 |
+| 217.0 | 868 | - | 0.9359 |
+| 218.0 | 872 | - | 0.9362 |
+| 219.0 | 876 | - | 0.9362 |
+| 220.0 | 880 | - | 0.9362 |
+| 221.0 | 884 | - | 0.9362 |
+| 222.0 | 888 | - | 0.9363 |
+| 223.0 | 892 | - | 0.9368 |
+| 224.0 | 896 | - | 0.9374 |
+| 225.0 | 900 | - | 0.9381 |
+| 226.0 | 904 | - | 0.9378 |
+| 227.0 | 908 | - | 0.9378 |
+| 228.0 | 912 | - | 0.9376 |
+| 229.0 | 916 | - | 0.9373 |
+| 230.0 | 920 | - | 0.9380 |
+| 231.0 | 924 | - | 0.9381 |
+| 232.0 | 928 | - | 0.9386 |
+| 233.0 | 932 | - | 0.9399 |
+| 234.0 | 936 | - | 0.9404 |
+| 235.0 | 940 | - | 0.9402 |
+| 236.0 | 944 | - | 0.9406 |
+| 237.0 | 948 | - | 0.9406 |
+| 238.0 | 952 | - | 0.9404 |
+| 239.0 | 956 | - | 0.9410 |
+| 240.0 | 960 | - | 0.9412 |
+| 241.0 | 964 | - | 0.9412 |
+| 242.0 | 968 | - | 0.9423 |
+| 243.0 | 972 | - | 0.9429 |
+| 244.0 | 976 | - | 0.9429 |
+| 245.0 | 980 | - | 0.9432 |
+| 246.0 | 984 | - | 0.9432 |
+| 247.0 | 988 | - | 0.9439 |
+| 248.0 | 992 | - | 0.9449 |
+| 249.0 | 996 | - | 0.9452 |
+| 250.0 | 1000 | 2.507 | 0.9461 |
+| 251.0 | 1004 | - | 0.9464 |
+| 252.0 | 1008 | - | 0.9464 |
+| 253.0 | 1012 | - | 0.9460 |
+| 254.0 | 1016 | - | 0.9456 |
+| 255.0 | 1020 | - | 0.9471 |
+| 256.0 | 1024 | - | 0.9468 |
+| 257.0 | 1028 | - | 0.9472 |
+| 258.0 | 1032 | - | 0.9476 |
+| 259.0 | 1036 | - | 0.9481 |
+| 260.0 | 1040 | - | 0.9490 |
+| 261.0 | 1044 | - | 0.9488 |
+| 262.0 | 1048 | - | 0.9488 |
+| 263.0 | 1052 | - | 0.9478 |
+| 264.0 | 1056 | - | 0.9475 |
+| 265.0 | 1060 | - | 0.9485 |
+| 266.0 | 1064 | - | 0.9490 |
+| 267.0 | 1068 | - | 0.9487 |
+| 268.0 | 1072 | - | 0.9484 |
+| 269.0 | 1076 | - | 0.9490 |
+| 270.0 | 1080 | - | 0.9495 |
+| 271.0 | 1084 | - | 0.9506 |
+| 272.0 | 1088 | - | 0.9513 |
+| 273.0 | 1092 | - | 0.9518 |
+| 274.0 | 1096 | - | 0.9522 |
+| 275.0 | 1100 | - | 0.9526 |
+| 276.0 | 1104 | - | 0.9522 |
+| 277.0 | 1108 | - | 0.9526 |
+| 278.0 | 1112 | - | 0.9531 |
+| 279.0 | 1116 | - | 0.9537 |
+| 280.0 | 1120 | - | 0.9533 |
+| 281.0 | 1124 | - | 0.9523 |
+| 282.0 | 1128 | - | 0.9544 |
+| 283.0 | 1132 | - | 0.9546 |
+| 284.0 | 1136 | - | 0.9553 |
+| 285.0 | 1140 | - | 0.9554 |
+| 286.0 | 1144 | - | 0.9565 |
+| 287.0 | 1148 | - | 0.9568 |
+| 288.0 | 1152 | - | 0.9569 |
+| 289.0 | 1156 | - | 0.9569 |
+| 290.0 | 1160 | - | 0.9567 |
+| 291.0 | 1164 | - | 0.9568 |
+| 292.0 | 1168 | - | 0.9574 |
+| 293.0 | 1172 | - | 0.9574 |
+| 294.0 | 1176 | - | 0.9574 |
+| 295.0 | 1180 | - | 0.9580 |
+| 296.0 | 1184 | - | 0.9586 |
