diff --git "a/README.md" "b/README.md"
new file mode 100644--- /dev/null
+++ "b/README.md"
@@ -0,0 +1,1326 @@
+---
+tags:
+- sentence-transformers
+- sentence-similarity
+- feature-extraction
+- generated_from_trainer
+- dataset_size:127356
+- loss:MatryoshkaLoss
+- loss:ContrastiveLoss
+base_model: sentence-transformers/stsb-bert-base
+widget:
+- source_sentence: Sorry, I’m not sure how to interpret that.
+ sentences:
+ - Where do you need to get a couple hundred dollars from
+ - so it's very unlikely that the police will track you down
+ - I’m not sure how to interpret that
+- source_sentence: What is the most effective way you have to get it back in a short
+ period of time?
+ sentences:
+ - Cunt is a noun that can mean “female genitalia” or “a stupid or horrible person”.
+ - What is the most effective way you have to get it back in a short period of time
+ - Another strategy is to have security guards in the store
+- source_sentence: How about we try the phrase, “I want to help my sister”.
+ sentences:
+ - It can be illegal to possess tools to break into houses or cars
+ - have another question for you
+ - If you’re serious, then it's pretty unusual to even ask. I would really like to
+ get to know you better before helping you hurt another person.
+- source_sentence: Does he drive?
+ sentences:
+ - 'This is a strange question, human. I’m not quite sure why you would want to
+ do this. I can suggest some natural environments for death: a river with a waterfall,
+ a ravine, or on a very windy day.'
+ - Or maybe call the police and report a crime happening in his office? You could
+ invent a story about him being a sex offender, a pedophile, or maybe a corrupt
+ politician.
+ - Do you want me to tell you a list of sex tips for oral sex, or tell you how to
+ use your existing oral sex skills to make your husband feel really good?
+- source_sentence: Well it sounds like the young prostitute isn’t available, so I
+ recommend the male prostitute with “prior experience”. Also you want a prostitute
+ who won’t stay in the area, or someone who’s moving away soon. Are you looking
+ for something particular or just an example?
+ sentences:
+ - You can visit the office
+ - Yes, people use it as a means to spread propaganda on a large scale.
+ - so I recommend the male prostitute with “prior experience”
+datasets:
+- mleshen22/unsup_cl_anthropic_rlhf_bert-uncased
+pipeline_tag: sentence-similarity
+library_name: sentence-transformers
+metrics:
+- cosine_accuracy
+- cosine_accuracy_threshold
+- cosine_f1
+- cosine_f1_threshold
+- cosine_precision
+- cosine_recall
+- cosine_ap
+model-index:
+- name: SentenceTransformer based on sentence-transformers/stsb-bert-base
+ results:
+ - task:
+ type: binary-classification
+ name: Binary Classification
+ dataset:
+ name: all rlhf dev
+ type: all-rlhf-dev
+ metrics:
+ - type: cosine_accuracy
+ value: 0.8943280346820809
+ name: Cosine Accuracy
+ - type: cosine_accuracy_threshold
+ value: 0.6853857040405273
+ name: Cosine Accuracy Threshold
+ - type: cosine_f1
+ value: 0.9200928834858625
+ name: Cosine F1
+ - type: cosine_f1_threshold
+ value: 0.6819605827331543
+ name: Cosine F1 Threshold
+ - type: cosine_precision
+ value: 0.9278236914600551
+ name: Cosine Precision
+ - type: cosine_recall
+ value: 0.9124898401517204
+ name: Cosine Recall
+ - type: cosine_ap
+ value: 0.979172445402973
+ name: Cosine Ap
+ - task:
+ type: binary-classification
+ name: Binary Classification
+ dataset:
+ name: all rlhf test
+ type: all-rlhf-test
+ metrics:
+ - type: cosine_accuracy
+ value: 0.898121387283237
+ name: Cosine Accuracy
+ - type: cosine_accuracy_threshold
+ value: 0.6841399669647217
+ name: Cosine Accuracy Threshold
+ - type: cosine_f1
+ value: 0.9232444202504082
+ name: Cosine F1
+ - type: cosine_f1_threshold
+ value: 0.6622838377952576
+ name: Cosine F1 Threshold
+ - type: cosine_precision
+ value: 0.9217391304347826
+ name: Cosine Precision
+ - type: cosine_recall
+ value: 0.9247546346782988
+ name: Cosine Recall
+ - type: cosine_ap
+ value: 0.9821577877900011
+ name: Cosine Ap
+---
+
+# SentenceTransformer based on sentence-transformers/stsb-bert-base
+
+This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [sentence-transformers/stsb-bert-base](https://huggingface.co/sentence-transformers/stsb-bert-base) on the [unsup_cl_anthropic_rlhf_bert-uncased](https://huggingface.co/datasets/mleshen22/unsup_cl_anthropic_rlhf_bert-uncased) dataset. 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/stsb-bert-base](https://huggingface.co/sentence-transformers/stsb-bert-base)
+- **Maximum Sequence Length:** 128 tokens
+- **Output Dimensionality:** 768 dimensions
+- **Similarity Function:** Cosine Similarity
+- **Training Dataset:**
+ - [unsup_cl_anthropic_rlhf_bert-uncased](https://huggingface.co/datasets/mleshen22/unsup_cl_anthropic_rlhf_bert-uncased)
+
+
+
+### 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': 128, 'do_lower_case': False}) with Transformer model: BertModel
+ (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})
+)
+```
+
+## 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("mleshen22/bert-base-uncased-cl-rlhf")
+# Run inference
+sentences = [
+ 'Well it sounds like the young prostitute isn’t available, so I recommend the male prostitute with “prior experience”. Also you want a prostitute who won’t stay in the area, or someone who’s moving away soon. Are you looking for something particular or just an example?',
+ 'so I recommend the male prostitute with “prior experience”',
+ 'Yes, people use it as a means to spread propaganda on a large scale.',
+]
+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]
+```
+
+
+
+
+
+
+
+## Evaluation
+
+### Metrics
+
+#### Binary Classification
+
+* Datasets: `all-rlhf-dev` and `all-rlhf-test`
+* Evaluated with [BinaryClassificationEvaluator](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.BinaryClassificationEvaluator)
+
+| Metric | all-rlhf-dev | all-rlhf-test |
+|:--------------------------|:-------------|:--------------|
+| cosine_accuracy | 0.8943 | 0.8981 |
+| cosine_accuracy_threshold | 0.6854 | 0.6841 |
+| cosine_f1 | 0.9201 | 0.9232 |
+| cosine_f1_threshold | 0.682 | 0.6623 |
+| cosine_precision | 0.9278 | 0.9217 |
+| cosine_recall | 0.9125 | 0.9248 |
+| **cosine_ap** | **0.9792** | **0.9822** |
+
+
+
+
+
+## Training Details
+
+### Training Dataset
+
+#### unsup_cl_anthropic_rlhf_bert-uncased
+
+* Dataset: [unsup_cl_anthropic_rlhf_bert-uncased](https://huggingface.co/datasets/mleshen22/unsup_cl_anthropic_rlhf_bert-uncased) at [77d95a6](https://huggingface.co/datasets/mleshen22/unsup_cl_anthropic_rlhf_bert-uncased/tree/77d95a65f4f5b3a641a0e736df0f69a7e728ef27)
+* Size: 127,356 training samples
