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Add new SentenceTransformer model.
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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 на 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) <!-- at revision dad72b8f77c5eef6995dd3e4691b758ba56b90c3 -->
- **Maximum Sequence Length:** 2048 tokens
- **Output Dimensionality:** 312 tokens
- **Similarity Function:** Cosine Similarity
<!-- - **Training Dataset:** Unknown -->
<!-- - **Language:** Unknown -->
<!-- - **License:** Unknown -->
### 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]
```
<!--
### Direct Usage (Transformers)
<details><summary>Click to see the direct usage in Transformers</summary>
</details>
-->
<!--
### Downstream Usage (Sentence Transformers)
You can finetune this model on your own dataset.
<details><summary>Click to expand</summary>
</details>
-->
<!--
### Out-of-Scope Use
*List how the model may foreseeably be misused and address what users ought not to do with the model.*
-->
## Evaluation
### Metrics
#### Information Retrieval
* Dataset: `test`
* Evaluated with [<code>InformationRetrievalEvaluator</code>](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 [<code>InformationRetrievalEvaluator</code>](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 |
<!--
## Bias, Risks and Limitations
*What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.*
-->
<!--
### Recommendations
*What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*
-->
## Training Details
### Training Dataset
#### Unnamed Dataset
* Size: 1,630 training samples
* Columns: <code>sentence_0</code> and <code>sentence_1</code>
* Approximate statistics based on the first 1000 samples:
| | sentence_0 | sentence_1 |
|:--------|:---------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|
| type | string | string |
| details | <ul><li>min: 3 tokens</li><li>mean: 12.4 tokens</li><li>max: 74 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 61.91 tokens</li><li>max: 371 tokens</li></ul> |
* Samples:
| sentence_0 | sentence_1 |
|:-------------------------------------------------------------------------------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------------------------------------------------------------------------|
| <code>Не отображается вкладка премия в ЛК. В консультации написали, что личный кабинет не передан на обслуживание в сервисную функцию HR Поддержку X5</code> | <code>Создайте, пожалуйста, обращение в ИТ поддержку на портале support</code> |
| <code>как пересмотреть зарплату?</code> | <code>По данному вопросу Вы можете обратиться в кадровую службу, создав заявку "Консультация по HR вопросам"</code> |
| <code>поменять телефон сотруднику</code> | <code>Кнопка "изменить номер" телефона находится в личном разделе в ЛК. Если доступа к ЛК нет, для смены номера телефона, обратитесь в поддержку</code> |
* Loss: [<code>MultipleNegativesRankingLoss</code>](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
<details><summary>Click to expand</summary>
