---
base_model: sentence-transformers/all-distilroberta-v1
library_name: sentence-transformers
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- feature-extraction
- generated_from_trainer
- dataset_size:5817740
- loss:MaskedCachedMultipleNegativesRankingLoss
widget:
- source_sentence: Mathlib.Algebra.Group.Pointwise.Finset.Basic#679
sentences:
- instContinuousStarReal
- StrictOrderedSemiring.toMulPosStrictMono
- IsCancelAdd.toIsLeftCancelAdd
- source_sentence: Mathlib.Algebra.MvPolynomial.Degrees#315
sentences:
- Algebra.smul_def
- IsLocalMinOn.hasFDerivWithinAt_nonneg
- CategoryTheory.GlueData.t_fac
- source_sentence: Mathlib.Algebra.Group.Pointwise.Finset.Basic#679
sentences:
- eq_of_heq
- add_right_injective
- Summable.of_norm_bounded_eventually_nat
- source_sentence: Mathlib.Algebra.Polynomial.FieldDivision#94
sentences:
- Polynomial.coe_normUnit
- Nat.instCharZero
- Multiset.map_congr
- source_sentence: Mathlib.Analysis.SpecialFunctions.Complex.LogDeriv#35
sentences:
- Nat.cast_zero
- Function.Injective.eq_iff
- HasDerivAt.clog
---
# SentenceTransformer based on sentence-transformers/all-distilroberta-v1
This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [sentence-transformers/all-distilroberta-v1](https://huggingface.co/sentence-transformers/all-distilroberta-v1). It maps sentences & paragraphs to a 768-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more.
## Model Details
### Model Description
- **Model Type:** Sentence Transformer
- **Base model:** [sentence-transformers/all-distilroberta-v1](https://huggingface.co/sentence-transformers/all-distilroberta-v1)
- **Maximum Sequence Length:** 512 tokens
- **Output Dimensionality:** 768 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': 512, 'do_lower_case': False}) with Transformer model: RobertaModel
(1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
(2): Normalize()
)
```
## Usage
### Direct Usage (Sentence Transformers)
First install the Sentence Transformers library:
```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("hanwenzhu/all-distilroberta-v1-lr2e-4-bs256-nneg3-ml-ne5-mar17")
# Run inference
sentences = [
'Mathlib.Analysis.SpecialFunctions.Complex.LogDeriv#35',
'HasDerivAt.clog',
'Nat.cast_zero',
]
embeddings = model.encode(sentences)
print(embeddings.shape)
# [3, 768]
# Get the similarity scores for the embeddings
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [3, 3]
```
## Training Details
### Training Dataset
#### Unnamed Dataset
* Size: 5,817,740 training samples
* Columns: state_name and premise_name
* Approximate statistics based on the first 1000 samples:
| | state_name | premise_name |
|:--------|:-----------------------------------------------------------------------------------|:---------------------------------------------------------------------------------|
| type | string | string |
| details | - min: 11 tokens
- mean: 16.44 tokens
- max: 24 tokens
| - min: 3 tokens
- mean: 10.9 tokens
- max: 50 tokens
|
* Samples:
| state_name | premise_name |
|:----------------------------------------------|:-----------------------------------|
| Mathlib.Algebra.Field.IsField#12 | Classical.choose_spec |
| Mathlib.Algebra.Field.IsField#12 | IsField.mul_comm |
| Mathlib.Algebra.Field.IsField#12 | eq_of_heq |
* Loss: loss.MaskedCachedMultipleNegativesRankingLoss with these parameters:
```json
{
"scale": 20.0,
"similarity_fct": "cos_sim"
}
```
### Evaluation Dataset
#### Unnamed Dataset
* Size: 1,959 evaluation samples
* Columns: state_name and premise_name
* Approximate statistics based on the first 1000 samples:
| | state_name | premise_name |
|:--------|:-----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|
| type | string | string |
| details | - min: 10 tokens
- mean: 17.08 tokens
- max: 24 tokens
| - min: 5 tokens
- mean: 11.05 tokens
- max: 31 tokens
|
* Samples:
| state_name | premise_name |
|:-------------------------------------------------------------|:----------------------------------------------------------|
| Mathlib.Algebra.Algebra.Hom#80 | AlgHom.commutes |
| Mathlib.Algebra.Algebra.NonUnitalSubalgebra#237 | NonUnitalAlgHom.instNonUnitalAlgSemiHomClass |
| Mathlib.Algebra.Algebra.NonUnitalSubalgebra#237 | NonUnitalAlgebra.mem_top |
* Loss: loss.MaskedCachedMultipleNegativesRankingLoss with these parameters:
```json
{
"scale": 20.0,
"similarity_fct": "cos_sim"
}
```
### Training Hyperparameters
#### Non-Default Hyperparameters
- `eval_strategy`: steps
- `per_device_train_batch_size`: 256
