--- language: - en license: apache-2.0 tags: - sentence-transformers - sentence-similarity - feature-extraction - generated_from_trainer - dataset_size:6300 - loss:MatryoshkaLoss - loss:MultipleNegativesRankingLoss base_model: BAAI/bge-base-en-v1.5 widget: - source_sentence: Termination of the Arm Share Purchase Agreement In February 2022, NVIDIA and SoftBank Group Corp., or SoftBank, announced the termination of the Share Purchase Agreement whereby NVIDIA would have acquired Arm Limited, or Arm, from SoftBank. The parties agreed to terminate because of significant regulatory challenges preventing the completion of the transaction. sentences: - How did eBay's net revenues from the first quarter of 2023 compare to the last quarter of 2022? - Why did NVIDIA and SoftBank terminate their Share Purchase Agreement for acquiring Arm Limited? - What effects did the implementation of the Reinvention Plan have on the company's financial statements in fiscal years 2022 and 2023? - source_sentence: In the fiscal year 2023, it was disclosed that $1,963 million of certain accumulated foreign earnings continue to be indefinitely reinvested. sentences: - What does the company imply about the severity of the lawsuits and regulatory proceedings they are involved in? - How much has been indefinitely reinvested from accumulated foreign earnings as of fiscal year 2023? - Are the consolidated financial statements and notes included directly in Item 8 of the Annual Report on Form 10-K? - source_sentence: The November 2029 fixed-to-floating rate Senior Notes bear interest at a fixed rate of 6.196%, payable semi-annually, until the interest reset date on November 17, 2028. sentences: - What is the fixed interest rate for the November 2029 fixed-to-floating rate Senior Notes before the reset date? - What is the weighted-average remaining term of the financing obligations as of December 31, 2023? - How long has Humana participated in the Medicare program for private health plans? - source_sentence: Our material cash requirements include debt repayment obligations of $1.9 billion. sentences: - What percentage is the initial preferred distribution for the April preferreds issued by AT&T in 2023? - What are the two main service segments of The Charles Schwab Corporation? - What is the total debt repayment obligation mentioned in the financial outline? - source_sentence: New stores | 131 | | 333 | | 464 | | 311 | | 225 | 536 sentences: - How many new stores did the Dollar Tree segment open in the fiscal year ending January 28, 2023? - How is the discount rate for the Family Dollar goodwill impairment evaluation determined? - What does IBM’s 2023 Annual Report to Stockholders include? pipeline_tag: sentence-similarity library_name: sentence-transformers metrics: - cosine_accuracy@1 - cosine_accuracy@3 - cosine_accuracy@5 - cosine_accuracy@10 - cosine_precision@1 - cosine_precision@3 - cosine_precision@5 - cosine_precision@10 - cosine_recall@1 - cosine_recall@3 - cosine_recall@5 - cosine_recall@10 - cosine_ndcg@10 - cosine_mrr@10 - cosine_map@100 model-index: - name: BGE base Financial Matryoshka results: - task: type: information-retrieval name: Information