- `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
</details>
### Training Logs
<details><summary>Click to expand</summary>
| 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 |
| 297.0 | 1188 | - | 0.9588 |
| 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 |
| 306.0 | 1224 | - | 0.9620 |
| 307.0 | 1228 | - | 0.9621 |
| 308.0 | 1232 | - | 0.9630 |
| 309.0 | 1236 | - | 0.9633 |
| 310.0 | 1240 | - | 0.9644 |
| 311.0 | 1244 | - | 0.9644 |
| 312.0 | 1248 | - | 0.9643 |
| 313.0 | 1252 | - | 0.9644 |
| 314.0 | 1256 | - | 0.9644 |
| 315.0 | 1260 | - | 0.9646 |
| 316.0 | 1264 | - | 0.9661 |
| 317.0 | 1268 | - | 0.9665 |
| 318.0 | 1272 | - | 0.9664 |
| 319.0 | 1276 | - | 0.9666 |
| 320.0 | 1280 | - | 0.9673 |
| 321.0 | 1284 | - | 0.9681 |
| 322.0 | 1288 | - | 0.9681 |
| 323.0 | 1292 | - | 0.9684 |
| 324.0 | 1296 | - | 0.9685 |
| 325.0 | 1300 | - | 0.9686 |
| 326.0 | 1304 | - | 0.9681 |
| 327.0 | 1308 | - | 0.9686 |
| 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 |
| 337.0 | 1348 | - | 0.9719 |
| 338.0 | 1352 | - | 0.9720 |
| 339.0 | 1356 | - | 0.9720 |
| 340.0 | 1360 | - | 0.9720 |
| 341.0 | 1364 | - | 0.9720 |
| 342.0 | 1368 | - | 0.9725 |
| 343.0 | 1372 | - | 0.9728 |
| 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 |
| 383.0 | 1532 | - | 0.9761 |
| 384.0 | 1536 | - | 0.9770 |
| 385.0 | 1540 | - | 0.9774 |
| 386.0 | 1544 | - | 0.9777 |
| 387.0 | 1548 | - | 0.9780 |
| 388.0 | 1552 | - | 0.9774 |
| 389.0 | 1556 | - | 0.9768 |
| 390.0 | 1560 | - | 0.9780 |
| 391.0 | 1564 | - | 0.9789 |
| 392.0 | 1568 | - | 0.9789 |
| 393.0 | 1572 | - | 0.9786 |
| 394.0 | 1576 | - | 0.9786 |
| 395.0 | 1580 | - | 0.9783 |
| 396.0 | 1584 | - | 0.9789 |
| 397.0 | 1588 | - | 0.9790 |
| 398.0 | 1592 | - | 0.9787 |
| 399.0 | 1596 | - | 0.9788 |
| 400.0 | 1600 | - | 0.9782 |
| 401.0 | 1604 | - | 0.9782 |
| 402.0 | 1608 | - | 0.9782 |
| 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 |
| 516.0 | 2064 | - | 0.9869 |
| 517.0 | 2068 | - | 0.9866 |
| 518.0 | 2072 | - | 0.9866 |
| 519.0 | 2076 | - | 0.9862 |
| 520.0 | 2080 | - | 0.9866 |
| 521.0 | 2084 | - | 0.9866 |
| 522.0 | 2088 | - | 0.9862 |
| 523.0 | 2092 | - | 0.9866 |
| 524.0 | 2096 | - | 0.9862 |
| 525.0 | 2100 | - | 0.9866 |
| 526.0 | 2104 | - | 0.9872 |
| 527.0 | 2108 | - | 0.9878 |
| 528.0 | 2112 | - | 0.9878 |
| 529.0 | 2116 | - | 0.9881 |
| 530.0 | 2120 | - | 0.9881 |
| 531.0 | 2124 | - | 0.9881 |
| 532.0 | 2128 | - | 0.9878 |
| 533.0 | 2132 | - | 0.9878 |
| 534.0 | 2136 | - | 0.9878 |
| 535.0 | 2140 | - | 0.9878 |
| 536.0 | 2144 | - | 0.9875 |
| 537.0 | 2148 | - | 0.9878 |
| 538.0 | 2152 | - | 0.9872 |
| 539.0 | 2156 | - | 0.9869 |
| 540.0 | 2160 | - | 0.9872 |
| 541.0 | 2164 | - | 0.9875 |
| 542.0 | 2168 | - | 0.9878 |
| 543.0 | 2172 | - | 0.9878 |
| 544.0 | 2176 | - | 0.9881 |
| 545.0 | 2180 | - | 0.9888 |
| 546.0 | 2184 | - | 0.9894 |
| 547.0 | 2188 | - | 0.9894 |
| 548.0 | 2192 | - | 0.9897 |
| 549.0 | 2196 | - | 0.9897 |
| 550.0 | 2200 | - | 0.9897 |
| 551.0 | 2204 | - | 0.9897 |