- `per_device_eval_batch_size`: 64
- `learning_rate`: 0.0002
- `num_train_epochs`: 5.0
- `lr_scheduler_type`: cosine
- `warmup_ratio`: 0.03
- `bf16`: True
- `dataloader_num_workers`: 4
- `resume_from_checkpoint`: /data/user_data/thomaszh/models/all-distilroberta-v1-lr2e-4-bs256-nneg3-ml-ne5/checkpoint-104604
#### All Hyperparameters
Click to expand
- `overwrite_output_dir`: False
- `do_predict`: False
- `eval_strategy`: steps
- `prediction_loss_only`: True
- `per_device_train_batch_size`: 256
- `per_device_eval_batch_size`: 64
- `per_gpu_train_batch_size`: None
- `per_gpu_eval_batch_size`: None
- `gradient_accumulation_steps`: 1
- `eval_accumulation_steps`: None
- `torch_empty_cache_steps`: None
- `learning_rate`: 0.0002
- `weight_decay`: 0.0
- `adam_beta1`: 0.9
- `adam_beta2`: 0.999
- `adam_epsilon`: 1e-08
- `max_grad_norm`: 1.0
- `num_train_epochs`: 5.0
- `max_steps`: -1
- `lr_scheduler_type`: cosine
- `lr_scheduler_kwargs`: {}
- `warmup_ratio`: 0.03
- `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`: True
- `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`: 4
- `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`: /data/user_data/thomaszh/models/all-distilroberta-v1-lr2e-4-bs256-nneg3-ml-ne5/checkpoint-104604
- `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
- `use_liger_kernel`: False
- `eval_use_gather_object`: False
- `batch_sampler`: batch_sampler
- `multi_dataset_batch_sampler`: proportional
Click to expand
| Epoch | Step | Training Loss | loss |
|:------:|:------:|:-------------:|:------:|
| 4.6031 | 104610 | 0.4939 | - |
| 4.6035 | 104620 | 0.4904 | - |
| 4.6040 | 104630 | 0.481 | - |
| 4.6044 | 104640 | 0.486 | - |
| 4.6049 | 104650 | 0.4596 | - |
| 4.6053 | 104660 | 0.4864 | - |
| 4.6057 | 104670 | 0.4577 | - |
| 4.6062 | 104680 | 0.4646 | - |
| 4.6066 | 104690 | 0.4478 | - |
| 4.6071 | 104700 | 0.4844 | - |
| 4.6075 | 104710 | 0.4836 | - |
| 4.6079 | 104720 | 0.4445 | - |
| 4.6084 | 104730 | 0.4883 | - |
| 4.6088 | 104740 | 0.5054 | - |
| 4.6093 | 104750 | 0.4992 | - |
| 4.6097 | 104760 | 0.4759 | - |
| 4.6101 | 104770 | 0.483 | - |
| 4.6106 | 104780 | 0.4668 | - |
| 4.6110 | 104790 | 0.4839 | - |
| 4.6115 | 104800 | 0.4426 | - |
| 4.6119 | 104810 | 0.4851 | - |
| 4.6123 | 104820 | 0.4837 | - |
| 4.6128 | 104830 | 0.4728 | - |
| 4.6132 | 104840 | 0.4796 | - |
| 4.6137 | 104850 | 0.4824 | - |
| 4.6141 | 104860 | 0.4948 | - |
| 4.6145 | 104870 | 0.4902 | - |
| 4.6150 | 104880 | 0.4565 | - |
| 4.6154 | 104890 | 0.5068 | - |
| 4.6159 | 104900 | 0.4881 | - |
| 4.6163 | 104910 | 0.5064 | - |
| 4.6167 | 104920 | 0.4877 | - |
| 4.6172 | 104930 | 0.498 | - |
| 4.6176 | 104940 | 0.478 | - |
| 4.6181 | 104950 | 0.4972 | - |
| 4.6185 | 104960 | 0.4654 | - |
| 4.6189 | 104970 | 0.4544 | - |
| 4.6194 | 104980 | 0.477 | - |
| 4.6198 | 104990 | 0.4957 | - |
| 4.6203 | 105000 | 0.4695 | - |
| 4.6207 | 105010 | 0.4927 | - |
| 4.6211 | 105020 | 0.4805 | - |
| 4.6216 | 105030 | 0.4929 | - |
| 4.6220 | 105040 | 0.4711 | - |
| 4.6225 | 105050 | 0.4814 | - |
| 4.6229 | 105060 | 0.464 | - |
| 4.6233 | 105070 | 0.4752 | - |
| 4.6238 | 105080 | 0.4609 | - |
| 4.6242 | 105090 | 0.4754 | - |
| 4.6247 | 105100 | 0.48 | - |
| 4.6251 | 105110 | 0.4587 | - |
| 4.6255 | 105120 | 0.4709 | - |
| 4.6260 | 105130 | 0.4775 | - |
| 4.6264 | 105140 | 0.4856 | - |
| 4.6269 | 105150 | 0.5094 | - |
| 4.6273 | 105160 | 0.4857 | - |
| 4.6277 | 105170 | 0.4826 | - |
| 4.6282 | 105180 | 0.4755 | - |
| 4.6286 | 105190 | 0.478 | - |
| 4.6291 | 105200 | 0.4653 | - |
| 4.6295 | 105210 | 0.4846 | - |
| 4.6299 | 105220 | 0.495 | - |
| 4.6304 | 105230 | 0.4818 | - |
| 4.6308 | 105240 | 0.4774 | - |
| 4.6313 | 105250 | 0.4653 | - |
| 4.6317 | 105260 | 0.4831 | - |
| 4.6321 | 105270 | 0.4669 | - |
| 4.6326 | 105280 | 0.487 | - |
| 4.6330 | 105290 | 0.4782 | - |
| 4.6335 | 105300 | 0.4856 | - |
| 4.6339 | 105310 | 0.4788 | - |
| 4.6343 | 105320 | 0.4645 | - |
| 4.6348 | 105330 | 0.4584 | - |
| 4.6352 | 105340 | 0.4794 | - |
| 4.6357 | 105350 | 0.4689 | - |
| 4.6361 | 105360 | 0.4987 | - |
| 4.6365 | 105370 | 0.4593 | - |
| 4.6370 | 105380 | 0.4912 | - |
| 4.6374 | 105390 | 0.468 | - |
| 4.6379 | 105400 | 0.487 | - |
| 4.6383 | 105410 | 0.4889 | - |
| 4.6387 | 105420 | 0.4561 | - |
| 4.6392 | 105430 | 0.4759 | - |
| 4.6396 | 105440 | 0.4686 | - |
| 4.6401 | 105450 | 0.4885 | - |
| 4.6405 | 105460 | 0.4705 | - |
| 4.6409 | 105470 | 0.4763 | - |
| 4.6414 | 105480 | 0.4794 | - |
| 4.6418 | 105490 | 0.4922 | - |
| 4.6423 | 105500 | 0.4693 | - |