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+| 298.0 | 1192 | - | 0.9594 |
+| 299.0 | 1196 | - | 0.9596 |
+| 300.0 | 1200 | - | 0.9602 |
+| 301.0 | 1204 | - | 0.9604 |
+| 302.0 | 1208 | - | 0.9598 |
+| 303.0 | 1212 | - | 0.9605 |
+| 304.0 | 1216 | - | 0.9608 |
+| 305.0 | 1220 | - | 0.9614 |
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+| 307.0 | 1228 | - | 0.9621 |
+| 308.0 | 1232 | - | 0.9630 |
+| 309.0 | 1236 | - | 0.9633 |
+| 310.0 | 1240 | - | 0.9644 |
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+| 314.0 | 1256 | - | 0.9644 |
+| 315.0 | 1260 | - | 0.9646 |
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+| 317.0 | 1268 | - | 0.9665 |
+| 318.0 | 1272 | - | 0.9664 |
+| 319.0 | 1276 | - | 0.9666 |
+| 320.0 | 1280 | - | 0.9673 |
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+| 322.0 | 1288 | - | 0.9681 |
+| 323.0 | 1292 | - | 0.9684 |
+| 324.0 | 1296 | - | 0.9685 |
+| 325.0 | 1300 | - | 0.9686 |
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+| 328.0 | 1312 | - | 0.9684 |
+| 329.0 | 1316 | - | 0.9685 |
+| 330.0 | 1320 | - | 0.9688 |
+| 331.0 | 1324 | - | 0.9690 |
+| 332.0 | 1328 | - | 0.9691 |
+| 333.0 | 1332 | - | 0.9695 |
+| 334.0 | 1336 | - | 0.9701 |
+| 335.0 | 1340 | - | 0.9714 |
+| 336.0 | 1344 | - | 0.9713 |
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+| 339.0 | 1356 | - | 0.9720 |
+| 340.0 | 1360 | - | 0.9720 |
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+| 342.0 | 1368 | - | 0.9725 |
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+| 344.0 | 1376 | - | 0.9725 |
+| 345.0 | 1380 | - | 0.9723 |
+| 346.0 | 1384 | - | 0.9727 |
+| 347.0 | 1388 | - | 0.9723 |
+| 348.0 | 1392 | - | 0.9729 |
+| 349.0 | 1396 | - | 0.9735 |
+| 350.0 | 1400 | - | 0.9735 |
+| 351.0 | 1404 | - | 0.9732 |
+| 352.0 | 1408 | - | 0.9739 |
+| 353.0 | 1412 | - | 0.9742 |
+| 354.0 | 1416 | - | 0.9747 |
+| 355.0 | 1420 | - | 0.9744 |
+| 356.0 | 1424 | - | 0.9744 |
+| 357.0 | 1428 | - | 0.9744 |
+| 358.0 | 1432 | - | 0.9743 |
+| 359.0 | 1436 | - | 0.9740 |
+| 360.0 | 1440 | - | 0.9742 |
+| 361.0 | 1444 | - | 0.9739 |
+| 362.0 | 1448 | - | 0.9736 |
+| 363.0 | 1452 | - | 0.9746 |
+| 364.0 | 1456 | - | 0.9752 |
+| 365.0 | 1460 | - | 0.9752 |
+| 366.0 | 1464 | - | 0.9752 |
+| 367.0 | 1468 | - | 0.9748 |
+| 368.0 | 1472 | - | 0.9748 |
+| 369.0 | 1476 | - | 0.9749 |
+| 370.0 | 1480 | - | 0.9755 |
+| 371.0 | 1484 | - | 0.9753 |
+| 372.0 | 1488 | - | 0.9759 |
+| 373.0 | 1492 | - | 0.9760 |
+| 374.0 | 1496 | - | 0.9755 |