| 552.0 | 2208 | - | 0.9897 |
| 553.0 | 2212 | - | 0.9894 |
| 554.0 | 2216 | - | 0.9891 |
| 555.0 | 2220 | - | 0.9888 |
| 556.0 | 2224 | - | 0.9884 |
| 557.0 | 2228 | - | 0.9884 |
| 558.0 | 2232 | - | 0.9884 |
| 559.0 | 2236 | - | 0.9888 |
| 560.0 | 2240 | - | 0.9891 |
| 561.0 | 2244 | - | 0.9891 |
| 562.0 | 2248 | - | 0.9894 |
| 563.0 | 2252 | - | 0.9897 |
| 564.0 | 2256 | - | 0.9897 |
| 565.0 | 2260 | - | 0.9897 |
| 566.0 | 2264 | - | 0.9900 |
| 567.0 | 2268 | - | 0.9903 |
| 568.0 | 2272 | - | 0.9900 |
| 569.0 | 2276 | - | 0.9903 |
| 570.0 | 2280 | - | 0.9900 |
| 571.0 | 2284 | - | 0.9900 |
| 572.0 | 2288 | - | 0.9900 |
| 573.0 | 2292 | - | 0.9900 |
| 574.0 | 2296 | - | 0.9903 |
| 575.0 | 2300 | - | 0.9903 |
| 576.0 | 2304 | - | 0.9903 |
| 577.0 | 2308 | - | 0.9903 |
| 578.0 | 2312 | - | 0.9903 |
| 579.0 | 2316 | - | 0.9897 |
| 580.0 | 2320 | - | 0.9897 |
| 581.0 | 2324 | - | 0.9897 |
| 582.0 | 2328 | - | 0.9897 |
| 583.0 | 2332 | - | 0.9900 |
| 584.0 | 2336 | - | 0.9900 |
| 585.0 | 2340 | - | 0.9900 |
| 586.0 | 2344 | - | 0.9904 |
| 587.0 | 2348 | - | 0.9904 |
| 588.0 | 2352 | - | 0.9904 |
| 589.0 | 2356 | - | 0.9901 |
| 590.0 | 2360 | - | 0.9901 |
| 591.0 | 2364 | - | 0.9898 |
| 592.0 | 2368 | - | 0.9898 |
| 593.0 | 2372 | - | 0.9898 |
| 594.0 | 2376 | - | 0.9901 |
| 595.0 | 2380 | - | 0.9901 |
| 596.0 | 2384 | - | 0.9901 |
| 597.0 | 2388 | - | 0.9901 |
| 598.0 | 2392 | - | 0.9901 |
| 599.0 | 2396 | - | 0.9904 |
| 600.0 | 2400 | - | 0.9904 |
| 601.0 | 2404 | - | 0.9904 |
| 602.0 | 2408 | - | 0.9904 |
| 603.0 | 2412 | - | 0.9904 |
| 604.0 | 2416 | - | 0.9907 |
| 605.0 | 2420 | - | 0.9904 |
| 606.0 | 2424 | - | 0.9904 |
| 607.0 | 2428 | - | 0.9904 |
| 608.0 | 2432 | - | 0.9904 |
| 609.0 | 2436 | - | 0.9904 |
| 610.0 | 2440 | - | 0.9904 |
| 611.0 | 2444 | - | 0.9907 |
| 612.0 | 2448 | - | 0.9907 |
| 613.0 | 2452 | - | 0.9907 |
| 614.0 | 2456 | - | 0.9907 |
| 615.0 | 2460 | - | 0.9907 |
| 616.0 | 2464 | - | 0.9907 |
| 617.0 | 2468 | - | 0.9910 |
| 618.0 | 2472 | - | 0.9910 |
| 619.0 | 2476 | - | 0.9910 |
| 620.0 | 2480 | - | 0.9910 |
| 621.0 | 2484 | - | 0.9913 |
| 622.0 | 2488 | - | 0.9910 |
| 623.0 | 2492 | - | 0.9907 |
| 624.0 | 2496 | - | 0.9907 |
| 625.0 | 2500 | 2.2939 | 0.9907 |
| 626.0 | 2504 | - | 0.9907 |
| 627.0 | 2508 | - | 0.9907 |
| 628.0 | 2512 | - | 0.9907 |
| 629.0 | 2516 | - | 0.9910 |
| 630.0 | 2520 | - | 0.9910 |
| 631.0 | 2524 | - | 0.9910 |
| 632.0 | 2528 | - | 0.9910 |
| 633.0 | 2532 | - | 0.9910 |
| 634.0 | 2536 | - | 0.9913 |
| 635.0 | 2540 | - | 0.9916 |
| 636.0 | 2544 | - | 0.9916 |
| 637.0 | 2548 | - | 0.9913 |
| 638.0 | 2552 | - | 0.9910 |
| 639.0 | 2556 | - | 0.9910 |
| 640.0 | 2560 | - | 0.9910 |
| 641.0 | 2564 | - | 0.9910 |
| 642.0 | 2568 | - | 0.9910 |
| 643.0 | 2572 | - | 0.9913 |
| 644.0 | 2576 | - | 0.9916 |
| 645.0 | 2580 | - | 0.9916 |
| 646.0 | 2584 | - | 0.9916 |
| 647.0 | 2588 | - | 0.9916 |
| 648.0 | 2592 | - | 0.9916 |
| 649.0 | 2596 | - | 0.9919 |
| 650.0 | 2600 | - | 0.9919 |
| 651.0 | 2604 | - | 0.9916 |