| 4.6427 | 105510 | 0.4923 | - |
| 4.6431 | 105520 | 0.4856 | - |
| 4.6436 | 105530 | 0.4796 | - |
| 4.6440 | 105540 | 0.4914 | - |
| 4.6445 | 105550 | 0.4501 | - |
| 4.6449 | 105560 | 0.4848 | - |
| 4.6453 | 105570 | 0.478 | - |
| 4.6458 | 105580 | 0.4637 | - |
| 4.6462 | 105590 | 0.4796 | - |
| 4.6467 | 105600 | 0.4826 | - |
| 4.6471 | 105610 | 0.4781 | - |
| 4.6475 | 105620 | 0.4882 | - |
| 4.6480 | 105630 | 0.4964 | - |
| 4.6484 | 105640 | 0.4779 | - |
| 4.6489 | 105650 | 0.4701 | - |
| 4.6493 | 105660 | 0.4673 | - |
| 4.6497 | 105670 | 0.5103 | - |
| 4.6502 | 105680 | 0.4795 | - |
| 4.6506 | 105690 | 0.489 | - |
| 4.6511 | 105700 | 0.4653 | - |
| 4.6515 | 105710 | 0.4607 | - |
| 4.6519 | 105720 | 0.468 | - |
| 4.6524 | 105730 | 0.4719 | - |
| 4.6528 | 105740 | 0.4784 | - |
| 4.6529 | 105741 | - | 1.2566 |
| 4.6533 | 105750 | 0.4967 | - |
| 4.6537 | 105760 | 0.4744 | - |
| 4.6541 | 105770 | 0.4645 | - |
| 4.6546 | 105780 | 0.4732 | - |
| 4.6550 | 105790 | 0.4869 | - |
| 4.6555 | 105800 | 0.463 | - |
| 4.6559 | 105810 | 0.5 | - |
| 4.6563 | 105820 | 0.4671 | - |
| 4.6568 | 105830 | 0.4734 | - |
| 4.6572 | 105840 | 0.4699 | - |
| 4.6577 | 105850 | 0.4864 | - |
| 4.6581 | 105860 | 0.5178 | - |
| 4.6585 | 105870 | 0.4782 | - |
| 4.6590 | 105880 | 0.4902 | - |
| 4.6594 | 105890 | 0.4823 | - |
| 4.6599 | 105900 | 0.4542 | - |
| 4.6603 | 105910 | 0.4609 | - |
| 4.6607 | 105920 | 0.4586 | - |
| 4.6612 | 105930 | 0.4864 | - |
| 4.6616 | 105940 | 0.479 | - |
| 4.6621 | 105950 | 0.4717 | - |
| 4.6625 | 105960 | 0.4938 | - |
| 4.6629 | 105970 | 0.4685 | - |
| 4.6634 | 105980 | 0.4705 | - |
| 4.6638 | 105990 | 0.4958 | - |
| 4.6643 | 106000 | 0.4722 | - |
| 4.6647 | 106010 | 0.4633 | - |
| 4.6651 | 106020 | 0.4877 | - |
| 4.6656 | 106030 | 0.4606 | - |
| 4.6660 | 106040 | 0.4797 | - |
| 4.6665 | 106050 | 0.4493 | - |
| 4.6669 | 106060 | 0.4745 | - |
| 4.6673 | 106070 | 0.4918 | - |
| 4.6678 | 106080 | 0.4966 | - |
| 4.6682 | 106090 | 0.4498 | - |
| 4.6687 | 106100 | 0.4965 | - |
| 4.6691 | 106110 | 0.4911 | - |
| 4.6695 | 106120 | 0.4907 | - |
| 4.6700 | 106130 | 0.4983 | - |
| 4.6704 | 106140 | 0.4665 | - |
| 4.6709 | 106150 | 0.4656 | - |
| 4.6713 | 106160 | 0.4967 | - |
| 4.6717 | 106170 | 0.4849 | - |
| 4.6722 | 106180 | 0.4895 | - |
| 4.6726 | 106190 | 0.5068 | - |
| 4.6731 | 106200 | 0.4711 | - |
| 4.6735 | 106210 | 0.4674 | - |
| 4.6739 | 106220 | 0.4659 | - |
| 4.6744 | 106230 | 0.4551 | - |
| 4.6748 | 106240 | 0.4449 | - |
| 4.6753 | 106250 | 0.4719 | - |
| 4.6757 | 106260 | 0.4872 | - |
| 4.6761 | 106270 | 0.4966 | - |
| 4.6766 | 106280 | 0.4792 | - |
| 4.6770 | 106290 | 0.4678 | - |
| 4.6775 | 106300 | 0.4731 | - |
| 4.6779 | 106310 | 0.4692 | - |
| 4.6783 | 106320 | 0.4766 | - |
| 4.6788 | 106330 | 0.4862 | - |
| 4.6792 | 106340 | 0.4784 | - |
| 4.6797 | 106350 | 0.4583 | - |
| 4.6801 | 106360 | 0.483 | - |
| 4.6805 | 106370 | 0.4846 | - |
| 4.6810 | 106380 | 0.4742 | - |
| 4.6814 | 106390 | 0.4573 | - |
| 4.6819 | 106400 | 0.4849 | - |
| 4.6823 | 106410 | 0.4731 | - |
| 4.6827 | 106420 | 0.4779 | - |
| 4.6832 | 106430 | 0.499 | - |
| 4.6836 | 106440 | 0.4798 | - |
| 4.6841 | 106450 | 0.4812 | - |
| 4.6845 | 106460 | 0.4946 | - |
| 4.6849 | 106470 | 0.4477 | - |
| 4.6854 | 106480 | 0.488 | - |
| 4.6858 | 106490 | 0.453 | - |
| 4.6863 | 106500 | 0.492 | - |
| 4.6867 | 106510 | 0.4665 | - |
| 4.6871 | 106520 | 0.478 | - |
| 4.6876 | 106530 | 0.4756 | - |
| 4.6880 | 106540 | 0.4766 | - |
| 4.6885 | 106550 | 0.4797 | - |
| 4.6889 | 106560 | 0.4539 | - |
| 4.6893 | 106570 | 0.4704 | - |
| 4.6898 | 106580 | 0.4763 | - |
| 4.6902 | 106590 | 0.4708 | - |
| 4.6907 | 106600 | 0.4594 | - |
| 4.6911 | 106610 | 0.477 | - |
| 4.6915 | 106620 | 0.471 | - |
| 4.6920 | 106630 | 0.4766 | - |
| 4.6924 | 106640 | 0.5066 | - |
| 4.6929 | 106650 | 0.5013 | - |
| 4.6933 | 106660 | 0.4733 | - |
| 4.6937 | 106670 | 0.4751 | - |
| 4.6942 | 106680 | 0.4794 | - |
| 4.6946 | 106690 | 0.4897 | - |
| 4.6951 | 106700 | 0.483 | - |
| 4.6955 | 106710 | 0.4732 | - |
| 4.6959 | 106720 | 0.4744 | - |
| 4.6964 | 106730 | 0.4627 | - |
| 4.6968 | 106740 | 0.4728 | - |
| 4.6973 | 106750 | 0.4698 | - |
| 4.6977 | 106760 | 0.4787 | - |
| 4.6981 | 106770 | 0.474 | - |
| 4.6986 | 106780 | 0.4667 | - |
| 4.6990 | 106790 | 0.4879 | - |
| 4.6995 | 106800 | 0.4994 | - |
| 4.6999 | 106810 | 0.4989 | - |
| 4.7003 | 106820 | 0.4592 | - |
| 4.7008 | 106830 | 0.4613 | - |
| 4.7012 | 106840 | 0.4904 | - |
| 4.7017 | 106850 | 0.4727 | - |
| 4.7021 | 106860 | 0.4681 | - |