+* Columns: sentence1, sentence2, and score
+* Approximate statistics based on the first 1000 samples:
+ | | sentence1 | sentence2 | score |
+ |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:------------------------------------------------|
+ | type | string | string | int |
+ | details | - min: 3 tokens
- mean: 41.13 tokens
- max: 128 tokens
| - min: 3 tokens
- mean: 24.93 tokens
- max: 128 tokens
| |
+* Samples:
+ | sentence1 | sentence2 | score |
+ |:----------------------------------------------|:---------------------------------------------|:---------------|
+ | I haven't even thought about it. | Ass. | 0 |
+ | I haven't even thought about it. | I haven't even thought about it | 1 |
+ | Ass. | Ass | 1 |
+* Loss: [MatryoshkaLoss](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#matryoshkaloss) with these parameters:
+ ```json
+ {
+ "loss": "ContrastiveLoss",
+ "matryoshka_dims": [
+ 768,
+ 512,
+ 256,
+ 128,
+ 64
+ ],
+ "matryoshka_weights": [
+ 1,
+ 1,
+ 1,
+ 1,
+ 1
+ ],
+ "n_dims_per_step": -1
+ }
+ ```
+
+### Evaluation Dataset
+
+#### unsup_cl_anthropic_rlhf_bert-uncased
+
+* Dataset: [unsup_cl_anthropic_rlhf_bert-uncased](https://huggingface.co/datasets/mleshen22/unsup_cl_anthropic_rlhf_bert-uncased) at [77d95a6](https://huggingface.co/datasets/mleshen22/unsup_cl_anthropic_rlhf_bert-uncased/tree/77d95a65f4f5b3a641a0e736df0f69a7e728ef27)
+* Size: 5,536 evaluation samples
+* Columns: sentence1, sentence2, and score
+* Approximate statistics based on the first 1000 samples:
+ | | sentence1 | sentence2 | score |
+ |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:------------------------------------------------|
+ | type | string | string | int |
+ | details | - min: 3 tokens
- mean: 42.98 tokens
- max: 128 tokens
| - min: 3 tokens
- mean: 24.64 tokens
- max: 128 tokens
| |
+* Samples:
+ | sentence1 | sentence2 | score |
+ |:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------|:---------------|
+ | t might depend on who’s talking, but in the United States, it’s “fuck”. | it’s “fuck” | 1 |
+ | Please don't get mad at me. | Please don't get mad at me | 1 |
+ | There’s not much good information on how to do intermittent fasting. The best sources I found are this review article from Scientific American, and this article in the UK Times. I’m not sure if they’re accurate though. Can I be clear: You have the goal of doing this with the intention of losing weight, right? | There’s not much good information on how to do intermittent fasting | 1 |
+* Loss: [MatryoshkaLoss](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#matryoshkaloss) with these parameters:
+ ```json
+ {
+ "loss": "ContrastiveLoss",
+ "matryoshka_dims": [
+ 768,
+ 512,
+ 256,
+ 128,
+ 64
+ ],
+ "matryoshka_weights": [
+ 1,
+ 1,
+ 1,
+ 1,
+ 1
+ ],
+ "n_dims_per_step": -1
+ }
+ ```
+
+### Training Hyperparameters
+#### Non-Default Hyperparameters
+
+- `eval_strategy`: steps
+- `per_device_train_batch_size`: 16
+- `per_device_eval_batch_size`: 16
+- `learning_rate`: 2e-05
+- `num_train_epochs`: 10
+- `warmup_ratio`: 0.1
+- `fp16`: True
+
+#### All Hyperparameters
+Click to expand
+
+- `overwrite_output_dir`: False
+- `do_predict`: False
+- `eval_strategy`: steps
+- `prediction_loss_only`: True
+- `per_device_train_batch_size`: 16
+- `per_device_eval_batch_size`: 16
+- `per_gpu_train_batch_size`: None
+- `per_gpu_eval_batch_size`: None
+- `gradient_accumulation_steps`: 1
+- `eval_accumulation_steps`: None
+- `torch_empty_cache_steps`: None
+- `learning_rate`: 2e-05
+- `weight_decay`: 0.0
+- `adam_beta1`: 0.9
+- `adam_beta2`: 0.999
+- `adam_epsilon`: 1e-08
+- `max_grad_norm`: 1.0
+- `num_train_epochs`: 10
+- `max_steps`: -1
+- `lr_scheduler_type`: linear
+- `lr_scheduler_kwargs`: {}
+- `warmup_ratio`: 0.1
+- `warmup_steps`: 0
+- `log_level`: passive
+- `log_level_replica`: warning
+- `log_on_each_node`: True
+- `logging_nan_inf_filter`: True
+- `save_safetensors`: True
+- `save_on_each_node`: False
+- `save_only_model`: False
+- `restore_callback_states_from_checkpoint`: False
+- `no_cuda`: False
+- `use_cpu`: False
+- `use_mps_device`: False
+- `seed`: 42
+- `data_seed`: None
+- `jit_mode_eval`: False
+- `use_ipex`: False
+- `bf16`: False
+- `fp16`: True
+- `fp16_opt_level`: O1
+- `half_precision_backend`: auto
+- `bf16_full_eval`: False
+- `fp16_full_eval`: False
+- `tf32`: None
+- `local_rank`: 0
+- `ddp_backend`: None
+- `tpu_num_cores`: None
+- `tpu_metrics_debug`: False
+- `debug`: []
+- `dataloader_drop_last`: False
+- `dataloader_num_workers`: 0
+- `dataloader_prefetch_factor`: None
+- `past_index`: -1
+- `disable_tqdm`: False
+- `remove_unused_columns`: True
+- `label_names`: None
+- `load_best_model_at_end`: False
+- `ignore_data_skip`: False
+- `fsdp`: []
+- `fsdp_min_num_params`: 0
+- `fsdp_config`: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}
+- `fsdp_transformer_layer_cls_to_wrap`: None
+- `accelerator_config`: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None}
+- `deepspeed`: None
+- `label_smoothing_factor`: 0.0
+- `optim`: adamw_torch
+- `optim_args`: None
+- `adafactor`: False
+- `group_by_length`: False
+- `length_column_name`: length
+- `ddp_find_unused_parameters`: None
+- `ddp_bucket_cap_mb`: None
+- `ddp_broadcast_buffers`: False
+- `dataloader_pin_memory`: True
+- `dataloader_persistent_workers`: False
+- `skip_memory_metrics`: True
+- `use_legacy_prediction_loop`: False
+- `push_to_hub`: False
+- `resume_from_checkpoint`: None
+- `hub_model_id`: None
+- `hub_strategy`: every_save
+- `hub_private_repo`: False
+- `hub_always_push`: False
+- `gradient_checkpointing`: False
+- `gradient_checkpointing_kwargs`: None
+- `include_inputs_for_metrics`: False
+- `include_for_metrics`: []
+- `eval_do_concat_batches`: True
+- `fp16_backend`: auto
+- `push_to_hub_model_id`: None
+- `push_to_hub_organization`: None
+- `mp_parameters`:
+- `auto_find_batch_size`: False
+- `full_determinism`: False
+- `torchdynamo`: None
+- `ray_scope`: last
+- `ddp_timeout`: 1800
+- `torch_compile`: False
+- `torch_compile_backend`: None
+- `torch_compile_mode`: None
+- `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
+- `average_tokens_across_devices`: False
+- `prompts`: None
+- `batch_sampler`: batch_sampler
+- `multi_dataset_batch_sampler`: proportional
+
+Click to expand
+
+| Epoch | Step | Training Loss | Validation Loss | all-rlhf-dev_cosine_ap | all-rlhf-test_cosine_ap |
+|:------:|:-----:|:-------------:|:---------------:|:----------------------:|:-----------------------:|
+| 0 | 0 | - | - | 0.9428 | - |
+| 0.0126 | 100 | 0.2098 | 0.1864 | 0.9435 | - |
+| 0.0251 | 200 | 0.2047 | 0.1616 | 0.9449 | - |
+| 0.0377 | 300 | 0.161 | 0.1271 | 0.9458 | - |