Retrieval dataset: name: dim 768 type: dim_768 metrics: - type: cosine_accuracy@1 value: 0.6628571428571428 name: Cosine Accuracy@1 - type: cosine_accuracy@3 value: 0.8128571428571428 name: Cosine Accuracy@3 - type: cosine_accuracy@5 value: 0.8385714285714285 name: Cosine Accuracy@5 - type: cosine_accuracy@10 value: 0.8871428571428571 name: Cosine Accuracy@10 - type: cosine_precision@1 value: 0.6628571428571428 name: Cosine Precision@1 - type: cosine_precision@3 value: 0.270952380952381 name: Cosine Precision@3 - type: cosine_precision@5 value: 0.16771428571428568 name: Cosine Precision@5 - type: cosine_precision@10 value: 0.0887142857142857 name: Cosine Precision@10 - type: cosine_recall@1 value: 0.6628571428571428 name: Cosine Recall@1 - type: cosine_recall@3 value: 0.8128571428571428 name: Cosine Recall@3 - type: cosine_recall@5 value: 0.8385714285714285 name: Cosine Recall@5 - type: cosine_recall@10 value: 0.8871428571428571 name: Cosine Recall@10 - type: cosine_ndcg@10 value: 0.7771376992897233 name: Cosine Ndcg@10 - type: cosine_mrr@10 value: 0.7417278911564624 name: Cosine Mrr@10 - type: cosine_map@100 value: 0.7459340014094423 name: Cosine Map@100 - task: type: information-retrieval name: Information Retrieval dataset: name: dim 512 type: dim_512 metrics: - type: cosine_accuracy@1 value: 0.66 name: Cosine Accuracy@1 - type: cosine_accuracy@3 value: 0.8114285714285714 name: Cosine Accuracy@3 - type: cosine_accuracy@5 value: 0.84 name: Cosine Accuracy@5 - type: cosine_accuracy@10 value: 0.8871428571428571 name: Cosine Accuracy@10 - type: cosine_precision@1 value: 0.66 name: Cosine Precision@1 - type: cosine_precision@3 value: 0.2704761904761904 name: Cosine Precision@3 - type: cosine_precision@5 value: 0.16799999999999998 name: Cosine Precision@5 - type: cosine_precision@10 value: 0.0887142857142857 name: Cosine Precision@10 - type: cosine_recall@1 value: 0.66 name: Cosine Recall@1 - type: cosine_recall@3 value: 0.8114285714285714 name: Cosine Recall@3 - type: cosine_recall@5 value: 0.84 name: Cosine Recall@5 - type: cosine_recall@10 value: 0.8871428571428571 name: Cosine Recall@10 - type: cosine_ndcg@10 value: 0.7738952698065006 name: Cosine Ndcg@10 - type: cosine_mrr@10 value: 0.7376156462585033 name: Cosine Mrr@10 - type: cosine_map@100 value: 0.7416047303260471 name: Cosine Map@100 - task: type: information-retrieval name: Information Retrieval dataset: name: dim 256 type: dim_256 metrics: - type: cosine_accuracy@1 value: 0.6671428571428571 name: Cosine Accuracy@1 - type: cosine_accuracy@3 value: 0.8057142857142857 name: Cosine Accuracy@3 - type: cosine_accuracy@5 value: 0.8371428571428572 name: Cosine Accuracy@5 - type: cosine_accuracy@10 value: 0.88 name: Cosine Accuracy@10 - type: cosine_precision@1 value: 0.6671428571428571 name: Cosine Precision@1 - type: cosine_precision@3 value: 0.26857142857142857 name: Cosine Precision@3 - type: cosine_precision@5 value: 0.1674285714285714 name: Cosine Precision@5 - type: cosine_precision@10 value: 0.088 name: Cosine Precision@10 - type: cosine_recall@1 value: 0.6671428571428571 name: Cosine Recall@1 - type: cosine_recall@3 value: 0.8057142857142857 name: Cosine Recall@3 - type: cosine_recall@5 value: 0.8371428571428572 name: Cosine Recall@5 - type: cosine_recall@10 value: 0.88 name: Cosine Recall@10 - type: cosine_ndcg@10 value: 0.7749410226388818 name: Cosine Ndcg@10 - type: cosine_mrr@10 value: 0.7410992063492059 name: Cosine Mrr@10 - type: cosine_map@100 value: 0.745220616023529 name: Cosine Map@100 - task: type: information-retrieval name: Information Retrieval dataset: name: dim 128 type: dim_128 metrics: - type: cosine_accuracy@1 value: 0.6342857142857142 name: Cosine Accuracy@1 - type: cosine_accuracy@3 value: 0.79 name: Cosine Accuracy@3 - type: cosine_accuracy@5 value: 0.8314285714285714 name: Cosine Accuracy@5 - type: cosine_accuracy@10 value: 0.8728571428571429 name: Cosine Accuracy@10 - type: cosine_precision@1 value: 0.6342857142857142 name: Cosine Precision@1 - type: cosine_precision@3 value: 0.2633333333333333 name: Cosine Precision@3 - type: cosine_precision@5 value: 0.1662857142857143 name: Cosine Precision@5 - type: cosine_precision@10 value: 0.08728571428571427 name: Cosine Precision@10 - type: cosine_recall@1 value: 0.6342857142857142 name: Cosine Recall@1 - type: cosine_recall@3 value: 0.79 name: Cosine Recall@3 - type: cosine_recall@5 value: 0.8314285714285714 name: Cosine Recall@5 - type: cosine_recall@10 value: 0.8728571428571429 name: Cosine Recall@10 - type: cosine_ndcg@10 value: 0.7567972995851519 name: Cosine Ndcg@10 - type: cosine_mrr@10 value: 0.7192930839002263 name: Cosine Mrr@10 - type: cosine_map@100 value: 0.7237935936286254 name: Cosine Map@100 - task: type: information-retrieval name: Information Retrieval dataset: name: dim 64 type: dim_64 metrics: - type: cosine_accuracy@1 value: 0.6285714285714286 name: Cosine Accuracy@1 - type: cosine_accuracy@3 value: 0.7671428571428571 name: Cosine Accuracy@3 - type: cosine_accuracy@5 value: 0.8142857142857143 name: Cosine Accuracy@5 - type: cosine_accuracy@10 value: 0.8728571428571429 name: Cosine Accuracy@10 - type: cosine_precision@1 value: 0.6285714285714286 name: Cosine Precision@1 - type: cosine_precision@3 value: 0.2557142857142857 name: Cosine Precision@3 - type: cosine_precision@5 value: 0.16285714285714287 name: Cosine Precision@5 - type: cosine_precision@10 value: 0.08728571428571427 name: Cosine Precision@10 - type: cosine_recall@1 value: 0.6285714285714286 name: Cosine Recall@1 - type: cosine_recall@3 value: 0.7671428571428571 name: Cosine Recall@3 - type: cosine_recall@5 value: 0.8142857142857143 name: Cosine Recall@5 - type: cosine_recall@10 value: 0.8728571428571429 name: Cosine Recall@10 - type: cosine_ndcg@10 value: 0.7483704138772564 name: Cosine Ndcg@10 - type: cosine_mrr@10 value: 0.7087936507936506 name: Cosine Mrr@10 - type: cosine_map@100 value: 0.7127238799035323 name: Cosine Map@100 --- # BGE base Financial Matryoshka This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [BAAI/bge-base-en-v1.5](https://huggingface.co/BAAI/bge-base-en-v1.5) on the json 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:** [BAAI/bge-base-en-v1.5](https://huggingface.co/BAAI/bge-base-en-v1.5) - **Maximum Sequence Length:** 512 tokens - **Output Dimensionality:** 768 dimensions - **Similarity