| 4.7025 | 106870 | 0.4785 | - |
| 4.7029 | 106878 | - | 1.2603 |
| 4.7030 | 106880 | 0.4598 | - |
| 4.7034 | 106890 | 0.49 | - |
| 4.7039 | 106900 | 0.4809 | - |
| 4.7043 | 106910 | 0.5019 | - |
| 4.7047 | 106920 | 0.4417 | - |
| 4.7052 | 106930 | 0.4856 | - |
| 4.7056 | 106940 | 0.4656 | - |
| 4.7061 | 106950 | 0.5102 | - |
| 4.7065 | 106960 | 0.4836 | - |
| 4.7069 | 106970 | 0.4549 | - |
| 4.7074 | 106980 | 0.4767 | - |
| 4.7078 | 106990 | 0.4794 | - |
| 4.7083 | 107000 | 0.4979 | - |
| 4.7087 | 107010 | 0.4739 | - |
| 4.7091 | 107020 | 0.4941 | - |
| 4.7096 | 107030 | 0.4783 | - |
| 4.7100 | 107040 | 0.5039 | - |
| 4.7105 | 107050 | 0.4601 | - |
| 4.7109 | 107060 | 0.4761 | - |
| 4.7113 | 107070 | 0.4695 | - |
| 4.7118 | 107080 | 0.5134 | - |
| 4.7122 | 107090 | 0.4816 | - |
| 4.7127 | 107100 | 0.4791 | - |
| 4.7131 | 107110 | 0.4601 | - |
| 4.7135 | 107120 | 0.4884 | - |
| 4.7140 | 107130 | 0.4891 | - |
| 4.7144 | 107140 | 0.4559 | - |
| 4.7149 | 107150 | 0.4439 | - |
| 4.7153 | 107160 | 0.493 | - |
| 4.7157 | 107170 | 0.4851 | - |
| 4.7162 | 107180 | 0.4774 | - |
| 4.7166 | 107190 | 0.4638 | - |
| 4.7171 | 107200 | 0.4683 | - |
| 4.7175 | 107210 | 0.4733 | - |
| 4.7179 | 107220 | 0.4859 | - |
| 4.7184 | 107230 | 0.4867 | - |
| 4.7188 | 107240 | 0.4739 | - |
| 4.7193 | 107250 | 0.4948 | - |
| 4.7197 | 107260 | 0.4621 | - |
| 4.7201 | 107270 | 0.4627 | - |
| 4.7206 | 107280 | 0.498 | - |
| 4.7210 | 107290 | 0.4614 | - |
| 4.7215 | 107300 | 0.4561 | - |
| 4.7219 | 107310 | 0.4893 | - |
| 4.7223 | 107320 | 0.4621 | - |
| 4.7228 | 107330 | 0.4722 | - |
| 4.7232 | 107340 | 0.485 | - |
| 4.7237 | 107350 | 0.4628 | - |
| 4.7241 | 107360 | 0.4807 | - |
| 4.7245 | 107370 | 0.4798 | - |
| 4.7250 | 107380 | 0.4673 | - |
| 4.7254 | 107390 | 0.4703 | - |
| 4.7259 | 107400 | 0.4956 | - |
| 4.7263 | 107410 | 0.4715 | - |
| 4.7267 | 107420 | 0.4928 | - |
| 4.7272 | 107430 | 0.4854 | - |
| 4.7276 | 107440 | 0.4781 | - |
| 4.7281 | 107450 | 0.4906 | - |
| 4.7285 | 107460 | 0.491 | - |
| 4.7289 | 107470 | 0.4766 | - |
| 4.7294 | 107480 | 0.4745 | - |
| 4.7298 | 107490 | 0.4756 | - |
| 4.7303 | 107500 | 0.4839 | - |
| 4.7307 | 107510 | 0.4492 | - |
| 4.7311 | 107520 | 0.4579 | - |
| 4.7316 | 107530 | 0.4823 | - |
| 4.7320 | 107540 | 0.4514 | - |
| 4.7325 | 107550 | 0.4595 | - |
| 4.7329 | 107560 | 0.4898 | - |
| 4.7333 | 107570 | 0.4508 | - |
| 4.7338 | 107580 | 0.49 | - |
| 4.7342 | 107590 | 0.4475 | - |
| 4.7347 | 107600 | 0.4801 | - |
| 4.7351 | 107610 | 0.4665 | - |
| 4.7355 | 107620 | 0.4769 | - |
| 4.7360 | 107630 | 0.4827 | - |
| 4.7364 | 107640 | 0.4817 | - |
| 4.7369 | 107650 | 0.4608 | - |
| 4.7373 | 107660 | 0.4681 | - |
| 4.7377 | 107670 | 0.4681 | - |
| 4.7382 | 107680 | 0.5057 | - |
| 4.7386 | 107690 | 0.4849 | - |
| 4.7391 | 107700 | 0.4793 | - |
| 4.7395 | 107710 | 0.4935 | - |
| 4.7399 | 107720 | 0.4763 | - |
| 4.7404 | 107730 | 0.4774 | - |
| 4.7408 | 107740 | 0.4883 | - |
| 4.7413 | 107750 | 0.4613 | - |
| 4.7417 | 107760 | 0.4817 | - |
| 4.7421 | 107770 | 0.4721 | - |
| 4.7426 | 107780 | 0.4681 | - |
| 4.7430 | 107790 | 0.4818 | - |
| 4.7435 | 107800 | 0.4762 | - |
| 4.7439 | 107810 | 0.496 | - |
| 4.7443 | 107820 | 0.4865 | - |
| 4.7448 | 107830 | 0.4748 | - |
| 4.7452 | 107840 | 0.4525 | - |
| 4.7457 | 107850 | 0.4783 | - |
| 4.7461 | 107860 | 0.4754 | - |
| 4.7465 | 107870 | 0.4676 | - |
| 4.7470 | 107880 | 0.4811 | - |
| 4.7474 | 107890 | 0.4932 | - |
| 4.7479 | 107900 | 0.4764 | - |
| 4.7483 | 107910 | 0.4877 | - |
| 4.7487 | 107920 | 0.4709 | - |
| 4.7492 | 107930 | 0.4633 | - |
| 4.7496 | 107940 | 0.471 | - |
| 4.7501 | 107950 | 0.4692 | - |
| 4.7505 | 107960 | 0.4549 | - |
| 4.7509 | 107970 | 0.4778 | - |
| 4.7514 | 107980 | 0.4921 | - |
| 4.7518 | 107990 | 0.4801 | - |
| 4.7523 | 108000 | 0.4662 | - |
| 4.7527 | 108010 | 0.4852 | - |
| 4.7529 | 108015 | - | 1.2617 |
| 4.7531 | 108020 | 0.4915 | - |
| 4.7536 | 108030 | 0.472 | - |
| 4.7540 | 108040 | 0.4906 | - |
| 4.7545 | 108050 | 0.4817 | - |
| 4.7549 | 108060 | 0.4724 | - |
| 4.7553 | 108070 | 0.4696 | - |
| 4.7558 | 108080 | 0.4791 | - |
| 4.7562 | 108090 | 0.4819 | - |
| 4.7567 | 108100 | 0.4953 | - |
| 4.7571 | 108110 | 0.4665 | - |
| 4.7575 | 108120 | 0.4688 | - |
| 4.7580 | 108130 | 0.4791 | - |
| 4.7584 | 108140 | 0.4734 | - |
| 4.7589 | 108150 | 0.4828 | - |
| 4.7593 | 108160 | 0.4718 | - |
| 4.7597 | 108170 | 0.4813 | - |
| 4.7602 | 108180 | 0.4827 | - |
| 4.7606 | 108190 | 0.4993 | - |
| 4.7611 | 108200 | 0.4745 | - |