+| 375.0 | 1500 | 2.391 | 0.9755 |
+| 376.0 | 1504 | - | 0.9757 |
+| 377.0 | 1508 | - | 0.9757 |
+| 378.0 | 1512 | - | 0.9760 |
+| 379.0 | 1516 | - | 0.9762 |
+| 380.0 | 1520 | - | 0.9760 |
+| 381.0 | 1524 | - | 0.9762 |
+| 382.0 | 1528 | - | 0.9761 |
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+| 384.0 | 1536 | - | 0.9770 |
+| 385.0 | 1540 | - | 0.9774 |
+| 386.0 | 1544 | - | 0.9777 |
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+| 388.0 | 1552 | - | 0.9774 |
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+| 390.0 | 1560 | - | 0.9780 |
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+| 395.0 | 1580 | - | 0.9783 |
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+| 399.0 | 1596 | - | 0.9788 |
+| 400.0 | 1600 | - | 0.9782 |
+| 401.0 | 1604 | - | 0.9782 |
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+| 403.0 | 1612 | - | 0.9782 |
+| 404.0 | 1616 | - | 0.9788 |
+| 405.0 | 1620 | - | 0.9789 |
+| 406.0 | 1624 | - | 0.9789 |
+| 407.0 | 1628 | - | 0.9793 |
+| 408.0 | 1632 | - | 0.9794 |
+| 409.0 | 1636 | - | 0.9797 |
+| 410.0 | 1640 | - | 0.9803 |
+| 411.0 | 1644 | - | 0.9800 |
+| 412.0 | 1648 | - | 0.9796 |
+| 413.0 | 1652 | - | 0.9799 |
+| 414.0 | 1656 | - | 0.9799 |
+| 415.0 | 1660 | - | 0.9796 |
+| 416.0 | 1664 | - | 0.9797 |
+| 417.0 | 1668 | - | 0.9797 |
+| 418.0 | 1672 | - | 0.9800 |
+| 419.0 | 1676 | - | 0.9803 |
+| 420.0 | 1680 | - | 0.9809 |
+| 421.0 | 1684 | - | 0.9806 |
+| 422.0 | 1688 | - | 0.9809 |
+| 423.0 | 1692 | - | 0.9812 |
+| 424.0 | 1696 | - | 0.9810 |
+| 425.0 | 1700 | - | 0.9806 |
+| 426.0 | 1704 | - | 0.9806 |
+| 427.0 | 1708 | - | 0.9799 |
+| 428.0 | 1712 | - | 0.9796 |
+| 429.0 | 1716 | - | 0.9802 |
+| 430.0 | 1720 | - | 0.9802 |
+| 431.0 | 1724 | - | 0.9810 |
+| 432.0 | 1728 | - | 0.9810 |
+| 433.0 | 1732 | - | 0.9807 |
+| 434.0 | 1736 | - | 0.9810 |
+| 435.0 | 1740 | - | 0.9813 |
+| 436.0 | 1744 | - | 0.9816 |
+| 437.0 | 1748 | - | 0.9820 |
+| 438.0 | 1752 | - | 0.9816 |
+| 439.0 | 1756 | - | 0.9816 |
+| 440.0 | 1760 | - | 0.9813 |
+| 441.0 | 1764 | - | 0.9820 |
+| 442.0 | 1768 | - | 0.9823 |
+| 443.0 | 1772 | - | 0.9820 |
+| 444.0 | 1776 | - | 0.9823 |
+| 445.0 | 1780 | - | 0.9826 |
+| 446.0 | 1784 | - | 0.9823 |
+| 447.0 | 1788 | - | 0.9832 |
+| 448.0 | 1792 | - | 0.9832 |
+| 449.0 | 1796 | - | 0.9832 |
+| 450.0 | 1800 | - | 0.9835 |
+| 451.0 | 1804 | - | 0.9835 |
+| 452.0 | 1808 | - | 0.9835 |
+| 453.0 | 1812 | - | 0.9835 |
+| 454.0 | 1816 | - | 0.9835 |
+| 455.0 | 1820 | - | 0.9835 |