| 652.0 | 2608 | - | 0.9916 |
| 653.0 | 2612 | - | 0.9919 |
| 654.0 | 2616 | - | 0.9919 |
| 655.0 | 2620 | - | 0.9919 |
| 656.0 | 2624 | - | 0.9916 |
| 657.0 | 2628 | - | 0.9916 |
| 658.0 | 2632 | - | 0.9916 |
| 659.0 | 2636 | - | 0.9916 |
| 660.0 | 2640 | - | 0.9919 |
| 661.0 | 2644 | - | 0.9922 |
| 662.0 | 2648 | - | 0.9922 |
| 663.0 | 2652 | - | 0.9922 |
| 664.0 | 2656 | - | 0.9922 |
| 665.0 | 2660 | - | 0.9919 |
| 666.0 | 2664 | - | 0.9922 |
| 667.0 | 2668 | - | 0.9922 |
| 668.0 | 2672 | - | 0.9925 |
| 669.0 | 2676 | - | 0.9928 |
| 670.0 | 2680 | - | 0.9925 |
| 671.0 | 2684 | - | 0.9928 |
| 672.0 | 2688 | - | 0.9925 |
| 673.0 | 2692 | - | 0.9925 |
| 674.0 | 2696 | - | 0.9928 |
| 675.0 | 2700 | - | 0.9928 |
| 676.0 | 2704 | - | 0.9931 |
| 677.0 | 2708 | - | 0.9931 |
| 678.0 | 2712 | - | 0.9931 |
| 679.0 | 2716 | - | 0.9928 |
| 680.0 | 2720 | - | 0.9925 |
| 681.0 | 2724 | - | 0.9922 |
| 682.0 | 2728 | - | 0.9922 |
| 683.0 | 2732 | - | 0.9922 |
| 684.0 | 2736 | - | 0.9922 |
| 685.0 | 2740 | - | 0.9922 |
| 686.0 | 2744 | - | 0.9922 |
| 687.0 | 2748 | - | 0.9925 |
| 688.0 | 2752 | - | 0.9931 |
| 689.0 | 2756 | - | 0.9931 |
| 690.0 | 2760 | - | 0.9935 |
| 691.0 | 2764 | - | 0.9935 |
| 692.0 | 2768 | - | 0.9935 |
| 693.0 | 2772 | - | 0.9931 |
| 694.0 | 2776 | - | 0.9931 |
| 695.0 | 2780 | - | 0.9931 |
| 696.0 | 2784 | - | 0.9928 |
| 697.0 | 2788 | - | 0.9928 |
| 698.0 | 2792 | - | 0.9925 |
| 699.0 | 2796 | - | 0.9925 |
| 700.0 | 2800 | - | 0.9928 |
| 701.0 | 2804 | - | 0.9931 |
| 702.0 | 2808 | - | 0.9931 |
| 703.0 | 2812 | - | 0.9931 |
| 704.0 | 2816 | - | 0.9931 |
| 705.0 | 2820 | - | 0.9931 |
| 706.0 | 2824 | - | 0.9928 |
| 707.0 | 2828 | - | 0.9931 |
| 708.0 | 2832 | - | 0.9928 |
| 709.0 | 2836 | - | 0.9928 |
| 710.0 | 2840 | - | 0.9928 |
| 711.0 | 2844 | - | 0.9925 |
| 712.0 | 2848 | - | 0.9922 |
| 713.0 | 2852 | - | 0.9922 |
| 714.0 | 2856 | - | 0.9922 |
| 715.0 | 2860 | - | 0.9922 |
| 716.0 | 2864 | - | 0.9922 |
| 717.0 | 2868 | - | 0.9922 |
| 718.0 | 2872 | - | 0.9928 |
| 719.0 | 2876 | - | 0.9928 |
| 720.0 | 2880 | - | 0.9928 |
| 721.0 | 2884 | - | 0.9928 |
| 722.0 | 2888 | - | 0.9931 |
| 723.0 | 2892 | - | 0.9928 |
| 724.0 | 2896 | - | 0.9928 |
| 725.0 | 2900 | - | 0.9928 |
| 726.0 | 2904 | - | 0.9931 |
| 727.0 | 2908 | - | 0.9931 |
| 728.0 | 2912 | - | 0.9931 |
| 729.0 | 2916 | - | 0.9931 |
| 730.0 | 2920 | - | 0.9928 |
| 731.0 | 2924 | - | 0.9928 |
| 732.0 | 2928 | - | 0.9931 |
| 733.0 | 2932 | - | 0.9931 |
| 734.0 | 2936 | - | 0.9928 |
| 735.0 | 2940 | - | 0.9928 |
| 736.0 | 2944 | - | 0.9931 |
| 737.0 | 2948 | - | 0.9931 |
| 738.0 | 2952 | - | 0.9928 |
| 739.0 | 2956 | - | 0.9928 |
| 740.0 | 2960 | - | 0.9928 |
| 741.0 | 2964 | - | 0.9928 |
| 742.0 | 2968 | - | 0.9928 |
| 743.0 | 2972 | - | 0.9928 |
| 744.0 | 2976 | - | 0.9935 |
| 745.0 | 2980 | - | 0.9935 |
| 746.0 | 2984 | - | 0.9935 |
| 747.0 | 2988 | - | 0.9935 |
| 748.0 | 2992 | - | 0.9935 |
| 749.0 | 2996 | - | 0.9935 |
| 750.0 | 3000 | 2.2749 | 0.9935 |
| 751.0 | 3004 | - | 0.9935 |
| 752.0 | 3008 | - | 0.9938 |