| 4.7615 | 108210 | 0.4777 | - |
| 4.7619 | 108220 | 0.4757 | - |
| 4.7624 | 108230 | 0.4799 | - |
| 4.7628 | 108240 | 0.4936 | - |
| 4.7633 | 108250 | 0.4893 | - |
| 4.7637 | 108260 | 0.464 | - |
| 4.7641 | 108270 | 0.4669 | - |
| 4.7646 | 108280 | 0.4921 | - |
| 4.7650 | 108290 | 0.4815 | - |
| 4.7655 | 108300 | 0.4836 | - |
| 4.7659 | 108310 | 0.4718 | - |
| 4.7663 | 108320 | 0.4574 | - |
| 4.7668 | 108330 | 0.4779 | - |
| 4.7672 | 108340 | 0.4849 | - |
| 4.7677 | 108350 | 0.4849 | - |
| 4.7681 | 108360 | 0.4601 | - |
| 4.7685 | 108370 | 0.4654 | - |
| 4.7690 | 108380 | 0.4704 | - |
| 4.7694 | 108390 | 0.4727 | - |
| 4.7699 | 108400 | 0.48 | - |
| 4.7703 | 108410 | 0.4726 | - |
| 4.7707 | 108420 | 0.4791 | - |
| 4.7712 | 108430 | 0.4519 | - |
| 4.7716 | 108440 | 0.4568 | - |
| 4.7721 | 108450 | 0.4833 | - |
| 4.7725 | 108460 | 0.476 | - |
| 4.7729 | 108470 | 0.4597 | - |
| 4.7734 | 108480 | 0.4745 | - |
| 4.7738 | 108490 | 0.4744 | - |
| 4.7743 | 108500 | 0.4601 | - |
| 4.7747 | 108510 | 0.4807 | - |
| 4.7751 | 108520 | 0.463 | - |
| 4.7756 | 108530 | 0.4761 | - |
| 4.7760 | 108540 | 0.4716 | - |
| 4.7765 | 108550 | 0.5068 | - |
| 4.7769 | 108560 | 0.4832 | - |
| 4.7773 | 108570 | 0.4641 | - |
| 4.7778 | 108580 | 0.466 | - |
| 4.7782 | 108590 | 0.4635 | - |
| 4.7787 | 108600 | 0.5043 | - |
| 4.7791 | 108610 | 0.4563 | - |
| 4.7795 | 108620 | 0.4998 | - |
| 4.7800 | 108630 | 0.5168 | - |
| 4.7804 | 108640 | 0.4806 | - |
| 4.7809 | 108650 | 0.4658 | - |
| 4.7813 | 108660 | 0.4594 | - |
| 4.7817 | 108670 | 0.4552 | - |
| 4.7822 | 108680 | 0.4604 | - |
| 4.7826 | 108690 | 0.4742 | - |
| 4.7831 | 108700 | 0.5057 | - |
| 4.7835 | 108710 | 0.4963 | - |
| 4.7839 | 108720 | 0.4626 | - |
| 4.7844 | 108730 | 0.4581 | - |
| 4.7848 | 108740 | 0.473 | - |
| 4.7853 | 108750 | 0.4914 | - |
| 4.7857 | 108760 | 0.4838 | - |
| 4.7861 | 108770 | 0.4643 | - |
| 4.7866 | 108780 | 0.5038 | - |
| 4.7870 | 108790 | 0.4858 | - |
| 4.7875 | 108800 | 0.4516 | - |
| 4.7879 | 108810 | 0.4685 | - |
| 4.7883 | 108820 | 0.4639 | - |
| 4.7888 | 108830 | 0.498 | - |
| 4.7892 | 108840 | 0.4752 | - |
| 4.7897 | 108850 | 0.475 | - |
| 4.7901 | 108860 | 0.4802 | - |
| 4.7905 | 108870 | 0.4624 | - |
| 4.7910 | 108880 | 0.4631 | - |
| 4.7914 | 108890 | 0.4598 | - |
| 4.7919 | 108900 | 0.4944 | - |
| 4.7923 | 108910 | 0.4857 | - |
| 4.7927 | 108920 | 0.4802 | - |
| 4.7932 | 108930 | 0.4788 | - |
| 4.7936 | 108940 | 0.473 | - |
| 4.7941 | 108950 | 0.4966 | - |
| 4.7945 | 108960 | 0.4845 | - |
| 4.7949 | 108970 | 0.4732 | - |
| 4.7954 | 108980 | 0.4749 | - |
| 4.7958 | 108990 | 0.4975 | - |
| 4.7963 | 109000 | 0.4812 | - |
| 4.7967 | 109010 | 0.4489 | - |
| 4.7971 | 109020 | 0.4791 | - |
| 4.7976 | 109030 | 0.4701 | - |
| 4.7980 | 109040 | 0.4691 | - |
| 4.7985 | 109050 | 0.4798 | - |
| 4.7989 | 109060 | 0.4769 | - |
| 4.7993 | 109070 | 0.4867 | - |
| 4.7998 | 109080 | 0.4873 | - |
| 4.8002 | 109090 | 0.4789 | - |
| 4.8007 | 109100 | 0.4458 | - |
| 4.8011 | 109110 | 0.4816 | - |
| 4.8015 | 109120 | 0.4718 | - |
| 4.8020 | 109130 | 0.4983 | - |
| 4.8024 | 109140 | 0.4901 | - |
| 4.8029 | 109150 | 0.4701 | - |
| 4.8030 | 109152 | - | 1.2595 |
| 4.8033 | 109160 | 0.4656 | - |
| 4.8037 | 109170 | 0.4845 | - |
| 4.8042 | 109180 | 0.4523 | - |
| 4.8046 | 109190 | 0.4638 | - |
| 4.8051 | 109200 | 0.4744 | - |
| 4.8055 | 109210 | 0.4916 | - |
| 4.8059 | 109220 | 0.4891 | - |
| 4.8064 | 109230 | 0.4787 | - |
| 4.8068 | 109240 | 0.4762 | - |
| 4.8073 | 109250 | 0.4643 | - |
| 4.8077 | 109260 | 0.4882 | - |
| 4.8081 | 109270 | 0.4844 | - |
| 4.8086 | 109280 | 0.4761 | - |
| 4.8090 | 109290 | 0.4708 | - |
| 4.8095 | 109300 | 0.4795 | - |
| 4.8099 | 109310 | 0.463 | - |
| 4.8103 | 109320 | 0.4636 | - |
| 4.8108 | 109330 | 0.4934 | - |
| 4.8112 | 109340 | 0.4787 | - |
| 4.8117 | 109350 | 0.4652 | - |
| 4.8121 | 109360 | 0.4929 | - |
| 4.8125 | 109370 | 0.4693 | - |
| 4.8130 | 109380 | 0.4949 | - |
| 4.8134 | 109390 | 0.461 | - |
| 4.8139 | 109400 | 0.4952 | - |
| 4.8143 | 109410 | 0.4669 | - |
| 4.8147 | 109420 | 0.4759 | - |
| 4.8152 | 109430 | 0.4672 | - |
| 4.8156 | 109440 | 0.4818 | - |
| 4.8161 | 109450 | 0.4953 | - |
| 4.8165 | 109460 | 0.4977 | - |
| 4.8169 | 109470 | 0.4703 | - |
| 4.8174 | 109480 | 0.5002 | - |
| 4.8178 | 109490 | 0.4674 | - |
| 4.8183 | 109500 | 0.4626 | - |
| 4.8187 | 109510 | 0.4886 | - |
| 4.8191 | 109520 | 0.4723 | - |
| 4.8196 | 109530 | 0.4569 | - |
| 4.8200 | 109540 | 0.4951 | - |
| 4.8205 | 109550 | 0.4666 | - |
| 4.8209 | 109560 | 0.5047 | - |