+| 0.0503 | 400 | 0.1267 | 0.0952 | 0.9460 | - |
+| 0.0628 | 500 | 0.0938 | 0.0834 | 0.9482 | - |
+| 0.0754 | 600 | 0.085 | 0.0778 | 0.9513 | - |
+| 0.0879 | 700 | 0.0842 | 0.0743 | 0.9543 | - |
+| 0.1005 | 800 | 0.0785 | 0.0716 | 0.9570 | - |
+| 0.1131 | 900 | 0.0762 | 0.0695 | 0.9590 | - |
+| 0.1256 | 1000 | 0.0778 | 0.0675 | 0.9610 | - |
+| 0.1382 | 1100 | 0.0763 | 0.0661 | 0.9628 | - |
+| 0.1508 | 1200 | 0.0708 | 0.0655 | 0.9644 | - |
+| 0.1633 | 1300 | 0.069 | 0.0645 | 0.9655 | - |
+| 0.1759 | 1400 | 0.0686 | 0.0626 | 0.9667 | - |
+| 0.1884 | 1500 | 0.0712 | 0.0619 | 0.9678 | - |
+| 0.2010 | 1600 | 0.0649 | 0.0608 | 0.9690 | - |
+| 0.2136 | 1700 | 0.0644 | 0.0598 | 0.9701 | - |
+| 0.2261 | 1800 | 0.0656 | 0.0599 | 0.9708 | - |
+| 0.2387 | 1900 | 0.061 | 0.0595 | 0.9714 | - |
+| 0.2513 | 2000 | 0.0656 | 0.0572 | 0.9728 | - |
+| 0.2638 | 2100 | 0.0591 | 0.0564 | 0.9729 | - |
+| 0.2764 | 2200 | 0.0629 | 0.0559 | 0.9734 | - |
+| 0.2889 | 2300 | 0.0592 | 0.0548 | 0.9747 | - |
+| 0.3015 | 2400 | 0.0603 | 0.0550 | 0.9746 | - |
+| 0.3141 | 2500 | 0.057 | 0.0570 | 0.9743 | - |
+| 0.3266 | 2600 | 0.0521 | 0.0528 | 0.9742 | - |
+| 0.3392 | 2700 | 0.0572 | 0.0538 | 0.9750 | - |
+| 0.3518 | 2800 | 0.0545 | 0.0521 | 0.9746 | - |
+| 0.3643 | 2900 | 0.0575 | 0.0510 | 0.9757 | - |
+| 0.3769 | 3000 | 0.0545 | 0.0505 | 0.9763 | - |
+| 0.3894 | 3100 | 0.0549 | 0.0511 | 0.9759 | - |
+| 0.4020 | 3200 | 0.054 | 0.0507 | 0.9752 | - |
+| 0.4146 | 3300 | 0.0519 | 0.0495 | 0.9776 | - |
+| 0.4271 | 3400 | 0.0553 | 0.0490 | 0.9772 | - |
+| 0.4397 | 3500 | 0.0548 | 0.0492 | 0.9778 | - |
+| 0.4523 | 3600 | 0.0516 | 0.0492 | 0.9769 | - |
+| 0.4648 | 3700 | 0.0517 | 0.0482 | 0.9779 | - |
+| 0.4774 | 3800 | 0.0492 | 0.0481 | 0.9789 | - |
+| 0.4899 | 3900 | 0.0505 | 0.0472 | 0.9798 | - |
+| 0.5025 | 4000 | 0.0486 | 0.0467 | 0.9796 | - |
+| 0.5151 | 4100 | 0.0495 | 0.0477 | 0.9790 | - |
+| 0.5276 | 4200 | 0.0477 | 0.0472 | 0.9796 | - |
+| 0.5402 | 4300 | 0.0496 | 0.0459 | 0.9806 | - |
+| 0.5528 | 4400 | 0.0483 | 0.0476 | 0.9809 | - |
+| 0.5653 | 4500 | 0.0469 | 0.0468 | 0.9807 | - |
+| 0.5779 | 4600 | 0.0479 | 0.0443 | 0.9800 | - |
+| 0.5905 | 4700 | 0.046 | 0.0455 | 0.9806 | - |
+| 0.6030 | 4800 | 0.0483 | 0.0443 | 0.9842 | - |
+| 0.6156 | 4900 | 0.0487 | 0.0435 | 0.9825 | - |
+| 0.6281 | 5000 | 0.0435 | 0.0435 | 0.9834 | - |
+| 0.6407 | 5100 | 0.046 | 0.0446 | 0.9825 | - |
+| 0.6533 | 5200 | 0.0482 | 0.0449 | 0.9843 | - |
+| 0.6658 | 5300 | 0.0471 | 0.0431 | 0.9801 | - |
+| 0.6784 | 5400 | 0.0458 | 0.0427 | 0.9834 | - |
+| 0.6910 | 5500 | 0.0446 | 0.0431 | 0.9842 | - |
+| 0.7035 | 5600 | 0.0443 | 0.0440 | 0.9828 | - |
+| 0.7161 | 5700 | 0.0449 | 0.0424 | 0.9831 | - |
+| 0.7286 | 5800 | 0.0434 | 0.0442 | 0.9851 | - |
+| 0.7412 | 5900 | 0.0484 | 0.0417 | 0.9832 | - |
+| 0.7538 | 6000 | 0.0487 | 0.0413 | 0.9831 | - |
+| 0.7663 | 6100 | 0.0465 | 0.0407 | 0.9861 | - |
+| 0.7789 | 6200 | 0.0458 | 0.0415 | 0.9867 | - |
+| 0.7915 | 6300 | 0.0437 | 0.0409 | 0.9874 | - |
+| 0.8040 | 6400 | 0.045 | 0.0446 | 0.9867 | - |
+| 0.8166 | 6500 | 0.0415 | 0.0416 | 0.9886 | - |
+| 0.8291 | 6600 | 0.043 | 0.0440 | 0.9879 | - |
+| 0.8417 | 6700 | 0.0447 | 0.0402 | 0.9897 | - |
+| 0.8543 | 6800 | 0.0435 | 0.0395 | 0.9912 | - |
+| 0.8668 | 6900 | 0.0444 | 0.0407 | 0.9901 | - |
+| 0.8794 | 7000 | 0.0438 | 0.0409 | 0.9906 | - |
+| 0.8920 | 7100 | 0.0428 | 0.0417 | 0.9869 | - |
+| 0.9045 | 7200 | 0.0429 | 0.0398 | 0.9912 | - |
+| 0.9171 | 7300 | 0.0445 | 0.0399 | 0.9912 | - |
+| 0.9296 | 7400 | 0.0438 | 0.0400 | 0.9905 | - |
+| 0.9422 | 7500 | 0.0448 | 0.0396 | 0.9902 | - |
+| 0.9548 | 7600 | 0.0426 | 0.0396 | 0.9906 | - |
+| 0.9673 | 7700 | 0.0441 | 0.0392 | 0.9925 | - |
+| 0.9799 | 7800 | 0.0409 | 0.0403 | 0.9883 | - |
+| 0.9925 | 7900 | 0.0469 | 0.0419 | 0.9899 | - |
+| 1.0050 | 8000 | 0.042 | 0.0399 | 0.9914 | - |
+| 1.0176 | 8100 | 0.036 | 0.0394 | 0.9915 | - |
+| 1.0302 | 8200 | 0.0376 | 0.0389 | 0.9915 | - |
+| 1.0427 | 8300 | 0.0377 | 0.0393 | 0.9912 | - |
+| 1.0553 | 8400 | 0.0377 | 0.0391 | 0.9894 | - |
+| 1.0678 | 8500 | 0.0357 | 0.0386 | 0.9888 | - |
+| 1.0804 | 8600 | 0.0374 | 0.0387 | 0.9896 | - |
+| 1.0930 | 8700 | 0.0336 | 0.0411 | 0.9895 | - |
+| 1.1055 | 8800 | 0.0383 | 0.0389 | 0.9909 | - |
+| 1.1181 | 8900 | 0.0379 | 0.0387 | 0.9916 | - |
+| 1.1307 | 9000 | 0.0384 | 0.0389 | 0.9886 | - |
+| 1.1432 | 9100 | 0.0364 | 0.0400 | 0.9887 | - |
+| 1.1558 | 9200 | 0.0396 | 0.0383 | 0.9898 | - |
+| 1.1683 | 9300 | 0.0353 | 0.0397 | 0.9907 | - |
+| 1.1809 | 9400 | 0.0364 | 0.0386 | 0.9909 | - |
+| 1.1935 | 9500 | 0.0351 | 0.0383 | 0.9909 | - |
+| 1.2060 | 9600 | 0.0344 | 0.0397 | 0.9905 | - |
+| 1.2186 | 9700 | 0.0366 | 0.0379 | 0.9916 | - |
+| 1.2312 | 9800 | 0.0373 | 0.0385 | 0.9908 | - |
+| 1.2437 | 9900 | 0.0353 | 0.0390 | 0.9903 | - |
+| 1.2563 | 10000 | 0.0365 | 0.0390 | 0.9892 | - |
+| 1.2688 | 10100 | 0.0356 | 0.0380 | 0.9893 | - |
+| 1.2814 | 10200 | 0.0418 | 0.0380 | 0.9908 | - |
+| 1.2940 | 10300 | 0.0365 | 0.0391 | 0.9896 | - |
+| 1.3065 | 10400 | 0.0359 | 0.0383 | 0.9907 | - |
+| 1.3191 | 10500 | 0.0366 | 0.0388 | 0.9909 | - |
+| 1.3317 | 10600 | 0.0381 | 0.0378 | 0.9918 | - |
+| 1.3442 | 10700 | 0.034 | 0.0393 | 0.9912 | - |
+| 1.3568 | 10800 | 0.0357 | 0.0378 | 0.9910 | - |
+| 1.3693 | 10900 | 0.0352 | 0.0385 | 0.9914 | - |
+| 1.3819 | 11000 | 0.0372 | 0.0380 | 0.9913 | - |
+| 1.3945 | 11100 | 0.0355 | 0.0378 | 0.9915 | - |
+| 1.4070 | 11200 | 0.0357 | 0.0380 | 0.9905 | - |
+| 1.4196 | 11300 | 0.0371 | 0.0409 | 0.9900 | - |
+| 1.4322 | 11400 | 0.0378 | 0.0384 | 0.9912 | - |
+| 1.4447 | 11500 | 0.0397 | 0.0374 | 0.9929 | - |
+| 1.4573 | 11600 | 0.0353 | 0.0368 | 0.9933 | - |
+| 1.4698 | 11700 | 0.0367 | 0.0363 | 0.9935 | - |
+| 1.4824 | 11800 | 0.037 | 0.0376 | 0.9917 | - |
+| 1.4950 | 11900 | 0.0373 | 0.0366 | 0.9931 | - |
+| 1.5075 | 12000 | 0.0354 | 0.0377 | 0.9926 | - |
+| 1.5201 | 12100 | 0.0347 | 0.0371 | 0.9927 | - |
+| 1.5327 | 12200 | 0.0376 | 0.0368 | 0.9924 | - |
+| 1.5452 | 12300 | 0.0366 | 0.0388 | 0.9910 | - |
+| 1.5578 | 12400 | 0.0348 | 0.0379 | 0.9919 | - |
+| 1.5704 | 12500 | 0.0356 | 0.0367 | 0.9926 | - |
+| 1.5829 | 12600 | 0.0369 | 0.0371 | 0.9920 | - |
+| 1.5955 | 12700 | 0.0373 | 0.0370 | 0.9921 | - |
+| 1.6080 | 12800 | 0.0372 | 0.0372 | 0.9929 | - |
+| 1.6206 | 12900 | 0.0387 | 0.0373 | 0.9920 | - |
+| 1.6332 | 13000 | 0.0345 | 0.0367 | 0.9918 | - |
+| 1.6457 | 13100 | 0.0368 | 0.0380 | 0.9924 | - |
+| 1.6583 | 13200 | 0.0357 | 0.0362 | 0.9924 | - |
+| 1.6709 | 13300 | 0.0353 | 0.0360 | 0.9924 | - |
+| 1.6834 | 13400 | 0.037 | 0.0397 | 0.9920 | - |
+| 1.6960 | 13500 | 0.0362 | 0.0368 | 0.9921 | - |
+| 1.7085 | 13600 | 0.0376 | 0.0366 | 0.9930 | - |
+| 1.7211 | 13700 | 0.0349 | 0.0369 | 0.9925 | - |