+| 456.0 | 1824 | - | 0.9838 |
+| 457.0 | 1828 | - | 0.9838 |
+| 458.0 | 1832 | - | 0.9841 |
+| 459.0 | 1836 | - | 0.9841 |
+| 460.0 | 1840 | - | 0.9841 |
+| 461.0 | 1844 | - | 0.9841 |
+| 462.0 | 1848 | - | 0.9844 |
+| 463.0 | 1852 | - | 0.9850 |
+| 464.0 | 1856 | - | 0.9844 |
+| 465.0 | 1860 | - | 0.9841 |
+| 466.0 | 1864 | - | 0.9844 |
+| 467.0 | 1868 | - | 0.9850 |
+| 468.0 | 1872 | - | 0.9853 |
+| 469.0 | 1876 | - | 0.9850 |
+| 470.0 | 1880 | - | 0.9856 |
+| 471.0 | 1884 | - | 0.9856 |
+| 472.0 | 1888 | - | 0.9856 |
+| 473.0 | 1892 | - | 0.9853 |
+| 474.0 | 1896 | - | 0.9856 |
+| 475.0 | 1900 | - | 0.9850 |
+| 476.0 | 1904 | - | 0.9850 |
+| 477.0 | 1908 | - | 0.9850 |
+| 478.0 | 1912 | - | 0.9850 |
+| 479.0 | 1916 | - | 0.9853 |
+| 480.0 | 1920 | - | 0.9856 |
+| 481.0 | 1924 | - | 0.9859 |
+| 482.0 | 1928 | - | 0.9862 |
+| 483.0 | 1932 | - | 0.9862 |
+| 484.0 | 1936 | - | 0.9862 |
+| 485.0 | 1940 | - | 0.9862 |
+| 486.0 | 1944 | - | 0.9859 |
+| 487.0 | 1948 | - | 0.9859 |
+| 488.0 | 1952 | - | 0.9856 |
+| 489.0 | 1956 | - | 0.9859 |
+| 490.0 | 1960 | - | 0.9859 |
+| 491.0 | 1964 | - | 0.9859 |
+| 492.0 | 1968 | - | 0.9856 |
+| 493.0 | 1972 | - | 0.9856 |
+| 494.0 | 1976 | - | 0.9856 |
+| 495.0 | 1980 | - | 0.9856 |
+| 496.0 | 1984 | - | 0.9862 |
+| 497.0 | 1988 | - | 0.9862 |
+| 498.0 | 1992 | - | 0.9856 |
+| 499.0 | 1996 | - | 0.9856 |
+| 500.0 | 2000 | 2.3269 | 0.9856 |
+| 501.0 | 2004 | - | 0.9856 |
+| 502.0 | 2008 | - | 0.9856 |
+| 503.0 | 2012 | - | 0.9859 |
+| 504.0 | 2016 | - | 0.9862 |
+| 505.0 | 2020 | - | 0.9866 |
+| 506.0 | 2024 | - | 0.9866 |
+| 507.0 | 2028 | - | 0.9869 |
+| 508.0 | 2032 | - | 0.9869 |
+| 509.0 | 2036 | - | 0.9869 |
+| 510.0 | 2040 | - | 0.9875 |
+| 511.0 | 2044 | - | 0.9875 |
+| 512.0 | 2048 | - | 0.9875 |
+| 513.0 | 2052 | - | 0.9872 |
+| 514.0 | 2056 | - | 0.9872 |
+| 515.0 | 2060 | - | 0.9869 |
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+| 535.0 | 2140 | - | 0.9878 |
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+| 625.0 | 2500 | 2.2939 | 0.9907 |
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+| 628.0 | 2512 | - | 0.9907 |
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+| 1114.0 | 4456 | - | 0.9948 |
+| 1115.0 | 4460 | - | 0.9948 |
+| 1116.0 | 4464 | - | 0.9948 |
+| 1117.0 | 4468 | - | 0.9948 |
+| 1118.0 | 4472 | - | 0.9948 |
+| 1119.0 | 4476 | - | 0.9948 |
+| 1120.0 | 4480 | - | 0.9948 |
+| 1121.0 | 4484 | - | 0.9948 |
+| 1122.0 | 4488 | - | 0.9948 |
+| 1123.0 | 4492 | - | 0.9948 |