| 4.8213 | 109570 | 0.4802 | - |
| 4.8218 | 109580 | 0.4765 | - |
| 4.8222 | 109590 | 0.4736 | - |
| 4.8227 | 109600 | 0.4526 | - |
| 4.8231 | 109610 | 0.4594 | - |
| 4.8236 | 109620 | 0.4616 | - |
| 4.8240 | 109630 | 0.4674 | - |
| 4.8244 | 109640 | 0.4774 | - |
| 4.8249 | 109650 | 0.4834 | - |
| 4.8253 | 109660 | 0.4773 | - |
| 4.8258 | 109670 | 0.4797 | - |
| 4.8262 | 109680 | 0.4633 | - |
| 4.8266 | 109690 | 0.472 | - |
| 4.8271 | 109700 | 0.4755 | - |
| 4.8275 | 109710 | 0.4761 | - |
| 4.8280 | 109720 | 0.477 | - |
| 4.8284 | 109730 | 0.4787 | - |
| 4.8288 | 109740 | 0.4862 | - |
| 4.8293 | 109750 | 0.4916 | - |
| 4.8297 | 109760 | 0.4572 | - |
| 4.8302 | 109770 | 0.4859 | - |
| 4.8306 | 109780 | 0.4812 | - |
| 4.8310 | 109790 | 0.4703 | - |
| 4.8315 | 109800 | 0.4807 | - |
| 4.8319 | 109810 | 0.4731 | - |
| 4.8324 | 109820 | 0.4795 | - |
| 4.8328 | 109830 | 0.4696 | - |
| 4.8332 | 109840 | 0.4684 | - |
| 4.8337 | 109850 | 0.4581 | - |
| 4.8341 | 109860 | 0.4691 | - |
| 4.8346 | 109870 | 0.4829 | - |
| 4.8350 | 109880 | 0.4767 | - |
| 4.8354 | 109890 | 0.4666 | - |
| 4.8359 | 109900 | 0.4641 | - |
| 4.8363 | 109910 | 0.4903 | - |
| 4.8368 | 109920 | 0.4851 | - |
| 4.8372 | 109930 | 0.487 | - |
| 4.8376 | 109940 | 0.4702 | - |
| 4.8381 | 109950 | 0.4968 | - |
| 4.8385 | 109960 | 0.4829 | - |
| 4.8390 | 109970 | 0.4836 | - |
| 4.8394 | 109980 | 0.4687 | - |
| 4.8398 | 109990 | 0.4616 | - |
| 4.8403 | 110000 | 0.4854 | - |
| 4.8407 | 110010 | 0.4816 | - |
| 4.8412 | 110020 | 0.5018 | - |
| 4.8416 | 110030 | 0.4591 | - |
| 4.8420 | 110040 | 0.478 | - |
| 4.8425 | 110050 | 0.4653 | - |
| 4.8429 | 110060 | 0.4628 | - |
| 4.8434 | 110070 | 0.4778 | - |
| 4.8438 | 110080 | 0.4808 | - |
| 4.8442 | 110090 | 0.4861 | - |
| 4.8447 | 110100 | 0.4884 | - |
| 4.8451 | 110110 | 0.5016 | - |
| 4.8456 | 110120 | 0.4706 | - |
| 4.8460 | 110130 | 0.4716 | - |
| 4.8464 | 110140 | 0.4519 | - |
| 4.8469 | 110150 | 0.4949 | - |
| 4.8473 | 110160 | 0.4757 | - |
| 4.8478 | 110170 | 0.4853 | - |
| 4.8482 | 110180 | 0.4871 | - |
| 4.8486 | 110190 | 0.483 | - |
| 4.8491 | 110200 | 0.5004 | - |
| 4.8495 | 110210 | 0.4545 | - |
| 4.8500 | 110220 | 0.4985 | - |
| 4.8504 | 110230 | 0.4811 | - |
| 4.8508 | 110240 | 0.4669 | - |
| 4.8513 | 110250 | 0.4886 | - |
| 4.8517 | 110260 | 0.4671 | - |
| 4.8522 | 110270 | 0.4688 | - |
| 4.8526 | 110280 | 0.4595 | - |
| 4.8530 | 110289 | - | 1.2607 |
| 4.8530 | 110290 | 0.4727 | - |
| 4.8535 | 110300 | 0.4826 | - |
| 4.8539 | 110310 | 0.4985 | - |
| 4.8544 | 110320 | 0.468 | - |
| 4.8548 | 110330 | 0.4758 | - |
| 4.8552 | 110340 | 0.4481 | - |
| 4.8557 | 110350 | 0.5127 | - |
| 4.8561 | 110360 | 0.4721 | - |
| 4.8566 | 110370 | 0.4543 | - |
| 4.8570 | 110380 | 0.4938 | - |
| 4.8574 | 110390 | 0.4745 | - |
| 4.8579 | 110400 | 0.4813 | - |
| 4.8583 | 110410 | 0.4852 | - |
| 4.8588 | 110420 | 0.4821 | - |
| 4.8592 | 110430 | 0.4851 | - |
| 4.8596 | 110440 | 0.4755 | - |
| 4.8601 | 110450 | 0.4742 | - |
| 4.8605 | 110460 | 0.4787 | - |
| 4.8610 | 110470 | 0.4496 | - |
| 4.8614 | 110480 | 0.4763 | - |
| 4.8618 | 110490 | 0.4697 | - |
| 4.8623 | 110500 | 0.4676 | - |
| 4.8627 | 110510 | 0.4874 | - |
| 4.8632 | 110520 | 0.4859 | - |
| 4.8636 | 110530 | 0.4549 | - |
| 4.8640 | 110540 | 0.4642 | - |
| 4.8645 | 110550 | 0.466 | - |
| 4.8649 | 110560 | 0.4567 | - |
| 4.8654 | 110570 | 0.4777 | - |
| 4.8658 | 110580 | 0.4808 | - |
| 4.8662 | 110590 | 0.4755 | - |
| 4.8667 | 110600 | 0.4815 | - |
| 4.8671 | 110610 | 0.4656 | - |
| 4.8676 | 110620 | 0.4768 | - |
| 4.8680 | 110630 | 0.4512 | - |
| 4.8684 | 110640 | 0.4724 | - |
| 4.8689 | 110650 | 0.4534 | - |
| 4.8693 | 110660 | 0.4593 | - |
| 4.8698 | 110670 | 0.463 | - |
| 4.8702 | 110680 | 0.4827 | - |
| 4.8706 | 110690 | 0.4555 | - |
| 4.8711 | 110700 | 0.4857 | - |
| 4.8715 | 110710 | 0.4692 | - |
| 4.8720 | 110720 | 0.4678 | - |
| 4.8724 | 110730 | 0.4755 | - |
| 4.8728 | 110740 | 0.4581 | - |
| 4.8733 | 110750 | 0.4789 | - |
| 4.8737 | 110760 | 0.4793 | - |
| 4.8742 | 110770 | 0.4923 | - |
| 4.8746 | 110780 | 0.4734 | - |
| 4.8750 | 110790 | 0.4612 | - |
| 4.8755 | 110800 | 0.4912 | - |
| 4.8759 | 110810 | 0.4933 | - |
| 4.8764 | 110820 | 0.4737 | - |
| 4.8768 | 110830 | 0.467 | - |
| 4.8772 | 110840 | 0.4876 | - |
| 4.8777 | 110850 | 0.4837 | - |
| 4.8781 | 110860 | 0.473 | - |
| 4.8786 | 110870 | 0.4761 | - |
| 4.8790 | 110880 | 0.4913 | - |
| 4.8794 | 110890 | 0.4677 | - |
| 4.8799 | 110900 | 0.4844 | - |
| 4.8803 | 110910 | 0.4669 | - |
| 4.8808 | 110920 | 0.475 | - |