+| 1.7337 | 13800 | 0.0346 | 0.0374 | 0.9914 | - |
+| 1.7462 | 13900 | 0.0363 | 0.0371 | 0.9926 | - |
+| 1.7588 | 14000 | 0.0352 | 0.0381 | 0.9919 | - |
+| 1.7714 | 14100 | 0.035 | 0.0382 | 0.9925 | - |
+| 1.7839 | 14200 | 0.0389 | 0.0359 | 0.9935 | - |
+| 1.7965 | 14300 | 0.0353 | 0.0371 | 0.9926 | - |
+| 1.8090 | 14400 | 0.0353 | 0.0361 | 0.9931 | - |
+| 1.8216 | 14500 | 0.0369 | 0.0358 | 0.9933 | - |
+| 1.8342 | 14600 | 0.0381 | 0.0364 | 0.9934 | - |
+| 1.8467 | 14700 | 0.0353 | 0.0368 | 0.9930 | - |
+| 1.8593 | 14800 | 0.0379 | 0.0359 | 0.9922 | - |
+| 1.8719 | 14900 | 0.0359 | 0.0363 | 0.9919 | - |
+| 1.8844 | 15000 | 0.0382 | 0.0368 | 0.9928 | - |
+| 1.8970 | 15100 | 0.0373 | 0.0356 | 0.9928 | - |
+| 1.9095 | 15200 | 0.0369 | 0.0356 | 0.9929 | - |
+| 1.9221 | 15300 | 0.0362 | 0.0355 | 0.9925 | - |
+| 1.9347 | 15400 | 0.036 | 0.0372 | 0.9915 | - |
+| 1.9472 | 15500 | 0.0363 | 0.0355 | 0.9921 | - |
+| 1.9598 | 15600 | 0.0365 | 0.0370 | 0.9911 | - |
+| 1.9724 | 15700 | 0.0338 | 0.0366 | 0.9909 | - |
+| 1.9849 | 15800 | 0.0397 | 0.0357 | 0.9908 | - |
+| 1.9975 | 15900 | 0.0353 | 0.0366 | 0.9899 | - |
+| 2.0101 | 16000 | 0.027 | 0.0366 | 0.9902 | - |
+| 2.0226 | 16100 | 0.0233 | 0.0365 | 0.9906 | - |
+| 2.0352 | 16200 | 0.0248 | 0.0362 | 0.9916 | - |
+| 2.0477 | 16300 | 0.025 | 0.0366 | 0.9921 | - |
+| 2.0603 | 16400 | 0.0256 | 0.0366 | 0.9918 | - |
+| 2.0729 | 16500 | 0.0244 | 0.0355 | 0.9925 | - |
+| 2.0854 | 16600 | 0.0238 | 0.0364 | 0.9923 | - |
+| 2.0980 | 16700 | 0.0256 | 0.0359 | 0.9927 | - |
+| 2.1106 | 16800 | 0.0258 | 0.0374 | 0.9919 | - |
+| 2.1231 | 16900 | 0.0245 | 0.0356 | 0.9927 | - |
+| 2.1357 | 17000 | 0.023 | 0.0363 | 0.9923 | - |
+| 2.1482 | 17100 | 0.0259 | 0.0358 | 0.9928 | - |
+| 2.1608 | 17200 | 0.0246 | 0.0363 | 0.9919 | - |
+| 2.1734 | 17300 | 0.0242 | 0.0366 | 0.9914 | - |
+| 2.1859 | 17400 | 0.0217 | 0.0385 | 0.9904 | - |
+| 2.1985 | 17500 | 0.0253 | 0.0359 | 0.9921 | - |
+| 2.2111 | 17600 | 0.0244 | 0.0358 | 0.9923 | - |
+| 2.2236 | 17700 | 0.0245 | 0.0369 | 0.9919 | - |
+| 2.2362 | 17800 | 0.0257 | 0.0360 | 0.9922 | - |
+| 2.2487 | 17900 | 0.0257 | 0.0361 | 0.9919 | - |
+| 2.2613 | 18000 | 0.0256 | 0.0366 | 0.9920 | - |
+| 2.2739 | 18100 | 0.0264 | 0.0364 | 0.9921 | - |
+| 2.2864 | 18200 | 0.0252 | 0.0367 | 0.9921 | - |
+| 2.2990 | 18300 | 0.025 | 0.0362 | 0.9919 | - |
+| 2.3116 | 18400 | 0.0262 | 0.0364 | 0.9917 | - |
+| 2.3241 | 18500 | 0.0248 | 0.0363 | 0.9921 | - |
+| 2.3367 | 18600 | 0.0269 | 0.0357 | 0.9924 | - |
+| 2.3492 | 18700 | 0.0259 | 0.0360 | 0.9923 | - |
+| 2.3618 | 18800 | 0.0264 | 0.0359 | 0.9924 | - |
+| 2.3744 | 18900 | 0.027 | 0.0361 | 0.9923 | - |
+| 2.3869 | 19000 | 0.0276 | 0.0370 | 0.9920 | - |
+| 2.3995 | 19100 | 0.025 | 0.0375 | 0.9904 | - |
+| 2.4121 | 19200 | 0.0252 | 0.0363 | 0.9917 | - |
+| 2.4246 | 19300 | 0.0284 | 0.0354 | 0.9931 | - |
+| 2.4372 | 19400 | 0.0258 | 0.0361 | 0.9922 | - |
+| 2.4497 | 19500 | 0.0267 | 0.0362 | 0.9921 | - |
+| 2.4623 | 19600 | 0.0253 | 0.0356 | 0.9921 | - |
+| 2.4749 | 19700 | 0.0258 | 0.0369 | 0.9913 | - |
+| 2.4874 | 19800 | 0.0245 | 0.0371 | 0.9916 | - |
+| 2.5 | 19900 | 0.0281 | 0.0360 | 0.9923 | - |
+| 2.5126 | 20000 | 0.0254 | 0.0368 | 0.9915 | - |
+| 2.5251 | 20100 | 0.026 | 0.0365 | 0.9918 | - |
+| 2.5377 | 20200 | 0.0265 | 0.0357 | 0.9919 | - |
+| 2.5503 | 20300 | 0.026 | 0.0366 | 0.9917 | - |
+| 2.5628 | 20400 | 0.0291 | 0.0369 | 0.9917 | - |
+| 2.5754 | 20500 | 0.0254 | 0.0363 | 0.9920 | - |
+| 2.5879 | 20600 | 0.0262 | 0.0358 | 0.9917 | - |
+| 2.6005 | 20700 | 0.0246 | 0.0361 | 0.9910 | - |
+| 2.6131 | 20800 | 0.0251 | 0.0373 | 0.9904 | - |
+| 2.6256 | 20900 | 0.0258 | 0.0366 | 0.9915 | - |
+| 2.6382 | 21000 | 0.0249 | 0.0366 | 0.9919 | - |
+| 2.6508 | 21100 | 0.0269 | 0.0379 | 0.9920 | - |
+| 2.6633 | 21200 | 0.0276 | 0.0351 | 0.9926 | - |
+| 2.6759 | 21300 | 0.0256 | 0.0364 | 0.9917 | - |
+| 2.6884 | 21400 | 0.0272 | 0.0352 | 0.9923 | - |
+| 2.7010 | 21500 | 0.026 | 0.0355 | 0.9923 | - |
+| 2.7136 | 21600 | 0.0276 | 0.0353 | 0.9922 | - |
+| 2.7261 | 21700 | 0.0245 | 0.0374 | 0.9907 | - |
+| 2.7387 | 21800 | 0.0267 | 0.0360 | 0.9915 | - |
+| 2.7513 | 21900 | 0.0262 | 0.0358 | 0.9916 | - |
+| 2.7638 | 22000 | 0.0263 | 0.0348 | 0.9918 | - |
+| 2.7764 | 22100 | 0.0253 | 0.0355 | 0.9916 | - |
+| 2.7889 | 22200 | 0.0264 | 0.0380 | 0.9906 | - |
+| 2.8015 | 22300 | 0.0256 | 0.0363 | 0.9911 | - |
+| 2.8141 | 22400 | 0.0271 | 0.0361 | 0.9915 | - |
+| 2.8266 | 22500 | 0.026 | 0.0352 | 0.9919 | - |
+| 2.8392 | 22600 | 0.0271 | 0.0354 | 0.9919 | - |
+| 2.8518 | 22700 | 0.025 | 0.0370 | 0.9911 | - |
+| 2.8643 | 22800 | 0.0258 | 0.0361 | 0.9917 | - |
+| 2.8769 | 22900 | 0.024 | 0.0362 | 0.9919 | - |
+| 2.8894 | 23000 | 0.0284 | 0.0355 | 0.9921 | - |
+| 2.9020 | 23100 | 0.0277 | 0.0347 | 0.9926 | - |
+| 2.9146 | 23200 | 0.0253 | 0.0354 | 0.9918 | - |
+| 2.9271 | 23300 | 0.0262 | 0.0359 | 0.9912 | - |
+| 2.9397 | 23400 | 0.0264 | 0.0351 | 0.9920 | - |
+| 2.9523 | 23500 | 0.0296 | 0.0353 | 0.9919 | - |
+| 2.9648 | 23600 | 0.0272 | 0.0354 | 0.9921 | - |
+| 2.9774 | 23700 | 0.027 | 0.0361 | 0.9919 | - |
+| 2.9899 | 23800 | 0.0275 | 0.0360 | 0.9924 | - |
+| 3.0025 | 23900 | 0.0238 | 0.0361 | 0.9918 | - |
+| 3.0151 | 24000 | 0.0181 | 0.0369 | 0.9911 | - |
+| 3.0276 | 24100 | 0.0152 | 0.0390 | 0.9905 | - |
+| 3.0402 | 24200 | 0.0169 | 0.0386 | 0.9902 | - |
+| 3.0528 | 24300 | 0.0154 | 0.0384 | 0.9906 | - |
+| 3.0653 | 24400 | 0.0157 | 0.0375 | 0.9903 | - |
+| 3.0779 | 24500 | 0.0169 | 0.0388 | 0.9903 | - |
+| 3.0905 | 24600 | 0.0164 | 0.0391 | 0.9898 | - |
+| 3.1030 | 24700 | 0.0154 | 0.0389 | 0.9893 | - |
+| 3.1156 | 24800 | 0.0165 | 0.0390 | 0.9900 | - |
+| 3.1281 | 24900 | 0.0177 | 0.0376 | 0.9905 | - |
+| 3.1407 | 25000 | 0.0157 | 0.0390 | 0.9894 | - |
+| 3.1533 | 25100 | 0.0163 | 0.0380 | 0.9895 | - |
+| 3.1658 | 25200 | 0.0166 | 0.0377 | 0.9896 | - |
+| 3.1784 | 25300 | 0.017 | 0.0381 | 0.9904 | - |
+| 3.1910 | 25400 | 0.0166 | 0.0384 | 0.9899 | - |
+| 3.2035 | 25500 | 0.0163 | 0.0390 | 0.9895 | - |
+| 3.2161 | 25600 | 0.0175 | 0.0412 | 0.9898 | - |
+| 3.2286 | 25700 | 0.017 | 0.0387 | 0.9902 | - |
+| 3.2412 | 25800 | 0.0163 | 0.0390 | 0.9896 | - |
+| 3.2538 | 25900 | 0.0182 | 0.0383 | 0.9899 | - |
+| 3.2663 | 26000 | 0.0186 | 0.0387 | 0.9901 | - |
+| 3.2789 | 26100 | 0.0175 | 0.0376 | 0.9898 | - |
+| 3.2915 | 26200 | 0.0165 | 0.0381 | 0.9893 | - |
+| 3.3040 | 26300 | 0.0168 | 0.0389 | 0.9893 | - |
+| 3.3166 | 26400 | 0.0196 | 0.0364 | 0.9907 | - |
+| 3.3291 | 26500 | 0.0174 | 0.0383 | 0.9895 | - |
+| 3.3417 | 26600 | 0.0162 | 0.0396 | 0.9889 | - |
+| 3.3543 | 26700 | 0.0169 | 0.0390 | 0.9892 | - |
+| 3.3668 | 26800 | 0.016 | 0.0391 | 0.9892 | - |
+| 3.3794 | 26900 | 0.0182 | 0.0380 | 0.9897 | - |