| 753.0 | 3012 | - | 0.9938 |
| 754.0 | 3016 | - | 0.9938 |
| 755.0 | 3020 | - | 0.9941 |
| 756.0 | 3024 | - | 0.9938 |
| 757.0 | 3028 | - | 0.9938 |
| 758.0 | 3032 | - | 0.9938 |
| 759.0 | 3036 | - | 0.9938 |
| 760.0 | 3040 | - | 0.9938 |
| 761.0 | 3044 | - | 0.9938 |
| 762.0 | 3048 | - | 0.9938 |
| 763.0 | 3052 | - | 0.9939 |
| 764.0 | 3056 | - | 0.9942 |
| 765.0 | 3060 | - | 0.9942 |
| 766.0 | 3064 | - | 0.9939 |
| 767.0 | 3068 | - | 0.9939 |
| 768.0 | 3072 | - | 0.9942 |
| 769.0 | 3076 | - | 0.9939 |
| 770.0 | 3080 | - | 0.9939 |
| 771.0 | 3084 | - | 0.9938 |
| 772.0 | 3088 | - | 0.9938 |
| 773.0 | 3092 | - | 0.9938 |
| 774.0 | 3096 | - | 0.9938 |
| 775.0 | 3100 | - | 0.9938 |
| 776.0 | 3104 | - | 0.9938 |
| 777.0 | 3108 | - | 0.9935 |
| 778.0 | 3112 | - | 0.9935 |
| 779.0 | 3116 | - | 0.9935 |
| 780.0 | 3120 | - | 0.9938 |
| 781.0 | 3124 | - | 0.9938 |
| 782.0 | 3128 | - | 0.9935 |
| 783.0 | 3132 | - | 0.9935 |
| 784.0 | 3136 | - | 0.9935 |
| 785.0 | 3140 | - | 0.9931 |
| 786.0 | 3144 | - | 0.9931 |
| 787.0 | 3148 | - | 0.9931 |
| 788.0 | 3152 | - | 0.9931 |
| 789.0 | 3156 | - | 0.9931 |
| 790.0 | 3160 | - | 0.9931 |
| 791.0 | 3164 | - | 0.9931 |
| 792.0 | 3168 | - | 0.9935 |
| 793.0 | 3172 | - | 0.9935 |
| 794.0 | 3176 | - | 0.9935 |
| 795.0 | 3180 | - | 0.9935 |
| 796.0 | 3184 | - | 0.9935 |
| 797.0 | 3188 | - | 0.9933 |
| 798.0 | 3192 | - | 0.9933 |
| 799.0 | 3196 | - | 0.9936 |
| 800.0 | 3200 | - | 0.9936 |
| 801.0 | 3204 | - | 0.9933 |
| 802.0 | 3208 | - | 0.9935 |
| 803.0 | 3212 | - | 0.9938 |
| 804.0 | 3216 | - | 0.9935 |
| 805.0 | 3220 | - | 0.9931 |
| 806.0 | 3224 | - | 0.9936 |
| 807.0 | 3228 | - | 0.9936 |
| 808.0 | 3232 | - | 0.9939 |
| 809.0 | 3236 | - | 0.9942 |
| 810.0 | 3240 | - | 0.9945 |
| 811.0 | 3244 | - | 0.9945 |
| 812.0 | 3248 | - | 0.9945 |
| 813.0 | 3252 | - | 0.9945 |
| 814.0 | 3256 | - | 0.9942 |
| 815.0 | 3260 | - | 0.9939 |
| 816.0 | 3264 | - | 0.9942 |
| 817.0 | 3268 | - | 0.9939 |
| 818.0 | 3272 | - | 0.9942 |
| 819.0 | 3276 | - | 0.9942 |
| 820.0 | 3280 | - | 0.9942 |
| 821.0 | 3284 | - | 0.9945 |
| 822.0 | 3288 | - | 0.9945 |
| 823.0 | 3292 | - | 0.9945 |
| 824.0 | 3296 | - | 0.9945 |
| 825.0 | 3300 | - | 0.9945 |
| 826.0 | 3304 | - | 0.9945 |
| 827.0 | 3308 | - | 0.9945 |
| 828.0 | 3312 | - | 0.9945 |
| 829.0 | 3316 | - | 0.9945 |
| 830.0 | 3320 | - | 0.9945 |
| 831.0 | 3324 | - | 0.9945 |
| 832.0 | 3328 | - | 0.9945 |
| 833.0 | 3332 | - | 0.9945 |
| 834.0 | 3336 | - | 0.9948 |
| 835.0 | 3340 | - | 0.9948 |
| 836.0 | 3344 | - | 0.9948 |
| 837.0 | 3348 | - | 0.9948 |
| 838.0 | 3352 | - | 0.9948 |
| 839.0 | 3356 | - | 0.9948 |
| 840.0 | 3360 | - | 0.9948 |
| 841.0 | 3364 | - | 0.9948 |
| 842.0 | 3368 | - | 0.9948 |
| 843.0 | 3372 | - | 0.9948 |
| 844.0 | 3376 | - | 0.9945 |
| 845.0 | 3380 | - | 0.9945 |
| 846.0 | 3384 | - | 0.9948 |
| 847.0 | 3388 | - | 0.9948 |
| 848.0 | 3392 | - | 0.9948 |
| 849.0 | 3396 | - | 0.9948 |
| 850.0 | 3400 | - | 0.9948 |
| 851.0 | 3404 | - | 0.9948 |
| 852.0 | 3408 | - | 0.9948 |