Function:** Cosine Similarity - **Training Dataset:** - json - **Language:** en - **License:** apache-2.0 ### 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': True}) with Transformer model: BertModel (1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True}) (2): Normalize() ) ``` ## Usage ### Direct Usage (Sentence Transformers) First install the Sentence Transformers library: ```bash pip install -U sentence-transformers ``` Then you can load this model and run inference. ```python from sentence_transformers import SentenceTransformer # Download from the 🤗 Hub model = SentenceTransformer("thang1943/bge-base-financial-matryoshka") # Run inference sentences = [ 'New stores | 131 | | 333 | | 464 | | 311 | | 225 | 536', 'How many new stores did the Dollar Tree segment open in the fiscal year ending January 28, 2023?', 'How is the discount rate for the Family Dollar goodwill impairment evaluation determined?', ] 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 #### Information Retrieval * Datasets: `dim_768`, `dim_512`, `dim_256`, `dim_128` and `dim_64` * Evaluated with [InformationRetrievalEvaluator](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.InformationRetrievalEvaluator) | Metric | dim_768 | dim_512 | dim_256 | dim_128 | dim_64 | |:--------------------|:-----------|:-----------|:-----------|:-----------|:-----------| | cosine_accuracy@1 | 0.6629 | 0.66 | 0.6671 | 0.6343 | 0.6286 | | cosine_accuracy@3 | 0.8129 | 0.8114 | 0.8057 | 0.79 | 0.7671 | | cosine_accuracy@5 | 0.8386 | 0.84 | 0.8371 | 0.8314 | 0.8143 | | cosine_accuracy@10 | 0.8871 | 0.8871 | 0.88 | 0.8729 | 0.8729 | | cosine_precision@1 | 0.6629 | 0.66 | 0.6671 | 0.6343 | 0.6286 | | cosine_precision@3 | 0.271 | 0.2705 | 0.2686 | 0.2633 | 0.2557 | | cosine_precision@5 | 0.1677 | 0.168 | 0.1674 | 0.1663 | 0.1629 | | cosine_precision@10 | 0.0887 | 0.0887 | 0.088 | 0.0873 | 0.0873 | | cosine_recall@1 | 0.6629 | 0.66 | 0.6671 | 0.6343 | 0.6286 | | cosine_recall@3 | 0.8129 | 0.8114 | 0.8057 | 0.79 | 0.7671 | | cosine_recall@5 | 0.8386 | 0.84 | 0.8371 | 0.8314 | 0.8143 | | cosine_recall@10 | 0.8871 | 0.8871 | 0.88 | 0.8729 | 0.8729 | | **cosine_ndcg@10** | **0.7771** | **0.7739** | **0.7749** | **0.7568** | **0.7484** | | cosine_mrr@10 | 0.7417 | 0.7376 | 0.7411 | 0.7193 | 0.7088 | | cosine_map@100 | 0.7459 | 0.7416 | 0.7452 | 0.7238 | 0.7127 | ## Training Details ### Training Dataset #### json * Dataset: json * Size: 6,300 training samples * Columns: positive and anchor * Approximate statistics based on the first 1000 samples: | | positive | anchor | |:--------|:-----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | | details | | | * Samples: | positive | anchor | |:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------------------------------------------------------------------------| | In their 2023 forward-looking statements, Goldman Sachs mentioned that results, financial condition, liquidity, and capital actions may differ, possibly materially, from the anticipated results. Important factors include those described in "Risk Factors" in Part I, Item 1A and "Forward-Looking Statements" in Part I, Item 1. | What factors could potentially alter