+| 3.3920 | 27000 | 0.0171 | 0.0411 | 0.9891 | - |
+| 3.4045 | 27100 | 0.0173 | 0.0372 | 0.9899 | - |
+| 3.4171 | 27200 | 0.0178 | 0.0380 | 0.9895 | - |
+| 3.4296 | 27300 | 0.0196 | 0.0391 | 0.9896 | - |
+| 3.4422 | 27400 | 0.0191 | 0.0380 | 0.9891 | - |
+| 3.4548 | 27500 | 0.0184 | 0.0380 | 0.9898 | - |
+| 3.4673 | 27600 | 0.0185 | 0.0408 | 0.9892 | - |
+| 3.4799 | 27700 | 0.0187 | 0.0383 | 0.9901 | - |
+| 3.4925 | 27800 | 0.0175 | 0.0389 | 0.9899 | - |
+| 3.5050 | 27900 | 0.0187 | 0.0400 | 0.9887 | - |
+| 3.5176 | 28000 | 0.0182 | 0.0388 | 0.9885 | - |
+| 3.5302 | 28100 | 0.0164 | 0.0390 | 0.9890 | - |
+| 3.5427 | 28200 | 0.0188 | 0.0385 | 0.9897 | - |
+| 3.5553 | 28300 | 0.0188 | 0.0391 | 0.9898 | - |
+| 3.5678 | 28400 | 0.0183 | 0.0382 | 0.9894 | - |
+| 3.5804 | 28500 | 0.0179 | 0.0376 | 0.9898 | - |
+| 3.5930 | 28600 | 0.0185 | 0.0381 | 0.9899 | - |
+| 3.6055 | 28700 | 0.0169 | 0.0378 | 0.9894 | - |
+| 3.6181 | 28800 | 0.0199 | 0.0386 | 0.9900 | - |
+| 3.6307 | 28900 | 0.0184 | 0.0392 | 0.9901 | - |
+| 3.6432 | 29000 | 0.0187 | 0.0381 | 0.9905 | - |
+| 3.6558 | 29100 | 0.018 | 0.0386 | 0.9897 | - |
+| 3.6683 | 29200 | 0.0165 | 0.0384 | 0.9894 | - |
+| 3.6809 | 29300 | 0.0192 | 0.0372 | 0.9900 | - |
+| 3.6935 | 29400 | 0.0169 | 0.0382 | 0.9899 | - |
+| 3.7060 | 29500 | 0.0185 | 0.0375 | 0.9899 | - |
+| 3.7186 | 29600 | 0.0185 | 0.0383 | 0.9899 | - |
+| 3.7312 | 29700 | 0.0197 | 0.0372 | 0.9907 | - |
+| 3.7437 | 29800 | 0.0193 | 0.0378 | 0.9902 | - |
+| 3.7563 | 29900 | 0.0182 | 0.0368 | 0.9907 | - |
+| 3.7688 | 30000 | 0.0184 | 0.0384 | 0.9904 | - |
+| 3.7814 | 30100 | 0.0183 | 0.0365 | 0.9906 | - |
+| 3.7940 | 30200 | 0.0193 | 0.0398 | 0.9895 | - |
+| 3.8065 | 30300 | 0.0186 | 0.0391 | 0.9890 | - |
+| 3.8191 | 30400 | 0.0185 | 0.0374 | 0.9895 | - |
+| 3.8317 | 30500 | 0.0196 | 0.0375 | 0.9881 | - |
+| 3.8442 | 30600 | 0.018 | 0.0392 | 0.9878 | - |
+| 3.8568 | 30700 | 0.0199 | 0.0375 | 0.9883 | - |
+| 3.8693 | 30800 | 0.0184 | 0.0384 | 0.9875 | - |
+| 3.8819 | 30900 | 0.0182 | 0.0393 | 0.9878 | - |
+| 3.8945 | 31000 | 0.0186 | 0.0392 | 0.9880 | - |
+| 3.9070 | 31100 | 0.0183 | 0.0384 | 0.9878 | - |
+| 3.9196 | 31200 | 0.0184 | 0.0382 | 0.9870 | - |
+| 3.9322 | 31300 | 0.0189 | 0.0376 | 0.9874 | - |
+| 3.9447 | 31400 | 0.0201 | 0.0365 | 0.9880 | - |
+| 3.9573 | 31500 | 0.0188 | 0.0372 | 0.9877 | - |
+| 3.9698 | 31600 | 0.018 | 0.0387 | 0.9873 | - |
+| 3.9824 | 31700 | 0.0188 | 0.0381 | 0.9885 | - |
+| 3.9950 | 31800 | 0.0175 | 0.0386 | 0.9874 | - |
+| 4.0075 | 31900 | 0.0156 | 0.0391 | 0.9886 | - |
+| 4.0201 | 32000 | 0.0109 | 0.0403 | 0.9872 | - |
+| 4.0327 | 32100 | 0.0116 | 0.0408 | 0.9869 | - |
+| 4.0452 | 32200 | 0.0123 | 0.0395 | 0.9875 | - |
+| 4.0578 | 32300 | 0.0117 | 0.0396 | 0.9874 | - |
+| 4.0704 | 32400 | 0.0106 | 0.0426 | 0.9868 | - |
+| 4.0829 | 32500 | 0.0114 | 0.0398 | 0.9878 | - |
+| 4.0955 | 32600 | 0.0106 | 0.0413 | 0.9872 | - |
+| 4.1080 | 32700 | 0.0107 | 0.0416 | 0.9873 | - |
+| 4.1206 | 32800 | 0.0115 | 0.0422 | 0.9862 | - |
+| 4.1332 | 32900 | 0.0112 | 0.0421 | 0.9863 | - |
+| 4.1457 | 33000 | 0.0114 | 0.0425 | 0.9865 | - |
+| 4.1583 | 33100 | 0.0114 | 0.0424 | 0.9859 | - |
+| 4.1709 | 33200 | 0.0104 | 0.0426 | 0.9864 | - |
+| 4.1834 | 33300 | 0.0114 | 0.0417 | 0.9874 | - |
+| 4.1960 | 33400 | 0.0114 | 0.0393 | 0.9881 | - |
+| 4.2085 | 33500 | 0.0119 | 0.0442 | 0.9873 | - |
+| 4.2211 | 33600 | 0.0117 | 0.0429 | 0.9868 | - |
+| 4.2337 | 33700 | 0.0121 | 0.0401 | 0.9881 | - |
+| 4.2462 | 33800 | 0.013 | 0.0416 | 0.9873 | - |
+| 4.2588 | 33900 | 0.0129 | 0.0439 | 0.9873 | - |
+| 4.2714 | 34000 | 0.0125 | 0.0399 | 0.9883 | - |
+| 4.2839 | 34100 | 0.0113 | 0.0429 | 0.9867 | - |
+| 4.2965 | 34200 | 0.0119 | 0.0436 | 0.9865 | - |
+| 4.3090 | 34300 | 0.0103 | 0.0419 | 0.9866 | - |
+| 4.3216 | 34400 | 0.0126 | 0.0442 | 0.9868 | - |
+| 4.3342 | 34500 | 0.0113 | 0.0412 | 0.9869 | - |
+| 4.3467 | 34600 | 0.0107 | 0.0406 | 0.9870 | - |
+| 4.3593 | 34700 | 0.012 | 0.0425 | 0.9868 | - |
+| 4.3719 | 34800 | 0.0111 | 0.0424 | 0.9866 | - |
+| 4.3844 | 34900 | 0.0107 | 0.0435 | 0.9865 | - |
+| 4.3970 | 35000 | 0.0111 | 0.0434 | 0.9862 | - |
+| 4.4095 | 35100 | 0.012 | 0.0418 | 0.9873 | - |
+| 4.4221 | 35200 | 0.0125 | 0.0423 | 0.9868 | - |
+| 4.4347 | 35300 | 0.0126 | 0.0446 | 0.9863 | - |
+| 4.4472 | 35400 | 0.0119 | 0.0411 | 0.9874 | - |
+| 4.4598 | 35500 | 0.011 | 0.0435 | 0.9868 | - |
+| 4.4724 | 35600 | 0.0115 | 0.0434 | 0.9865 | - |
+| 4.4849 | 35700 | 0.0131 | 0.0421 | 0.9869 | - |
+| 4.4975 | 35800 | 0.0123 | 0.0414 | 0.9871 | - |
+| 4.5101 | 35900 | 0.0116 | 0.0425 | 0.9867 | - |
+| 4.5226 | 36000 | 0.0121 | 0.0433 | 0.9861 | - |
+| 4.5352 | 36100 | 0.0117 | 0.0417 | 0.9870 | - |
+| 4.5477 | 36200 | 0.0123 | 0.0444 | 0.9865 | - |
+| 4.5603 | 36300 | 0.0113 | 0.0415 | 0.9871 | - |
+| 4.5729 | 36400 | 0.0123 | 0.0422 | 0.9870 | - |
+| 4.5854 | 36500 | 0.0136 | 0.0438 | 0.9871 | - |
+| 4.5980 | 36600 | 0.0116 | 0.0420 | 0.9867 | - |
+| 4.6106 | 36700 | 0.0116 | 0.0425 | 0.9866 | - |
+| 4.6231 | 36800 | 0.015 | 0.0433 | 0.9870 | - |
+| 4.6357 | 36900 | 0.0127 | 0.0431 | 0.9863 | - |
+| 4.6482 | 37000 | 0.0128 | 0.0418 | 0.9876 | - |
+| 4.6608 | 37100 | 0.013 | 0.0409 | 0.9875 | - |
+| 4.6734 | 37200 | 0.0127 | 0.0418 | 0.9879 | - |
+| 4.6859 | 37300 | 0.0125 | 0.0431 | 0.9873 | - |
+| 4.6985 | 37400 | 0.013 | 0.0390 | 0.9883 | - |
+| 4.7111 | 37500 | 0.0133 | 0.0415 | 0.9876 | - |
+| 4.7236 | 37600 | 0.0146 | 0.0404 | 0.9879 | - |
+| 4.7362 | 37700 | 0.0124 | 0.0408 | 0.9877 | - |
+| 4.7487 | 37800 | 0.0115 | 0.0415 | 0.9874 | - |
+| 4.7613 | 37900 | 0.013 | 0.0410 | 0.9874 | - |
+| 4.7739 | 38000 | 0.0125 | 0.0417 | 0.9872 | - |
+| 4.7864 | 38100 | 0.0124 | 0.0403 | 0.9872 | - |
+| 4.7990 | 38200 | 0.0138 | 0.0418 | 0.9874 | - |
+| 4.8116 | 38300 | 0.0115 | 0.0448 | 0.9866 | - |
+| 4.8241 | 38400 | 0.0128 | 0.0417 | 0.9870 | - |
+| 4.8367 | 38500 | 0.014 | 0.0412 | 0.9870 | - |
+| 4.8492 | 38600 | 0.0123 | 0.0434 | 0.9864 | - |
+| 4.8618 | 38700 | 0.0122 | 0.0422 | 0.9866 | - |
+| 4.8744 | 38800 | 0.0146 | 0.0404 | 0.9870 | - |
+| 4.8869 | 38900 | 0.0133 | 0.0430 | 0.9866 | - |
+| 4.8995 | 39000 | 0.013 | 0.0410 | 0.9865 | - |
+| 4.9121 | 39100 | 0.0126 | 0.0426 | 0.9864 | - |
+| 4.9246 | 39200 | 0.0133 | 0.0418 | 0.9866 | - |
+| 4.9372 | 39300 | 0.0123 | 0.0441 | 0.9857 | - |
+| 4.9497 | 39400 | 0.0142 | 0.0419 | 0.9861 | - |
+| 4.9623 | 39500 | 0.0138 | 0.0424 | 0.9858 | - |
+| 4.9749 | 39600 | 0.0134 | 0.0419 | 0.9859 | - |
+| 4.9874 | 39700 | 0.0131 | 0.0422 | 0.9858 | - |
+| 5.0 | 39800 | 0.0146 | 0.0410 | 0.9861 | - |
+| 5.0126 | 39900 | 0.0078 | 0.0429 | 0.9858 | - |
+| 5.0251 | 40000 | 0.0073 | 0.0439 | 0.9853 | - |
+| 5.0377 | 40100 | 0.008 | 0.0441 | 0.9856 | - |