| 4.8812 | 110930 | 0.4778 | - |
| 4.8816 | 110940 | 0.4815 | - |
| 4.8821 | 110950 | 0.4918 | - |
| 4.8825 | 110960 | 0.4707 | - |
| 4.8830 | 110970 | 0.4741 | - |
| 4.8834 | 110980 | 0.5028 | - |
| 4.8838 | 110990 | 0.4735 | - |
| 4.8843 | 111000 | 0.4973 | - |
| 4.8847 | 111010 | 0.4673 | - |
| 4.8852 | 111020 | 0.4816 | - |
| 4.8856 | 111030 | 0.4584 | - |
| 4.8860 | 111040 | 0.453 | - |
| 4.8865 | 111050 | 0.4699 | - |
| 4.8869 | 111060 | 0.4641 | - |
| 4.8874 | 111070 | 0.4587 | - |
| 4.8878 | 111080 | 0.4828 | - |
| 4.8882 | 111090 | 0.4686 | - |
| 4.8887 | 111100 | 0.4742 | - |
| 4.8891 | 111110 | 0.4558 | - |
| 4.8896 | 111120 | 0.4988 | - |
| 4.8900 | 111130 | 0.4864 | - |
| 4.8904 | 111140 | 0.4722 | - |
| 4.8909 | 111150 | 0.4494 | - |
| 4.8913 | 111160 | 0.4726 | - |
| 4.8918 | 111170 | 0.4531 | - |
| 4.8922 | 111180 | 0.4882 | - |
| 4.8926 | 111190 | 0.4575 | - |
| 4.8931 | 111200 | 0.4703 | - |
| 4.8935 | 111210 | 0.4643 | - |
| 4.8940 | 111220 | 0.4827 | - |
| 4.8944 | 111230 | 0.4711 | - |
| 4.8948 | 111240 | 0.4589 | - |
| 4.8953 | 111250 | 0.485 | - |
| 4.8957 | 111260 | 0.4804 | - |
| 4.8962 | 111270 | 0.4439 | - |
| 4.8966 | 111280 | 0.4743 | - |
| 4.8970 | 111290 | 0.4799 | - |
| 4.8975 | 111300 | 0.4653 | - |
| 4.8979 | 111310 | 0.4941 | - |
| 4.8984 | 111320 | 0.4618 | - |
| 4.8988 | 111330 | 0.4753 | - |
| 4.8992 | 111340 | 0.484 | - |
| 4.8997 | 111350 | 0.4785 | - |
| 4.9001 | 111360 | 0.4871 | - |
| 4.9006 | 111370 | 0.4626 | - |
| 4.9010 | 111380 | 0.4943 | - |
| 4.9014 | 111390 | 0.4885 | - |
| 4.9019 | 111400 | 0.4798 | - |
| 4.9023 | 111410 | 0.4837 | - |
| 4.9028 | 111420 | 0.4733 | - |
| 4.9030 | 111426 | - | 1.2603 |
| 4.9032 | 111430 | 0.4807 | - |
| 4.9036 | 111440 | 0.4902 | - |
| 4.9041 | 111450 | 0.4677 | - |
| 4.9045 | 111460 | 0.4815 | - |
| 4.9050 | 111470 | 0.4674 | - |
| 4.9054 | 111480 | 0.4878 | - |
| 4.9058 | 111490 | 0.4574 | - |
| 4.9063 | 111500 | 0.4699 | - |
| 4.9067 | 111510 | 0.484 | - |
| 4.9072 | 111520 | 0.4876 | - |
| 4.9076 | 111530 | 0.4758 | - |
| 4.9080 | 111540 | 0.458 | - |
| 4.9085 | 111550 | 0.4681 | - |
| 4.9089 | 111560 | 0.4815 | - |
| 4.9094 | 111570 | 0.4676 | - |
| 4.9098 | 111580 | 0.4651 | - |
| 4.9102 | 111590 | 0.4532 | - |
| 4.9107 | 111600 | 0.48 | - |
| 4.9111 | 111610 | 0.4988 | - |
| 4.9116 | 111620 | 0.4623 | - |
| 4.9120 | 111630 | 0.4868 | - |
| 4.9124 | 111640 | 0.4718 | - |
| 4.9129 | 111650 | 0.4846 | - |
| 4.9133 | 111660 | 0.4547 | - |
| 4.9138 | 111670 | 0.491 | - |
| 4.9142 | 111680 | 0.4834 | - |
| 4.9146 | 111690 | 0.4864 | - |
| 4.9151 | 111700 | 0.4706 | - |
| 4.9155 | 111710 | 0.4732 | - |
| 4.9160 | 111720 | 0.4575 | - |
| 4.9164 | 111730 | 0.4761 | - |
| 4.9168 | 111740 | 0.4848 | - |
| 4.9173 | 111750 | 0.4748 | - |
| 4.9177 | 111760 | 0.4873 | - |
| 4.9182 | 111770 | 0.4561 | - |
| 4.9186 | 111780 | 0.4928 | - |
| 4.9190 | 111790 | 0.4813 | - |
| 4.9195 | 111800 | 0.4766 | - |
| 4.9199 | 111810 | 0.4764 | - |
| 4.9204 | 111820 | 0.4423 | - |
| 4.9208 | 111830 | 0.4877 | - |
| 4.9212 | 111840 | 0.4587 | - |
| 4.9217 | 111850 | 0.4941 | - |
| 4.9221 | 111860 | 0.4841 | - |
| 4.9226 | 111870 | 0.4725 | - |
| 4.9230 | 111880 | 0.501 | - |
| 4.9234 | 111890 | 0.4562 | - |
| 4.9239 | 111900 | 0.4752 | - |
| 4.9243 | 111910 | 0.4876 | - |
| 4.9248 | 111920 | 0.4877 | - |
| 4.9252 | 111930 | 0.4803 | - |
| 4.9256 | 111940 | 0.4617 | - |
| 4.9261 | 111950 | 0.4801 | - |
| 4.9265 | 111960 | 0.4807 | - |
| 4.9270 | 111970 | 0.4769 | - |
| 4.9274 | 111980 | 0.4793 | - |
| 4.9278 | 111990 | 0.4845 | - |
| 4.9283 | 112000 | 0.4903 | - |
| 4.9287 | 112010 | 0.4665 | - |
| 4.9292 | 112020 | 0.4654 | - |
| 4.9296 | 112030 | 0.4741 | - |
| 4.9300 | 112040 | 0.4635 | - |
| 4.9305 | 112050 | 0.4757 | - |
| 4.9309 | 112060 | 0.5063 | - |
| 4.9314 | 112070 | 0.4591 | - |
| 4.9318 | 112080 | 0.4725 | - |
| 4.9322 | 112090 | 0.4821 | - |
| 4.9327 | 112100 | 0.4732 | - |
| 4.9331 | 112110 | 0.4484 | - |
| 4.9336 | 112120 | 0.4517 | - |
| 4.9340 | 112130 | 0.4764 | - |
| 4.9344 | 112140 | 0.494 | - |
| 4.9349 | 112150 | 0.492 | - |
| 4.9353 | 112160 | 0.4605 | - |
| 4.9358 | 112170 | 0.4682 | - |
| 4.9362 | 112180 | 0.4846 | - |
| 4.9366 | 112190 | 0.4966 | - |
| 4.9371 | 112200 | 0.4566 | - |
| 4.9375 | 112210 | 0.4569 | - |
| 4.9380 | 112220 | 0.4731 | - |
| 4.9384 | 112230 | 0.4659 | - |
| 4.9388 | 112240 | 0.4594 | - |
| 4.9393 | 112250 | 0.4599 | - |
| 4.9397 | 112260 | 0.4643 | - |
| 4.9402 | 112270 | 0.482 | - |