Goldman Sachs' anticipated financial outcomes according to their 2023 forward-looking statements? | | Visa Direct is part of Visa’s strategy beyond C2B payments and helps facilitate the delivery of funds to eligible cards, deposit accounts and digital wallets across more than 190 countries and territories. Visa Direct supports multiple use cases, such as P2P payments and account-to-account transfers, business and government payouts to individuals or small businesses, merchant settlements and refunds. | What is the purpose of Visa Direct? | | The Company's international operations are subject to different, and sometimes more stringent, legal and regulatory requirements, which vary widely by jurisdiction, including anti-corruption laws; economic sanctions laws; various privacy, insurance, tax, tariff and trade laws and regulations; corporate governance, privacy, data protection (including the EU's General Data Protection Regulation which began to apply across the EU during 2018), data mining, data transfer, labor and employment, intellectual property, consumer protection and investment laws and regulations; discriminatory licensing procedures; compulsory cessions of reinsurance; required localization of records and funds; higher premium and income taxes; limitations on dividends and repatriation of capital; and requirements for local participation in an insurer's ownership. | What types of laws and regulations govern the international operations of a company? | * Loss: [MatryoshkaLoss](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#matryoshkaloss) with these parameters: ```json { "loss": "MultipleNegativesRankingLoss", "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`: epoch - `per_device_train_batch_size`: 2 - `per_device_eval_batch_size`: 1 - `learning_rate`: 2e-05 - `num_train_epochs`: 4 - `lr_scheduler_type`: cosine - `warmup_ratio`: 0.1 - `bf16`: True - `tf32`: False - `load_best_model_at_end`: True - `optim`: adamw_torch_fused - `batch_sampler`: no_duplicates #### All Hyperparameters
Click to expand - `overwrite_output_dir`: False - `do_predict`: False - `eval_strategy`: epoch - `prediction_loss_only`: True - `per_device_train_batch_size`: 2 - `per_device_eval_batch_size`: 1 - `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`: 4 - `max_steps`: -1 - `lr_scheduler_type`: cosine - `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`: True - `fp16`: False - `fp16_opt_level`: O1 - `half_precision_backend`: auto - `bf16_full_eval`: False - `fp16_full_eval`: False - `tf32`: False - `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`: True - `ignore_data_skip`: False - `fsdp`: [] - `fsdp_min_num_params`: 0 - `fsdp_config`: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False} - `fsdp_transformer_layer_cls_to_wrap`: None - `accelerator_config`: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None} - `deepspeed`: None - `label_smoothing_factor`: 0.0 - `optim`: adamw_torch_fused - `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`: None - `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`: no_duplicates - `multi_dataset_batch_sampler`: proportional