| 853.0 | 3412 | - | 0.9948 |
| 854.0 | 3416 | - | 0.9948 |
| 855.0 | 3420 | - | 0.9948 |
| 856.0 | 3424 | - | 0.9948 |
| 857.0 | 3428 | - | 0.9945 |
| 858.0 | 3432 | - | 0.9945 |
| 859.0 | 3436 | - | 0.9945 |
| 860.0 | 3440 | - | 0.9945 |
| 861.0 | 3444 | - | 0.9945 |
| 862.0 | 3448 | - | 0.9948 |
| 863.0 | 3452 | - | 0.9948 |
| 864.0 | 3456 | - | 0.9948 |
| 865.0 | 3460 | - | 0.9948 |
| 866.0 | 3464 | - | 0.9948 |
| 867.0 | 3468 | - | 0.9948 |
| 868.0 | 3472 | - | 0.9948 |
| 869.0 | 3476 | - | 0.9948 |
| 870.0 | 3480 | - | 0.9948 |
| 871.0 | 3484 | - | 0.9948 |
| 872.0 | 3488 | - | 0.9948 |
| 873.0 | 3492 | - | 0.9948 |
| 874.0 | 3496 | - | 0.9948 |
| 875.0 | 3500 | 2.268 | 0.9948 |
| 876.0 | 3504 | - | 0.9948 |
| 877.0 | 3508 | - | 0.9948 |
| 878.0 | 3512 | - | 0.9948 |
| 879.0 | 3516 | - | 0.9948 |
| 880.0 | 3520 | - | 0.9948 |
| 881.0 | 3524 | - | 0.9948 |
| 882.0 | 3528 | - | 0.9948 |
| 883.0 | 3532 | - | 0.9948 |
| 884.0 | 3536 | - | 0.9948 |
| 885.0 | 3540 | - | 0.9948 |
| 886.0 | 3544 | - | 0.9948 |
| 887.0 | 3548 | - | 0.9948 |
| 888.0 | 3552 | - | 0.9948 |
| 889.0 | 3556 | - | 0.9948 |
| 890.0 | 3560 | - | 0.9948 |
| 891.0 | 3564 | - | 0.9948 |
| 892.0 | 3568 | - | 0.9948 |
| 893.0 | 3572 | - | 0.9948 |
| 894.0 | 3576 | - | 0.9948 |
| 895.0 | 3580 | - | 0.9948 |
| 896.0 | 3584 | - | 0.9948 |
| 897.0 | 3588 | - | 0.9948 |
| 898.0 | 3592 | - | 0.9948 |
| 899.0 | 3596 | - | 0.9948 |
| 900.0 | 3600 | - | 0.9948 |
| 901.0 | 3604 | - | 0.9948 |
| 902.0 | 3608 | - | 0.9948 |
| 903.0 | 3612 | - | 0.9948 |
| 904.0 | 3616 | - | 0.9948 |
| 905.0 | 3620 | - | 0.9948 |
| 906.0 | 3624 | - | 0.9948 |
| 907.0 | 3628 | - | 0.9948 |
| 908.0 | 3632 | - | 0.9948 |
| 909.0 | 3636 | - | 0.9948 |
| 910.0 | 3640 | - | 0.9948 |
| 911.0 | 3644 | - | 0.9948 |
| 912.0 | 3648 | - | 0.9948 |
| 913.0 | 3652 | - | 0.9948 |
| 914.0 | 3656 | - | 0.9948 |
| 915.0 | 3660 | - | 0.9948 |
| 916.0 | 3664 | - | 0.9948 |
| 917.0 | 3668 | - | 0.9948 |
| 918.0 | 3672 | - | 0.9948 |
| 919.0 | 3676 | - | 0.9948 |
| 920.0 | 3680 | - | 0.9948 |
| 921.0 | 3684 | - | 0.9948 |
| 922.0 | 3688 | - | 0.9948 |
| 923.0 | 3692 | - | 0.9948 |
| 924.0 | 3696 | - | 0.9948 |
| 925.0 | 3700 | - | 0.9948 |
| 926.0 | 3704 | - | 0.9948 |
| 927.0 | 3708 | - | 0.9948 |
| 928.0 | 3712 | - | 0.9948 |
| 929.0 | 3716 | - | 0.9948 |
| 930.0 | 3720 | - | 0.9948 |
| 931.0 | 3724 | - | 0.9948 |
| 932.0 | 3728 | - | 0.9948 |
| 933.0 | 3732 | - | 0.9948 |
| 934.0 | 3736 | - | 0.9948 |
| 935.0 | 3740 | - | 0.9948 |
| 936.0 | 3744 | - | 0.9948 |
| 937.0 | 3748 | - | 0.9948 |
| 938.0 | 3752 | - | 0.9948 |
| 939.0 | 3756 | - | 0.9948 |
| 940.0 | 3760 | - | 0.9948 |
| 941.0 | 3764 | - | 0.9948 |
| 942.0 | 3768 | - | 0.9948 |
| 943.0 | 3772 | - | 0.9948 |
| 944.0 | 3776 | - | 0.9948 |
| 945.0 | 3780 | - | 0.9948 |
| 946.0 | 3784 | - | 0.9948 |
| 947.0 | 3788 | - | 0.9948 |
| 948.0 | 3792 | - | 0.9948 |
| 949.0 | 3796 | - | 0.9948 |
| 950.0 | 3800 | - | 0.9948 |
| 951.0 | 3804 | - | 0.9948 |
| 952.0 | 3808 | - | 0.9948 |