+| 1124.0 | 4496 | - | 0.9948 |
+| 1125.0 | 4500 | 2.2654 | 0.9948 |
+| 1126.0 | 4504 | - | 0.9948 |
+| 1127.0 | 4508 | - | 0.9948 |
+| 1128.0 | 4512 | - | 0.9948 |
+| 1129.0 | 4516 | - | 0.9948 |
+| 1130.0 | 4520 | - | 0.9948 |
+| 1131.0 | 4524 | - | 0.9948 |
+| 1132.0 | 4528 | - | 0.9948 |
+| 1133.0 | 4532 | - | 0.9948 |
+| 1134.0 | 4536 | - | 0.9948 |
+| 1135.0 | 4540 | - | 0.9948 |
+| 1136.0 | 4544 | - | 0.9948 |
+| 1137.0 | 4548 | - | 0.9948 |
+| 1138.0 | 4552 | - | 0.9948 |
+| 1139.0 | 4556 | - | 0.9948 |
+| 1140.0 | 4560 | - | 0.9948 |
+| 1141.0 | 4564 | - | 0.9948 |
+| 1142.0 | 4568 | - | 0.9948 |
+| 1143.0 | 4572 | - | 0.9948 |
+| 1144.0 | 4576 | - | 0.9948 |
+| 1145.0 | 4580 | - | 0.9948 |
+| 1146.0 | 4584 | - | 0.9948 |
+| 1147.0 | 4588 | - | 0.9948 |
+| 1148.0 | 4592 | - | 0.9948 |
+| 1149.0 | 4596 | - | 0.9948 |
+| 1150.0 | 4600 | - | 0.9948 |
+| 1151.0 | 4604 | - | 0.9948 |
+| 1152.0 | 4608 | - | 0.9948 |
+| 1153.0 | 4612 | - | 0.9948 |
+| 1154.0 | 4616 | - | 0.9948 |
+| 1155.0 | 4620 | - | 0.9948 |
+| 1156.0 | 4624 | - | 0.9948 |
+| 1157.0 | 4628 | - | 0.9948 |
+| 1158.0 | 4632 | - | 0.9948 |
+| 1159.0 | 4636 | - | 0.9948 |
+| 1160.0 | 4640 | - | 0.9948 |
+| 1161.0 | 4644 | - | 0.9948 |
+| 1162.0 | 4648 | - | 0.9948 |
+| 1163.0 | 4652 | - | 0.9948 |
+| 1164.0 | 4656 | - | 0.9948 |
+| 1165.0 | 4660 | - | 0.9948 |
+| 1166.0 | 4664 | - | 0.9948 |
+| 1167.0 | 4668 | - | 0.9948 |
+| 1168.0 | 4672 | - | 0.9948 |
+| 1169.0 | 4676 | - | 0.9948 |
+| 1170.0 | 4680 | - | 0.9948 |
+| 1171.0 | 4684 | - | 0.9948 |
+| 1172.0 | 4688 | - | 0.9948 |
+| 1173.0 | 4692 | - | 0.9948 |
+| 1174.0 | 4696 | - | 0.9948 |
+| 1175.0 | 4700 | - | 0.9948 |
+| 1176.0 | 4704 | - | 0.9948 |
+| 1177.0 | 4708 | - | 0.9948 |
+| 1178.0 | 4712 | - | 0.9948 |
+| 1179.0 | 4716 | - | 0.9948 |
+| 1180.0 | 4720 | - | 0.9948 |
+| 1181.0 | 4724 | - | 0.9948 |
+| 1182.0 | 4728 | - | 0.9948 |
+| 1183.0 | 4732 | - | 0.9948 |
+| 1184.0 | 4736 | - | 0.9948 |
+| 1185.0 | 4740 | - | 0.9948 |
+| 1186.0 | 4744 | - | 0.9948 |
+| 1187.0 | 4748 | - | 0.9948 |
+| 1188.0 | 4752 | - | 0.9948 |
+| 1189.0 | 4756 | - | 0.9948 |
+| 1190.0 | 4760 | - | 0.9948 |
+| 1191.0 | 4764 | - | 0.9948 |
+| 1192.0 | 4768 | - | 0.9948 |
+| 1193.0 | 4772 | - | 0.9948 |
+| 1194.0 | 4776 | - | 0.9948 |
+| 1195.0 | 4780 | - | 0.9948 |
+| 1196.0 | 4784 | - | 0.9948 |
+| 1197.0 | 4788 | - | 0.9948 |
+| 1198.0 | 4792 | - | 0.9948 |
+| 1199.0 | 4796 | - | 0.9948 |
+| 1200.0 | 4800 | - | 0.9948 |
+
+