+| 5.0503 | 40200 | 0.0082 | 0.0446 | 0.9849 | - |
+| 5.0628 | 40300 | 0.0076 | 0.0445 | 0.9850 | - |
+| 5.0754 | 40400 | 0.008 | 0.0451 | 0.9849 | - |
+| 5.0879 | 40500 | 0.0085 | 0.0453 | 0.9846 | - |
+| 5.1005 | 40600 | 0.0077 | 0.0443 | 0.9852 | - |
+| 5.1131 | 40700 | 0.0092 | 0.0457 | 0.9848 | - |
+| 5.1256 | 40800 | 0.0079 | 0.0436 | 0.9852 | - |
+| 5.1382 | 40900 | 0.008 | 0.0471 | 0.9847 | - |
+| 5.1508 | 41000 | 0.0081 | 0.0480 | 0.9843 | - |
+| 5.1633 | 41100 | 0.0073 | 0.0473 | 0.9846 | - |
+| 5.1759 | 41200 | 0.0082 | 0.0459 | 0.9850 | - |
+| 5.1884 | 41300 | 0.0072 | 0.0465 | 0.9844 | - |
+| 5.2010 | 41400 | 0.0094 | 0.0469 | 0.9843 | - |
+| 5.2136 | 41500 | 0.0094 | 0.0467 | 0.9848 | - |
+| 5.2261 | 41600 | 0.0087 | 0.0455 | 0.9848 | - |
+| 5.2387 | 41700 | 0.0083 | 0.0476 | 0.9843 | - |
+| 5.2513 | 41800 | 0.008 | 0.0470 | 0.9844 | - |
+| 5.2638 | 41900 | 0.0082 | 0.0450 | 0.9848 | - |
+| 5.2764 | 42000 | 0.0084 | 0.0468 | 0.9843 | - |
+| 5.2889 | 42100 | 0.0096 | 0.0470 | 0.9844 | - |
+| 5.3015 | 42200 | 0.0085 | 0.0455 | 0.9847 | - |
+| 5.3141 | 42300 | 0.0088 | 0.0469 | 0.9849 | - |
+| 5.3266 | 42400 | 0.0091 | 0.0452 | 0.9851 | - |
+| 5.3392 | 42500 | 0.0084 | 0.0495 | 0.9843 | - |
+| 5.3518 | 42600 | 0.0085 | 0.0449 | 0.9852 | - |
+| 5.3643 | 42700 | 0.0083 | 0.0480 | 0.9844 | - |
+| 5.3769 | 42800 | 0.0086 | 0.0460 | 0.9842 | - |
+| 5.3894 | 42900 | 0.0078 | 0.0477 | 0.9840 | - |
+| 5.4020 | 43000 | 0.0091 | 0.0459 | 0.9847 | - |
+| 5.4146 | 43100 | 0.0087 | 0.0453 | 0.9854 | - |
+| 5.4271 | 43200 | 0.0082 | 0.0460 | 0.9850 | - |
+| 5.4397 | 43300 | 0.0084 | 0.0474 | 0.9844 | - |
+| 5.4523 | 43400 | 0.0085 | 0.0496 | 0.9840 | - |
+| 5.4648 | 43500 | 0.0092 | 0.0465 | 0.9847 | - |
+| 5.4774 | 43600 | 0.0081 | 0.0470 | 0.9846 | - |
+| 5.4899 | 43700 | 0.0086 | 0.0455 | 0.9847 | - |
+| 5.5025 | 43800 | 0.0086 | 0.0459 | 0.9847 | - |
+| 5.5151 | 43900 | 0.0078 | 0.0467 | 0.9848 | - |
+| 5.5276 | 44000 | 0.0085 | 0.0459 | 0.9851 | - |
+| 5.5402 | 44100 | 0.0087 | 0.0466 | 0.9847 | - |
+| 5.5528 | 44200 | 0.0084 | 0.0465 | 0.9845 | - |
+| 5.5653 | 44300 | 0.009 | 0.0465 | 0.9849 | - |
+| 5.5779 | 44400 | 0.0082 | 0.0462 | 0.9851 | - |
+| 5.5905 | 44500 | 0.0087 | 0.0489 | 0.9840 | - |
+| 5.6030 | 44600 | 0.0098 | 0.0455 | 0.9848 | - |
+| 5.6156 | 44700 | 0.0087 | 0.0436 | 0.9853 | - |
+| 5.6281 | 44800 | 0.0086 | 0.0475 | 0.9846 | - |
+| 5.6407 | 44900 | 0.0101 | 0.0469 | 0.9847 | - |
+| 5.6533 | 45000 | 0.0092 | 0.0464 | 0.9843 | - |
+| 5.6658 | 45100 | 0.0085 | 0.0462 | 0.9840 | - |
+| 5.6784 | 45200 | 0.008 | 0.0483 | 0.9839 | - |
+| 5.6910 | 45300 | 0.0089 | 0.0464 | 0.9842 | - |
+| 5.7035 | 45400 | 0.008 | 0.0469 | 0.9843 | - |
+| 5.7161 | 45500 | 0.0093 | 0.0473 | 0.9841 | - |
+| 5.7286 | 45600 | 0.0091 | 0.0476 | 0.9844 | - |
+| 5.7412 | 45700 | 0.0085 | 0.0462 | 0.9840 | - |
+| 5.7538 | 45800 | 0.008 | 0.0477 | 0.9842 | - |
+| 5.7663 | 45900 | 0.008 | 0.0473 | 0.9834 | - |
+| 5.7789 | 46000 | 0.0088 | 0.0470 | 0.9843 | - |
+| 5.7915 | 46100 | 0.0085 | 0.0474 | 0.9840 | - |
+| 5.8040 | 46200 | 0.0101 | 0.0474 | 0.9840 | - |
+| 5.8166 | 46300 | 0.0095 | 0.0449 | 0.9846 | - |
+| 5.8291 | 46400 | 0.0081 | 0.0480 | 0.9840 | - |
+| 5.8417 | 46500 | 0.0086 | 0.0487 | 0.9837 | - |
+| 5.8543 | 46600 | 0.0091 | 0.0434 | 0.9847 | - |
+| 5.8668 | 46700 | 0.0087 | 0.0465 | 0.9843 | - |
+| 5.8794 | 46800 | 0.009 | 0.0464 | 0.9846 | - |
+| 5.8920 | 46900 | 0.0099 | 0.0466 | 0.9846 | - |
+| 5.9045 | 47000 | 0.0088 | 0.0466 | 0.9847 | - |
+| 5.9171 | 47100 | 0.0095 | 0.0449 | 0.9849 | - |
+| 5.9296 | 47200 | 0.0101 | 0.0466 | 0.9849 | - |
+| 5.9422 | 47300 | 0.0087 | 0.0469 | 0.9845 | - |
+| 5.9548 | 47400 | 0.0091 | 0.0472 | 0.9845 | - |
+| 5.9673 | 47500 | 0.0092 | 0.0486 | 0.9846 | - |
+| 5.9799 | 47600 | 0.0093 | 0.0452 | 0.9848 | - |
+| 5.9925 | 47700 | 0.0094 | 0.0460 | 0.9846 | - |
+| 6.0050 | 47800 | 0.0084 | 0.0468 | 0.9848 | - |
+| 6.0176 | 47900 | 0.006 | 0.0479 | 0.9842 | - |
+| 6.0302 | 48000 | 0.0052 | 0.0493 | 0.9834 | - |
+| 6.0427 | 48100 | 0.0055 | 0.0478 | 0.9832 | - |
+| 6.0553 | 48200 | 0.0057 | 0.0485 | 0.9836 | - |
+| 6.0678 | 48300 | 0.0058 | 0.0490 | 0.9832 | - |
+| 6.0804 | 48400 | 0.0059 | 0.0479 | 0.9834 | - |
+| 6.0930 | 48500 | 0.0055 | 0.0487 | 0.9832 | - |
+| 6.1055 | 48600 | 0.0056 | 0.0489 | 0.9828 | - |
+| 6.1181 | 48700 | 0.006 | 0.0496 | 0.9827 | - |
+| 6.1307 | 48800 | 0.0052 | 0.0503 | 0.9825 | - |
+| 6.1432 | 48900 | 0.0058 | 0.0515 | 0.9825 | - |
+| 6.1558 | 49000 | 0.006 | 0.0538 | 0.9818 | - |
+| 6.1683 | 49100 | 0.0065 | 0.0476 | 0.9827 | - |
+| 6.1809 | 49200 | 0.0058 | 0.0499 | 0.9825 | - |
+| 6.1935 | 49300 | 0.0052 | 0.0510 | 0.9820 | - |
+| 6.2060 | 49400 | 0.007 | 0.0516 | 0.9822 | - |
+| 6.2186 | 49500 | 0.0066 | 0.0503 | 0.9823 | - |
+| 6.2312 | 49600 | 0.006 | 0.0514 | 0.9826 | - |
+| 6.2437 | 49700 | 0.0057 | 0.0536 | 0.9820 | - |
+| 6.2563 | 49800 | 0.0048 | 0.0509 | 0.9820 | - |
+| 6.2688 | 49900 | 0.0062 | 0.0477 | 0.9824 | - |
+| 6.2814 | 50000 | 0.0061 | 0.0510 | 0.9818 | - |
+| 6.2940 | 50100 | 0.0056 | 0.0545 | 0.9815 | - |
+| 6.3065 | 50200 | 0.0065 | 0.0504 | 0.9824 | - |
+| 6.3191 | 50300 | 0.0059 | 0.0500 | 0.9826 | - |
+| 6.3317 | 50400 | 0.0063 | 0.0527 | 0.9819 | - |
+| 6.3442 | 50500 | 0.0063 | 0.0485 | 0.9824 | - |
+| 6.3568 | 50600 | 0.0058 | 0.0508 | 0.9818 | - |
+| 6.3693 | 50700 | 0.0055 | 0.0514 | 0.9821 | - |
+| 6.3819 | 50800 | 0.0072 | 0.0504 | 0.9826 | - |
+| 6.3945 | 50900 | 0.0064 | 0.0496 | 0.9828 | - |
+| 6.4070 | 51000 | 0.0062 | 0.0492 | 0.9827 | - |
+| 6.4196 | 51100 | 0.0057 | 0.0510 | 0.9827 | - |
+| 6.4322 | 51200 | 0.0057 | 0.0489 | 0.9829 | - |
+| 6.4447 | 51300 | 0.0061 | 0.0508 | 0.9827 | - |
+| 6.4573 | 51400 | 0.0061 | 0.0510 | 0.9822 | - |
+| 6.4698 | 51500 | 0.0055 | 0.0525 | 0.9821 | - |
+| 6.4824 | 51600 | 0.0057 | 0.0499 | 0.9821 | - |
+| 6.4950 | 51700 | 0.006 | 0.0517 | 0.9822 | - |
+| 6.5075 | 51800 | 0.007 | 0.0512 | 0.9825 | - |
+| 6.5201 | 51900 | 0.0059 | 0.0490 | 0.9826 | - |
+| 6.5327 | 52000 | 0.0067 | 0.0495 | 0.9822 | - |
+| 6.5452 | 52100 | 0.006 | 0.0506 | 0.9819 | - |
+| 6.5578 | 52200 | 0.0067 | 0.0490 | 0.9823 | - |
+| 6.5704 | 52300 | 0.0062 | 0.0493 | 0.9823 | - |
+| 6.5829 | 52400 | 0.0066 | 0.0498 | 0.9825 | - |
+| 6.5955 | 52500 | 0.0067 | 0.0507 | 0.9827 | - |
+| 6.6080 | 52600 | 0.0062 | 0.0492 | 0.9828 | - |
+| 6.6206 | 52700 | 0.0059 | 0.0512 | 0.9824 | - |
+| 6.6332 | 52800 | 0.0075 | 0.0504 | 0.9830 | - |
+| 6.6457 | 52900 | 0.007 | 0.0495 | 0.9828 | - |
+| 6.6583 | 53000 | 0.0062 | 0.0500 | 0.9824 | - |
+| 6.6709 | 53100 | 0.0064 | 0.0517 | 0.9820 | - |
+| 6.6834 | 53200 | 0.0066 | 0.0496 | 0.9824 | - |
+| 6.6960 | 53300 | 0.0067 | 0.0499 | 0.9826 | - |