| 953.0 | 3812 | - | 0.9948 |
| 954.0 | 3816 | - | 0.9948 |
| 955.0 | 3820 | - | 0.9948 |
| 956.0 | 3824 | - | 0.9948 |
| 957.0 | 3828 | - | 0.9948 |
| 958.0 | 3832 | - | 0.9948 |
| 959.0 | 3836 | - | 0.9948 |
| 960.0 | 3840 | - | 0.9948 |
| 961.0 | 3844 | - | 0.9948 |
| 962.0 | 3848 | - | 0.9948 |
| 963.0 | 3852 | - | 0.9948 |
| 964.0 | 3856 | - | 0.9948 |
| 965.0 | 3860 | - | 0.9948 |
| 966.0 | 3864 | - | 0.9948 |
| 967.0 | 3868 | - | 0.9948 |
| 968.0 | 3872 | - | 0.9948 |
| 969.0 | 3876 | - | 0.9948 |
| 970.0 | 3880 | - | 0.9948 |
| 971.0 | 3884 | - | 0.9948 |
| 972.0 | 3888 | - | 0.9948 |
| 973.0 | 3892 | - | 0.9948 |
| 974.0 | 3896 | - | 0.9948 |
| 975.0 | 3900 | - | 0.9948 |
| 976.0 | 3904 | - | 0.9948 |
| 977.0 | 3908 | - | 0.9948 |
| 978.0 | 3912 | - | 0.9948 |
| 979.0 | 3916 | - | 0.9948 |
| 980.0 | 3920 | - | 0.9948 |
| 981.0 | 3924 | - | 0.9948 |
| 982.0 | 3928 | - | 0.9948 |
| 983.0 | 3932 | - | 0.9948 |
| 984.0 | 3936 | - | 0.9948 |
| 985.0 | 3940 | - | 0.9948 |
| 986.0 | 3944 | - | 0.9948 |
| 987.0 | 3948 | - | 0.9948 |
| 988.0 | 3952 | - | 0.9948 |
| 989.0 | 3956 | - | 0.9948 |
| 990.0 | 3960 | - | 0.9948 |
| 991.0 | 3964 | - | 0.9948 |
| 992.0 | 3968 | - | 0.9948 |
| 993.0 | 3972 | - | 0.9948 |
| 994.0 | 3976 | - | 0.9948 |
| 995.0 | 3980 | - | 0.9948 |
| 996.0 | 3984 | - | 0.9948 |
| 997.0 | 3988 | - | 0.9948 |
| 998.0 | 3992 | - | 0.9948 |
| 999.0 | 3996 | - | 0.9948 |
| 1000.0 | 4000 | 2.265 | 0.9948 |
| 1001.0 | 4004 | - | 0.9948 |
| 1002.0 | 4008 | - | 0.9948 |
| 1003.0 | 4012 | - | 0.9948 |
| 1004.0 | 4016 | - | 0.9948 |
| 1005.0 | 4020 | - | 0.9948 |
| 1006.0 | 4024 | - | 0.9948 |
| 1007.0 | 4028 | - | 0.9948 |
| 1008.0 | 4032 | - | 0.9948 |
| 1009.0 | 4036 | - | 0.9948 |
| 1010.0 | 4040 | - | 0.9948 |
| 1011.0 | 4044 | - | 0.9948 |
| 1012.0 | 4048 | - | 0.9948 |
| 1013.0 | 4052 | - | 0.9948 |
| 1014.0 | 4056 | - | 0.9948 |
| 1015.0 | 4060 | - | 0.9948 |
| 1016.0 | 4064 | - | 0.9948 |
| 1017.0 | 4068 | - | 0.9948 |
| 1018.0 | 4072 | - | 0.9948 |
| 1019.0 | 4076 | - | 0.9948 |
| 1020.0 | 4080 | - | 0.9948 |
| 1021.0 | 4084 | - | 0.9948 |
| 1022.0 | 4088 | - | 0.9948 |
| 1023.0 | 4092 | - | 0.9948 |
| 1024.0 | 4096 | - | 0.9948 |
| 1025.0 | 4100 | - | 0.9948 |
| 1026.0 | 4104 | - | 0.9948 |
| 1027.0 | 4108 | - | 0.9948 |
| 1028.0 | 4112 | - | 0.9948 |
| 1029.0 | 4116 | - | 0.9948 |
| 1030.0 | 4120 | - | 0.9948 |
| 1031.0 | 4124 | - | 0.9948 |
| 1032.0 | 4128 | - | 0.9948 |
| 1033.0 | 4132 | - | 0.9948 |
| 1034.0 | 4136 | - | 0.9948 |
| 1035.0 | 4140 | - | 0.9948 |
| 1036.0 | 4144 | - | 0.9948 |
| 1037.0 | 4148 | - | 0.9948 |
| 1038.0 | 4152 | - | 0.9948 |
| 1039.0 | 4156 | - | 0.9948 |
| 1040.0 | 4160 | - | 0.9948 |
| 1041.0 | 4164 | - | 0.9948 |
| 1042.0 | 4168 | - | 0.9948 |
| 1043.0 | 4172 | - | 0.9948 |
| 1044.0 | 4176 | - | 0.9948 |
| 1045.0 | 4180 | - | 0.9948 |
| 1046.0 | 4184 | - | 0.9948 |
| 1047.0 | 4188 | - | 0.9948 |
| 1048.0 | 4192 | - | 0.9948 |
| 1049.0 | 4196 | - | 0.9948 |
| 1050.0 | 4200 | - | 0.9948 |
| 1051.0 | 4204 | - | 0.9948 |