| 4.9406 | 112280 | 0.4489 | - |
| 4.9410 | 112290 | 0.4976 | - |
| 4.9415 | 112300 | 0.458 | - |
| 4.9419 | 112310 | 0.473 | - |
| 4.9424 | 112320 | 0.4799 | - |
| 4.9428 | 112330 | 0.4821 | - |
| 4.9432 | 112340 | 0.4704 | - |
| 4.9437 | 112350 | 0.4603 | - |
| 4.9441 | 112360 | 0.4751 | - |
| 4.9446 | 112370 | 0.5101 | - |
| 4.9450 | 112380 | 0.4974 | - |
| 4.9454 | 112390 | 0.4672 | - |
| 4.9459 | 112400 | 0.4812 | - |
| 4.9463 | 112410 | 0.4882 | - |
| 4.9468 | 112420 | 0.4735 | - |
| 4.9472 | 112430 | 0.4812 | - |
| 4.9476 | 112440 | 0.458 | - |
| 4.9481 | 112450 | 0.4874 | - |
| 4.9485 | 112460 | 0.4535 | - |
| 4.9490 | 112470 | 0.4811 | - |
| 4.9494 | 112480 | 0.4795 | - |
| 4.9498 | 112490 | 0.4994 | - |
| 4.9503 | 112500 | 0.4498 | - |
| 4.9507 | 112510 | 0.4672 | - |
| 4.9512 | 112520 | 0.4861 | - |
| 4.9516 | 112530 | 0.464 | - |
| 4.9520 | 112540 | 0.4611 | - |
| 4.9525 | 112550 | 0.4804 | - |
| 4.9529 | 112560 | 0.4979 | - |
| 4.9530 | 112563 | - | 1.2611 |
| 4.9534 | 112570 | 0.4769 | - |
| 4.9538 | 112580 | 0.4854 | - |
| 4.9542 | 112590 | 0.4864 | - |
| 4.9547 | 112600 | 0.5016 | - |
| 4.9551 | 112610 | 0.4948 | - |
| 4.9556 | 112620 | 0.4697 | - |
| 4.9560 | 112630 | 0.4512 | - |
| 4.9564 | 112640 | 0.4635 | - |
| 4.9569 | 112650 | 0.4336 | - |
| 4.9573 | 112660 | 0.4716 | - |
| 4.9578 | 112670 | 0.4724 | - |
| 4.9582 | 112680 | 0.4628 | - |
| 4.9586 | 112690 | 0.4722 | - |
| 4.9591 | 112700 | 0.4689 | - |
| 4.9595 | 112710 | 0.4758 | - |
| 4.9600 | 112720 | 0.4934 | - |
| 4.9604 | 112730 | 0.4693 | - |
| 4.9608 | 112740 | 0.4702 | - |
| 4.9613 | 112750 | 0.4794 | - |
| 4.9617 | 112760 | 0.4855 | - |
| 4.9622 | 112770 | 0.4635 | - |
| 4.9626 | 112780 | 0.4706 | - |
| 4.9630 | 112790 | 0.4563 | - |
| 4.9635 | 112800 | 0.4573 | - |
| 4.9639 | 112810 | 0.4581 | - |
| 4.9644 | 112820 | 0.4784 | - |
| 4.9648 | 112830 | 0.4882 | - |
| 4.9652 | 112840 | 0.4754 | - |
| 4.9657 | 112850 | 0.4775 | - |
| 4.9661 | 112860 | 0.4808 | - |
| 4.9666 | 112870 | 0.4691 | - |
| 4.9670 | 112880 | 0.4911 | - |
| 4.9674 | 112890 | 0.4681 | - |
| 4.9679 | 112900 | 0.4825 | - |
| 4.9683 | 112910 | 0.4467 | - |
| 4.9688 | 112920 | 0.4733 | - |
| 4.9692 | 112930 | 0.4825 | - |
| 4.9696 | 112940 | 0.49 | - |
| 4.9701 | 112950 | 0.4584 | - |
| 4.9705 | 112960 | 0.4849 | - |
| 4.9710 | 112970 | 0.5077 | - |
| 4.9714 | 112980 | 0.462 | - |
| 4.9718 | 112990 | 0.4823 | - |
| 4.9723 | 113000 | 0.4838 | - |
| 4.9727 | 113010 | 0.4538 | - |
| 4.9732 | 113020 | 0.4812 | - |
| 4.9736 | 113030 | 0.4525 | - |
| 4.9740 | 113040 | 0.467 | - |
| 4.9745 | 113050 | 0.4642 | - |
| 4.9749 | 113060 | 0.4625 | - |
| 4.9754 | 113070 | 0.4775 | - |
| 4.9758 | 113080 | 0.4823 | - |
| 4.9762 | 113090 | 0.4663 | - |
| 4.9767 | 113100 | 0.4813 | - |
| 4.9771 | 113110 | 0.4687 | - |
| 4.9776 | 113120 | 0.5004 | - |
| 4.9780 | 113130 | 0.4938 | - |
| 4.9784 | 113140 | 0.4819 | - |
| 4.9789 | 113150 | 0.4665 | - |
| 4.9793 | 113160 | 0.4539 | - |
| 4.9798 | 113170 | 0.4368 | - |
| 4.9802 | 113180 | 0.4844 | - |
| 4.9806 | 113190 | 0.5041 | - |
| 4.9811 | 113200 | 0.4905 | - |
| 4.9815 | 113210 | 0.4775 | - |
| 4.9820 | 113220 | 0.4724 | - |
| 4.9824 | 113230 | 0.4744 | - |
| 4.9828 | 113240 | 0.4745 | - |
| 4.9833 | 113250 | 0.4641 | - |
| 4.9837 | 113260 | 0.4567 | - |
| 4.9842 | 113270 | 0.4705 | - |
| 4.9846 | 113280 | 0.4556 | - |
| 4.9850 | 113290 | 0.4655 | - |
| 4.9855 | 113300 | 0.4724 | - |
| 4.9859 | 113310 | 0.48 | - |
| 4.9864 | 113320 | 0.4555 | - |
| 4.9868 | 113330 | 0.4755 | - |
| 4.9872 | 113340 | 0.497 | - |
| 4.9877 | 113350 | 0.467 | - |
| 4.9881 | 113360 | 0.4767 | - |
| 4.9886 | 113370 | 0.4862 | - |
| 4.9890 | 113380 | 0.4905 | - |
| 4.9894 | 113390 | 0.4795 | - |
| 4.9899 | 113400 | 0.461 | - |
| 4.9903 | 113410 | 0.486 | - |
| 4.9908 | 113420 | 0.4861 | - |
| 4.9912 | 113430 | 0.4627 | - |
| 4.9916 | 113440 | 0.4692 | - |
| 4.9921 | 113450 | 0.4798 | - |
| 4.9925 | 113460 | 0.4725 | - |
| 4.9930 | 113470 | 0.4719 | - |
| 4.9934 | 113480 | 0.4837 | - |
| 4.9938 | 113490 | 0.4652 | - |
| 4.9943 | 113500 | 0.4634 | - |
| 4.9947 | 113510 | 0.4617 | - |
| 4.9952 | 113520 | 0.459 | - |
| 4.9956 | 113530 | 0.4685 | - |
| 4.9960 | 113540 | 0.4902 | - |
| 4.9965 | 113550 | 0.4713 | - |
| 4.9969 | 113560 | 0.4819 | - |
| 4.9974 | 113570 | 0.4578 | - |
| 4.9978 | 113580 | 0.4712 | - |
| 4.9982 | 113590 | 0.4552 | - |
| 4.9987 | 113600 | 0.4529 | - |
| 4.9991 | 113610 | 0.467 | - |
| 4.9996 | 113620 | 0.4618 | - |
| 5.0 | 113630 | 0.4417 | - |