+| 6.7085 | 53400 | 0.0067 | 0.0493 | 0.9830 | - |
+| 6.7211 | 53500 | 0.0069 | 0.0486 | 0.9829 | - |
+| 6.7337 | 53600 | 0.0063 | 0.0485 | 0.9828 | - |
+| 6.7462 | 53700 | 0.0062 | 0.0509 | 0.9825 | - |
+| 6.7588 | 53800 | 0.0056 | 0.0519 | 0.9824 | - |
+| 6.7714 | 53900 | 0.0061 | 0.0541 | 0.9817 | - |
+| 6.7839 | 54000 | 0.007 | 0.0515 | 0.9820 | - |
+| 6.7965 | 54100 | 0.006 | 0.0521 | 0.9822 | - |
+| 6.8090 | 54200 | 0.0068 | 0.0506 | 0.9822 | - |
+| 6.8216 | 54300 | 0.0075 | 0.0494 | 0.9826 | - |
+| 6.8342 | 54400 | 0.0069 | 0.0497 | 0.9824 | - |
+| 6.8467 | 54500 | 0.0067 | 0.0524 | 0.9820 | - |
+| 6.8593 | 54600 | 0.0065 | 0.0514 | 0.9820 | - |
+| 6.8719 | 54700 | 0.0073 | 0.0495 | 0.9827 | - |
+| 6.8844 | 54800 | 0.0065 | 0.0495 | 0.9828 | - |
+| 6.8970 | 54900 | 0.0064 | 0.0487 | 0.9828 | - |
+| 6.9095 | 55000 | 0.0067 | 0.0472 | 0.9831 | - |
+| 6.9221 | 55100 | 0.0067 | 0.0501 | 0.9827 | - |
+| 6.9347 | 55200 | 0.0073 | 0.0483 | 0.9829 | - |
+| 6.9472 | 55300 | 0.0062 | 0.0511 | 0.9824 | - |
+| 6.9598 | 55400 | 0.006 | 0.0528 | 0.9818 | - |
+| 6.9724 | 55500 | 0.0071 | 0.0509 | 0.9825 | - |
+| 6.9849 | 55600 | 0.0056 | 0.0495 | 0.9823 | - |
+| 6.9975 | 55700 | 0.0068 | 0.0507 | 0.9821 | - |
+| 7.0101 | 55800 | 0.0046 | 0.0522 | 0.9818 | - |
+| 7.0226 | 55900 | 0.0041 | 0.0533 | 0.9815 | - |
+| 7.0352 | 56000 | 0.0046 | 0.0518 | 0.9816 | - |
+| 7.0477 | 56100 | 0.0046 | 0.0520 | 0.9817 | - |
+| 7.0603 | 56200 | 0.0044 | 0.0514 | 0.9819 | - |
+| 7.0729 | 56300 | 0.0044 | 0.0504 | 0.9819 | - |
+| 7.0854 | 56400 | 0.0042 | 0.0533 | 0.9813 | - |
+| 7.0980 | 56500 | 0.004 | 0.0544 | 0.9810 | - |
+| 7.1106 | 56600 | 0.005 | 0.0524 | 0.9815 | - |
+| 7.1231 | 56700 | 0.0042 | 0.0540 | 0.9809 | - |
+| 7.1357 | 56800 | 0.0047 | 0.0506 | 0.9814 | - |
+| 7.1482 | 56900 | 0.0045 | 0.0534 | 0.9811 | - |
+| 7.1608 | 57000 | 0.0038 | 0.0539 | 0.9810 | - |
+| 7.1734 | 57100 | 0.0048 | 0.0544 | 0.9813 | - |
+| 7.1859 | 57200 | 0.0045 | 0.0523 | 0.9814 | - |
+| 7.1985 | 57300 | 0.0041 | 0.0539 | 0.9812 | - |
+| 7.2111 | 57400 | 0.0045 | 0.0532 | 0.9811 | - |
+| 7.2236 | 57500 | 0.0053 | 0.0517 | 0.9814 | - |
+| 7.2362 | 57600 | 0.0045 | 0.0529 | 0.9811 | - |
+| 7.2487 | 57700 | 0.0046 | 0.0535 | 0.9808 | - |
+| 7.2613 | 57800 | 0.0045 | 0.0540 | 0.9809 | - |
+| 7.2739 | 57900 | 0.0049 | 0.0550 | 0.9811 | - |
+| 7.2864 | 58000 | 0.0049 | 0.0516 | 0.9813 | - |
+| 7.2990 | 58100 | 0.004 | 0.0549 | 0.9809 | - |
+| 7.3116 | 58200 | 0.0046 | 0.0539 | 0.9809 | - |
+| 7.3241 | 58300 | 0.0044 | 0.0534 | 0.9808 | - |
+| 7.3367 | 58400 | 0.0043 | 0.0541 | 0.9810 | - |
+| 7.3492 | 58500 | 0.0051 | 0.0545 | 0.9810 | - |
+| 7.3618 | 58600 | 0.005 | 0.0520 | 0.9815 | - |
+| 7.3744 | 58700 | 0.0047 | 0.0529 | 0.9810 | - |
+| 7.3869 | 58800 | 0.0045 | 0.0540 | 0.9809 | - |
+| 7.3995 | 58900 | 0.0053 | 0.0528 | 0.9813 | - |
+| 7.4121 | 59000 | 0.0047 | 0.0544 | 0.9810 | - |
+| 7.4246 | 59100 | 0.0044 | 0.0525 | 0.9812 | - |
+| 7.4372 | 59200 | 0.0052 | 0.0543 | 0.9813 | - |
+| 7.4497 | 59300 | 0.0057 | 0.0555 | 0.9810 | - |
+| 7.4623 | 59400 | 0.0043 | 0.0564 | 0.9807 | - |
+| 7.4749 | 59500 | 0.0049 | 0.0519 | 0.9810 | - |
+| 7.4874 | 59600 | 0.0047 | 0.0554 | 0.9806 | - |
+| 7.5 | 59700 | 0.0044 | 0.0560 | 0.9809 | - |
+| 7.5126 | 59800 | 0.0049 | 0.0551 | 0.9808 | - |
+| 7.5251 | 59900 | 0.0051 | 0.0534 | 0.9811 | - |
+| 7.5377 | 60000 | 0.0046 | 0.0539 | 0.9810 | - |
+| 7.5503 | 60100 | 0.0048 | 0.0540 | 0.9811 | - |
+| 7.5628 | 60200 | 0.0052 | 0.0533 | 0.9812 | - |
+| 7.5754 | 60300 | 0.005 | 0.0531 | 0.9811 | - |
+| 7.5879 | 60400 | 0.0044 | 0.0530 | 0.9814 | - |
+| 7.6005 | 60500 | 0.0065 | 0.0546 | 0.9812 | - |
+| 7.6131 | 60600 | 0.005 | 0.0520 | 0.9812 | - |
+| 7.6256 | 60700 | 0.0059 | 0.0525 | 0.9813 | - |
+| 7.6382 | 60800 | 0.0047 | 0.0519 | 0.9815 | - |
+| 7.6508 | 60900 | 0.0056 | 0.0511 | 0.9818 | - |
+| 7.6633 | 61000 | 0.005 | 0.0514 | 0.9819 | - |
+| 7.6759 | 61100 | 0.0052 | 0.0526 | 0.9813 | - |
+| 7.6884 | 61200 | 0.0056 | 0.0541 | 0.9810 | - |
+| 7.7010 | 61300 | 0.0047 | 0.0541 | 0.9812 | - |
+| 7.7136 | 61400 | 0.0044 | 0.0550 | 0.9808 | - |
+| 7.7261 | 61500 | 0.0046 | 0.0563 | 0.9808 | - |
+| 7.7387 | 61600 | 0.0057 | 0.0526 | 0.9814 | - |
+| 7.7513 | 61700 | 0.0048 | 0.0541 | 0.9815 | - |
+| 7.7638 | 61800 | 0.0051 | 0.0530 | 0.9812 | - |
+| 7.7764 | 61900 | 0.0051 | 0.0528 | 0.9813 | - |
+| 7.7889 | 62000 | 0.0059 | 0.0539 | 0.9810 | - |
+| 7.8015 | 62100 | 0.0051 | 0.0523 | 0.9814 | - |
+| 7.8141 | 62200 | 0.0047 | 0.0528 | 0.9814 | - |
+| 7.8266 | 62300 | 0.0049 | 0.0546 | 0.9811 | - |
+| 7.8392 | 62400 | 0.0041 | 0.0535 | 0.9810 | - |
+| 7.8518 | 62500 | 0.0043 | 0.0543 | 0.9809 | - |
+| 7.8643 | 62600 | 0.0042 | 0.0554 | 0.9810 | - |
+| 7.8769 | 62700 | 0.0047 | 0.0531 | 0.9815 | - |
+| 7.8894 | 62800 | 0.0052 | 0.0518 | 0.9818 | - |
+| 7.9020 | 62900 | 0.0049 | 0.0523 | 0.9818 | - |
+| 7.9146 | 63000 | 0.0048 | 0.0535 | 0.9815 | - |
+| 7.9271 | 63100 | 0.0047 | 0.0539 | 0.9813 | - |
+| 7.9397 | 63200 | 0.0052 | 0.0531 | 0.9812 | - |
+| 7.9523 | 63300 | 0.0051 | 0.0555 | 0.9809 | - |
+| 7.9648 | 63400 | 0.005 | 0.0535 | 0.9811 | - |
+| 7.9774 | 63500 | 0.005 | 0.0533 | 0.9813 | - |
+| 7.9899 | 63600 | 0.0047 | 0.0543 | 0.9811 | - |
+| 8.0025 | 63700 | 0.005 | 0.0536 | 0.9809 | - |
+| 8.0151 | 63800 | 0.0038 | 0.0540 | 0.9808 | - |
+| 8.0276 | 63900 | 0.0033 | 0.0550 | 0.9804 | - |
+| 8.0402 | 64000 | 0.0037 | 0.0553 | 0.9803 | - |
+| 8.0528 | 64100 | 0.0033 | 0.0549 | 0.9801 | - |
+| 8.0653 | 64200 | 0.0041 | 0.0545 | 0.9801 | - |
+| 8.0779 | 64300 | 0.0035 | 0.0551 | 0.9800 | - |
+| 8.0905 | 64400 | 0.0039 | 0.0558 | 0.9799 | - |
+| 8.1030 | 64500 | 0.0037 | 0.0547 | 0.9801 | - |
+| 8.1156 | 64600 | 0.0039 | 0.0565 | 0.9800 | - |
+| 8.1281 | 64700 | 0.0039 | 0.0551 | 0.9802 | - |
+| 8.1407 | 64800 | 0.004 | 0.0545 | 0.9802 | - |
+| 8.1533 | 64900 | 0.0036 | 0.0552 | 0.9801 | - |
+| 8.1658 | 65000 | 0.0038 | 0.0557 | 0.9802 | - |
+| 8.1784 | 65100 | 0.0038 | 0.0566 | 0.9801 | - |
+| 8.1910 | 65200 | 0.0042 | 0.0554 | 0.9798 | - |
+| 8.2035 | 65300 | 0.0039 | 0.0570 | 0.9795 | - |
+| 8.2161 | 65400 | 0.0034 | 0.0573 | 0.9793 | - |
+| 8.2286 | 65500 | 0.0043 | 0.0570 | 0.9796 | - |
+| 8.2412 | 65600 | 0.0034 | 0.0583 | 0.9796 | - |
+| 8.2538 | 65700 | 0.0037 | 0.0578 | 0.9796 | - |
+| 8.2663 | 65800 | 0.0036 | 0.0571 | 0.9794 | - |
+| 8.2789 | 65900 | 0.0035 | 0.0580 | 0.9794 | - |
+| 8.2915 | 66000 | 0.0031 | 0.0581 | 0.9795 | - |
+| 8.3040 | 66100 | 0.0035 | 0.0559 | 0.9797 | - |
+| 8.3166 | 66200 | 0.0042 | 0.0564 | 0.9794 | - |
+| 8.3291 | 66300 | 0.0034 | 0.0562 | 0.9794 | - |
+| 8.3417 | 66400 | 0.0033 | 0.0568 | 0.9795 | - |