| 1052.0 | 4208 | - | 0.9948 |
| 1053.0 | 4212 | - | 0.9948 |
| 1054.0 | 4216 | - | 0.9948 |
| 1055.0 | 4220 | - | 0.9948 |
| 1056.0 | 4224 | - | 0.9948 |
| 1057.0 | 4228 | - | 0.9948 |
| 1058.0 | 4232 | - | 0.9948 |
| 1059.0 | 4236 | - | 0.9948 |
| 1060.0 | 4240 | - | 0.9948 |
| 1061.0 | 4244 | - | 0.9948 |
| 1062.0 | 4248 | - | 0.9948 |
| 1063.0 | 4252 | - | 0.9948 |
| 1064.0 | 4256 | - | 0.9948 |
| 1065.0 | 4260 | - | 0.9948 |
| 1066.0 | 4264 | - | 0.9948 |
| 1067.0 | 4268 | - | 0.9948 |
| 1068.0 | 4272 | - | 0.9948 |
| 1069.0 | 4276 | - | 0.9948 |
| 1070.0 | 4280 | - | 0.9948 |
| 1071.0 | 4284 | - | 0.9948 |
| 1072.0 | 4288 | - | 0.9948 |
| 1073.0 | 4292 | - | 0.9948 |
| 1074.0 | 4296 | - | 0.9948 |
| 1075.0 | 4300 | - | 0.9948 |
| 1076.0 | 4304 | - | 0.9948 |
| 1077.0 | 4308 | - | 0.9948 |
| 1078.0 | 4312 | - | 0.9948 |
| 1079.0 | 4316 | - | 0.9948 |
| 1080.0 | 4320 | - | 0.9948 |
| 1081.0 | 4324 | - | 0.9948 |
| 1082.0 | 4328 | - | 0.9948 |
| 1083.0 | 4332 | - | 0.9948 |
| 1084.0 | 4336 | - | 0.9948 |
| 1085.0 | 4340 | - | 0.9948 |
| 1086.0 | 4344 | - | 0.9948 |
| 1087.0 | 4348 | - | 0.9948 |
| 1088.0 | 4352 | - | 0.9948 |
| 1089.0 | 4356 | - | 0.9948 |
| 1090.0 | 4360 | - | 0.9948 |
| 1091.0 | 4364 | - | 0.9948 |
| 1092.0 | 4368 | - | 0.9948 |
| 1093.0 | 4372 | - | 0.9948 |
| 1094.0 | 4376 | - | 0.9948 |
| 1095.0 | 4380 | - | 0.9948 |
| 1096.0 | 4384 | - | 0.9948 |
| 1097.0 | 4388 | - | 0.9948 |
| 1098.0 | 4392 | - | 0.9948 |
| 1099.0 | 4396 | - | 0.9948 |
| 1100.0 | 4400 | - | 0.9948 |
| 1101.0 | 4404 | - | 0.9948 |
| 1102.0 | 4408 | - | 0.9948 |
| 1103.0 | 4412 | - | 0.9948 |
| 1104.0 | 4416 | - | 0.9948 |
| 1105.0 | 4420 | - | 0.9948 |
| 1106.0 | 4424 | - | 0.9948 |
| 1107.0 | 4428 | - | 0.9948 |
| 1108.0 | 4432 | - | 0.9948 |
| 1109.0 | 4436 | - | 0.9948 |
| 1110.0 | 4440 | - | 0.9948 |
| 1111.0 | 4444 | - | 0.9948 |
| 1112.0 | 4448 | - | 0.9948 |
| 1113.0 | 4452 | - | 0.9948 |
| 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 |
</details>
### Framework Versions
- Python: 3.10.14
- Sentence Transformers: 3.0.1
- Transformers: 4.44.0
- PyTorch: 2.4.0
- Accelerate: 0.34.2
- Datasets: 2.21.0
- Tokenizers: 0.19.1
## Citation
### BibTeX
#### Sentence Transformers
```bibtex
@inproceedings{reimers-2019-sentence-bert,
title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
author = "Reimers, Nils and Gurevych, Iryna",
booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
month = "11",
year = "2019",
publisher = "Association for Computational Linguistics",
url = "https://arxiv.org/abs/1908.10084",
}
```
#### MultipleNegativesRankingLoss
```bibtex
@misc{henderson2017efficient,
title={Efficient Natural Language Response Suggestion for Smart Reply},
author={Matthew Henderson and Rami Al-Rfou and Brian Strope and Yun-hsuan Sung and Laszlo Lukacs and Ruiqi Guo and Sanjiv Kumar and Balint Miklos and Ray Kurzweil},
year={2017},
eprint={1705.00652},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
```
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