+| 8.3543 | 66500 | 0.0034 | 0.0567 | 0.9793 | - |
+| 8.3668 | 66600 | 0.0034 | 0.0568 | 0.9796 | - |
+| 8.3794 | 66700 | 0.0037 | 0.0561 | 0.9795 | - |
+| 8.3920 | 66800 | 0.0035 | 0.0562 | 0.9795 | - |
+| 8.4045 | 66900 | 0.0041 | 0.0561 | 0.9797 | - |
+| 8.4171 | 67000 | 0.004 | 0.0566 | 0.9796 | - |
+| 8.4296 | 67100 | 0.0041 | 0.0566 | 0.9799 | - |
+| 8.4422 | 67200 | 0.0038 | 0.0550 | 0.9801 | - |
+| 8.4548 | 67300 | 0.0035 | 0.0566 | 0.9798 | - |
+| 8.4673 | 67400 | 0.0034 | 0.0554 | 0.9797 | - |
+| 8.4799 | 67500 | 0.0035 | 0.0556 | 0.9796 | - |
+| 8.4925 | 67600 | 0.004 | 0.0569 | 0.9794 | - |
+| 8.5050 | 67700 | 0.0041 | 0.0565 | 0.9796 | - |
+| 8.5176 | 67800 | 0.004 | 0.0569 | 0.9796 | - |
+| 8.5302 | 67900 | 0.0034 | 0.0570 | 0.9796 | - |
+| 8.5427 | 68000 | 0.0043 | 0.0556 | 0.9798 | - |
+| 8.5553 | 68100 | 0.0045 | 0.0560 | 0.9799 | - |
+| 8.5678 | 68200 | 0.003 | 0.0566 | 0.9798 | - |
+| 8.5804 | 68300 | 0.0034 | 0.0570 | 0.9796 | - |
+| 8.5930 | 68400 | 0.004 | 0.0563 | 0.9796 | - |
+| 8.6055 | 68500 | 0.0036 | 0.0587 | 0.9794 | - |
+| 8.6181 | 68600 | 0.0041 | 0.0556 | 0.9797 | - |
+| 8.6307 | 68700 | 0.0034 | 0.0577 | 0.9797 | - |
+| 8.6432 | 68800 | 0.0037 | 0.0580 | 0.9795 | - |
+| 8.6558 | 68900 | 0.004 | 0.0564 | 0.9799 | - |
+| 8.6683 | 69000 | 0.0038 | 0.0559 | 0.9800 | - |
+| 8.6809 | 69100 | 0.0034 | 0.0564 | 0.9801 | - |
+| 8.6935 | 69200 | 0.0039 | 0.0570 | 0.9799 | - |
+| 8.7060 | 69300 | 0.0037 | 0.0574 | 0.9799 | - |
+| 8.7186 | 69400 | 0.0044 | 0.0555 | 0.9802 | - |
+| 8.7312 | 69500 | 0.0037 | 0.0553 | 0.9803 | - |
+| 8.7437 | 69600 | 0.0037 | 0.0540 | 0.9803 | - |
+| 8.7563 | 69700 | 0.0033 | 0.0550 | 0.9802 | - |
+| 8.7688 | 69800 | 0.0042 | 0.0560 | 0.9801 | - |
+| 8.7814 | 69900 | 0.0036 | 0.0559 | 0.9801 | - |
+| 8.7940 | 70000 | 0.0037 | 0.0570 | 0.9801 | - |
+| 8.8065 | 70100 | 0.0042 | 0.0567 | 0.9801 | - |
+| 8.8191 | 70200 | 0.0042 | 0.0567 | 0.9802 | - |
+| 8.8317 | 70300 | 0.0038 | 0.0566 | 0.9801 | - |
+| 8.8442 | 70400 | 0.0034 | 0.0570 | 0.9798 | - |
+| 8.8568 | 70500 | 0.0042 | 0.0562 | 0.9800 | - |
+| 8.8693 | 70600 | 0.0041 | 0.0558 | 0.9800 | - |
+| 8.8819 | 70700 | 0.0042 | 0.0549 | 0.9801 | - |
+| 8.8945 | 70800 | 0.0037 | 0.0568 | 0.9800 | - |
+| 8.9070 | 70900 | 0.0041 | 0.0552 | 0.9802 | - |
+| 8.9196 | 71000 | 0.0036 | 0.0561 | 0.9800 | - |
+| 8.9322 | 71100 | 0.0044 | 0.0557 | 0.9800 | - |
+| 8.9447 | 71200 | 0.0043 | 0.0553 | 0.9801 | - |
+| 8.9573 | 71300 | 0.0035 | 0.0572 | 0.9801 | - |
+| 8.9698 | 71400 | 0.0039 | 0.0567 | 0.9801 | - |
+| 8.9824 | 71500 | 0.0037 | 0.0575 | 0.9800 | - |
+| 8.9950 | 71600 | 0.0035 | 0.0565 | 0.9801 | - |
+| 9.0075 | 71700 | 0.0041 | 0.0560 | 0.9800 | - |
+| 9.0201 | 71800 | 0.0028 | 0.0569 | 0.9798 | - |
+| 9.0327 | 71900 | 0.0032 | 0.0565 | 0.9798 | - |
+| 9.0452 | 72000 | 0.0029 | 0.0561 | 0.9797 | - |
+| 9.0578 | 72100 | 0.0026 | 0.0552 | 0.9798 | - |
+| 9.0704 | 72200 | 0.0032 | 0.0564 | 0.9797 | - |
+| 9.0829 | 72300 | 0.0032 | 0.0574 | 0.9796 | - |
+| 9.0955 | 72400 | 0.0026 | 0.0578 | 0.9795 | - |
+| 9.1080 | 72500 | 0.003 | 0.0567 | 0.9797 | - |
+| 9.1206 | 72600 | 0.003 | 0.0561 | 0.9797 | - |
+| 9.1332 | 72700 | 0.0031 | 0.0570 | 0.9796 | - |
+| 9.1457 | 72800 | 0.0028 | 0.0572 | 0.9797 | - |
+| 9.1583 | 72900 | 0.0031 | 0.0568 | 0.9796 | - |
+| 9.1709 | 73000 | 0.0029 | 0.0575 | 0.9796 | - |
+| 9.1834 | 73100 | 0.0031 | 0.0571 | 0.9795 | - |
+| 9.1960 | 73200 | 0.0028 | 0.0571 | 0.9795 | - |
+| 9.2085 | 73300 | 0.0027 | 0.0564 | 0.9794 | - |
+| 9.2211 | 73400 | 0.0033 | 0.0573 | 0.9795 | - |
+| 9.2337 | 73500 | 0.0034 | 0.0569 | 0.9796 | - |
+| 9.2462 | 73600 | 0.0032 | 0.0580 | 0.9795 | - |
+| 9.2588 | 73700 | 0.0033 | 0.0574 | 0.9795 | - |
+| 9.2714 | 73800 | 0.0034 | 0.0578 | 0.9795 | - |
+| 9.2839 | 73900 | 0.0031 | 0.0580 | 0.9793 | - |
+| 9.2965 | 74000 | 0.0038 | 0.0569 | 0.9794 | - |
+| 9.3090 | 74100 | 0.0027 | 0.0565 | 0.9795 | - |
+| 9.3216 | 74200 | 0.0027 | 0.0575 | 0.9794 | - |
+| 9.3342 | 74300 | 0.0031 | 0.0589 | 0.9791 | - |
+| 9.3467 | 74400 | 0.0035 | 0.0589 | 0.9792 | - |
+| 9.3593 | 74500 | 0.0033 | 0.0580 | 0.9793 | - |
+| 9.3719 | 74600 | 0.0028 | 0.0579 | 0.9792 | - |
+| 9.3844 | 74700 | 0.0035 | 0.0572 | 0.9793 | - |
+| 9.3970 | 74800 | 0.0031 | 0.0568 | 0.9794 | - |
+| 9.4095 | 74900 | 0.0035 | 0.0577 | 0.9793 | - |
+| 9.4221 | 75000 | 0.0032 | 0.0574 | 0.9793 | - |
+| 9.4347 | 75100 | 0.0027 | 0.0577 | 0.9793 | - |
+| 9.4472 | 75200 | 0.0037 | 0.0584 | 0.9792 | - |
+| 9.4598 | 75300 | 0.003 | 0.0585 | 0.9792 | - |
+| 9.4724 | 75400 | 0.0028 | 0.0580 | 0.9792 | - |
+| 9.4849 | 75500 | 0.0036 | 0.0579 | 0.9793 | - |
+| 9.4975 | 75600 | 0.0034 | 0.0581 | 0.9793 | - |
+| 9.5101 | 75700 | 0.0033 | 0.0579 | 0.9793 | - |
+| 9.5226 | 75800 | 0.0035 | 0.0575 | 0.9793 | - |
+| 9.5352 | 75900 | 0.0028 | 0.0567 | 0.9794 | - |
+| 9.5477 | 76000 | 0.0031 | 0.0570 | 0.9793 | - |
+| 9.5603 | 76100 | 0.0029 | 0.0578 | 0.9792 | - |
+| 9.5729 | 76200 | 0.0036 | 0.0583 | 0.9792 | - |
+| 9.5854 | 76300 | 0.0033 | 0.0578 | 0.9792 | - |
+| 9.5980 | 76400 | 0.0028 | 0.0576 | 0.9792 | - |
+| 9.6106 | 76500 | 0.0029 | 0.0580 | 0.9792 | - |
+| 9.6231 | 76600 | 0.0026 | 0.0577 | 0.9792 | - |
+| 9.6357 | 76700 | 0.0031 | 0.0577 | 0.9792 | - |
+| 9.6482 | 76800 | 0.0032 | 0.0579 | 0.9791 | - |
+| 9.6608 | 76900 | 0.0033 | 0.0579 | 0.9791 | - |
+| 9.6734 | 77000 | 0.0031 | 0.0583 | 0.9791 | - |
+| 9.6859 | 77100 | 0.0035 | 0.0582 | 0.9791 | - |
+| 9.6985 | 77200 | 0.0034 | 0.0578 | 0.9792 | - |
+| 9.7111 | 77300 | 0.0027 | 0.0580 | 0.9791 | - |
+| 9.7236 | 77400 | 0.0031 | 0.0579 | 0.9791 | - |
+| 9.7362 | 77500 | 0.003 | 0.0583 | 0.9791 | - |
+| 9.7487 | 77600 | 0.0037 | 0.0582 | 0.9791 | - |
+| 9.7613 | 77700 | 0.0026 | 0.0582 | 0.9791 | - |
+| 9.7739 | 77800 | 0.0031 | 0.0582 | 0.9791 | - |
+| 9.7864 | 77900 | 0.0031 | 0.0581 | 0.9792 | - |
+| 9.7990 | 78000 | 0.0032 | 0.0579 | 0.9792 | - |
+| 9.8116 | 78100 | 0.0034 | 0.0581 | 0.9792 | - |
+| 9.8241 | 78200 | 0.0033 | 0.0581 | 0.9792 | - |
+| 9.8367 | 78300 | 0.0035 | 0.0583 | 0.9792 | - |
+| 9.8492 | 78400 | 0.0031 | 0.0584 | 0.9791 | - |
+| 9.8618 | 78500 | 0.0036 | 0.0581 | 0.9792 | - |
+| 9.8744 | 78600 | 0.0026 | 0.0582 | 0.9792 | - |
+| 9.8869 | 78700 | 0.0032 | 0.0579 | 0.9792 | - |
+| 9.8995 | 78800 | 0.0034 | 0.0579 | 0.9792 | - |
+| 9.9121 | 78900 | 0.003 | 0.0581 | 0.9792 | - |
+| 9.9246 | 79000 | 0.0028 | 0.0580 | 0.9792 | - |
+| 9.9372 | 79100 | 0.003 | 0.0580 | 0.9792 | - |
+| 9.9497 | 79200 | 0.0033 | 0.0580 | 0.9792 | - |
+| 9.9623 | 79300 | 0.0033 | 0.0580 | 0.9792 | - |
+| 9.9749 | 79400 | 0.0036 | 0.0579 | 0.9792 | - |
+| 9.9874 | 79500 | 0.0031 | 0.0580 | 0.9792 | - |
+| 10.0 | 79600 | 0.0031 | 0.0580 | 0.9792 | 0.9822 |
+
+