### Training Logs
Click to expand | Epoch | Step | Training Loss | dim_768_cosine_ndcg@10 | dim_512_cosine_ndcg@10 | dim_256_cosine_ndcg@10 | dim_128_cosine_ndcg@10 | dim_64_cosine_ndcg@10 | |:-------:|:--------:|:-------------:|:----------------------:|:----------------------:|:----------------------:|:----------------------:|:---------------------:| | 0.0032 | 10 | 0.271 | - | - | - | - | - | | 0.0063 | 20 | 0.0452 | - | - | - | - | - | | 0.0095 | 30 | 0.2152 | - | - | - | - | - | | 0.0127 | 40 | 0.0658 | - | - | - | - | - | | 0.0159 | 50 | 0.5701 | - | - | - | - | - | | 0.0190 | 60 | 0.0882 | - | - | - | - | - | | 0.0222 | 70 | 0.0902 | - | - | - | - | - | | 0.0254 | 80 | 0.8865 | - | - | - | - | - | | 0.0286 | 90 | 0.1985 | - | - | - | - | - | | 0.0317 | 100 | 0.2853 | - | - | - | - | - | | 0.0349 | 110 | 0.2637 | - | - | - | - | - | | 0.0381 | 120 | 0.007 | - | - | - | - | - | | 0.0413 | 130 | 0.0432 | - | - | - | - | - | | 0.0444 | 140 | 0.0126 | - | - | - | - | - | | 0.0476 | 150 | 0.0174 | - | - | - | - | - | | 0.0508 | 160 | 0.2123 | - | - | - | - | - | | 0.0540 | 170 | 0.0489 | - | - | - | - | - | | 0.0571 | 180 | 0.0306 | - | - | - | - | - | | 0.0603 | 190 | 0.0032 | - | - | - | - | - | | 0.0635 | 200 | 0.027 | - | - | - | - | - | | 0.0667 | 210 | 0.0131 | - | - | - | - | - | | 0.0698 | 220 | 0.0164 | - | - | - | - | - | | 0.0730 | 230 | 0.0044 | - | - | - | - | - | | 0.0762 | 240 | 0.0119 | - | - | - | - | - | | 0.0794 | 250 | 0.0539 | - | - | - | - | - | | 0.0825 | 260 | 0.0425 | - | - | - | - | - | | 0.0857 | 270 | 0.0213 | - | - | - | - | - | | 0.0889 | 280 | 0.0676 | - | - | - | - | - | | 0.0921 | 290 | 0.029 | - | - | - | - | - | | 0.0952 | 300 | 0.0147 | - | - | - | - | - | | 0.0984 | 310 | 0.0201 | - | - | - | - | - | | 0.1016 | 320 | 0.0112 | - | - | - | - | - | | 0.1048 | 330 | 0.0236 | - | - | - | - | - | | 0.1079 | 340 | 0.0619 | - | - | - | - | - | | 0.1111 | 350 | 0.0521 | - | - | - | - | - | | 0.1143 | 360 | 0.034 | - | - | - | - | - | | 0.1175 | 370 | 0.0729 | - | - | - | - | - | | 0.1206 | 380 | 0.6353 | - | - | - | - | - | | 0.1238 | 390 | 0.0053 | - | - | - | - | - | | 0.1270 | 400 | 0.0047 | - | - | - | - | - | | 0.1302 | 410 | 0.0038 | - | - | - | - | - | | 0.1333 | 420 | 0.1795 | - | - | - | - | - | | 0.1365 | 430 | 0.0715 | - | - | - | - | - | | 0.1397 | 440 | 0.0328 | - | - | - | - | - | | 0.1429 | 450 | 0.0301 | - | - | - | - | - | | 0.1460 | 460 | 0.0163 | - | - | - | - | - | | 0.1492 | 470 | 0.0515 | - | - | - | - | - | | 0.1524 | 480 | 0.0009 | - | - | - | - | - | | 0.1556 | 490 | 0.0645 | - | - | - | - | - | | 0.1587 | 500 | 0.0024 | - | - | - | - | - | | 0.1619 | 510 | 0.0833 | - | - | - | - | - | | 0.1651 | 520 | 0.0052 | - | - | - | - | - | | 0.1683 | 530 | 0.0056 | - | - | - | - | - | | 0.1714 | 540 | 0.164 | - | - | - | - | - | | 0.1746 | 550 | 0.0054 | - | - | - | - | - | | 0.1778 | 560 | 0.0446 | - | - | - | - | - | | 0.1810 | 570 | 0.001 | - | - | - | - | - | | 0.1841 | 580 | 0.0869 | - | - | - | - | - | | 0.1873 | 590 | 0.0036 | - | - | - | - | - | | 0.1905 | 600 | 0.022 | - | - | - | - | - | | 0.1937 | 610 | 0.0025 | - | - | - | - | - | | 0.1968 | 620 | 0.0112 | - | - | - | - | - | | 0.2 | 630 | 0.0005 | - | - | - | - | - | | 0.2032 | 640 | 0.0047 | - | - | - | - | - | | 0.2063 | 650 | 0.0003 | - | - | - | - | - | | 0.2095 | 660 | 0.089 | - | - | - | - | - | | 0.2127 | 670 | 0.0009 | - | - | - | - | - | | 0.2159 | 680 | 0.0012 | - | - | - | - | - | | 0.2190 | 690 | 0.0278 | - | - | - | - | - | | 0.2222 | 700 | 0.0013 | - | - | - | - | - | | 0.2254 | 710 | 0.0017 | - | - | - | - | - | | 0.2286 | 720 | 0.0137 | - | - | - | - | - | | 0.2317 | 730 | 0.2628 | - | - | - | - | - | | 0.2349 | 740 | 0.011 | - | - | - | - | - | | 0.2381 | 750 | 0.9877 | - | - | - | - | - | | 0.2413 | 760 | 0.0166 | - | - | - | - | - | | 0.2444 | 770 | 0.03 | - | - | - | - | - | | 0.2476 | 780 | 0.5091 | - | - | - | - | - | | 0.2508 | 790 | 0.0057 | - | - | - | - | - | | 0.2540 | 800 | 0.0003 | - | - | - | - | - | | 0.2571 | 810 | 0.0002 | - | - | - | - | - | | 0.2603 | 820 | 0.0515 | - | - | - | - | - | | 0.2635 | 830 | 0.134 | - | - | - | - | - | | 0.2667 | 840 | 0.0033 | - | - | - | - | - | | 0.2698 | 850 | 0.0046 | - | - | - | - | - | | 0.2730 | 860 | 0.004 | - | - | - | - | - | | 0.2762 | 870 | 0.0017 | - | - | - | - | - | | 0.2794 | 880 | 0.0027 | - | - | - | - | - | | 0.2825 | 890 | 0.0946 | - | - | - | - | - | | 0.2857 | 900 | 0.0016 | - | - | - | - | - | | 0.2889 | 910 | 0.0057 | - | - | - | - | - | | 0.2921 | 920 | 0.0005 | - | - | - | - | - | | 0.2952 | 930 | 0.0145 | - | - | - | - | - | | 0.2984 | 940 | 0.0049 | - | - | - | - | - | | 0.3016 | 950 | 0.0008 | - | - | - | - | - | | 0.3048 | 960 | 0.0013 | - | - | - | - | - | | 0.3079 | 970 | 0.0245 | - | - | - | - | - | | 0.3111 | 980 | 0.0012 | - | - | - | - | - | | 0.3143 | 990 | 0.0051 | - | - | - | - | - | | 0.3175 | 1000 | 0.0016 | - | - | - | - | - | | 0.3206 | 1010 | 0.0014 | - | - | - | - | - | | 0.3238 | 1020 | 0.0002 | - | - | - | - | - | | 0.3270 | 1030 | 0.0021 | - | - | - | - | - | | 0.3302 | 1040 | 0.0038 | - | - | - | - | - | | 0.3333 | 1050 | 0.0084 | - | - | - | - | - | | 0.3365 | 1060 | 0.0044 | - | - | - | - | - | | 0.3397 | 1070 | 0.0002 | - | - | - | - | - | | 0.3429 | 1080 | 0.0058 | - | - | - | - | - | | 0.3460 | 1090 | 0.008 | - | - | - | - | - | | 0.3492 | 1100 | 0.0008 | - | - | - | - | - | | 0.3524 | 1110 | 0.0043 | - | - | - | - | - | | 0.3556 | 1120 | 0.1245 | - | - | - | - | - | | 0.3587 | 1130 | 0.0037 | - | - | - | - | - | | 0.3619 | 1140 | 0.581 | - | - | - | - | - | | 0.3651 | 1150 | 0.0011 | - | - | - | - | - | | 0.3683 | 1160 | 0.0061 | - | - | - | - | - | | 0.3714 | 1170 | 0.0292 | - | - | - | - | - | | 0.3746 | 1180 | 0.005 | - | - | - | - | - | | 0.3778 | 1190 | 0.003 | - | - | - | - | - | | 0.3810 | 1200 | 0.0003 | - | - | - | - | - | | 0.3841 | 1210 | 0.0007 | - | - | - | - | - | | 0.3873 | 1220 | 0.5248 | - | - | - | - | - | | 0.3905 | 1230 | 0.3122 | - | - | - | - | - | | 0.3937 | 1240 | 0.0079 | - | - | - | - | - | | 0.3968 | 1250 | 0.014 | - | - | - | - | - | | 0.4 | 1260 | 0.0271 | - | - | - | - | - | | 0.4032 | 1270 | 0.0043 | - | - | - | - | - | | 0.4063 | 1280 | 0.0005 | - | - | - | - | - | | 0.4095 | 1290 | 0.0012 | - | - | - | - | - | | 0.4127 | 1300 | 0.0179 | - | - | - | - | - | | 0.4159 | 1310 | 0.0011 | - | - | - | - | - | | 0.4190 | 1320 | 0.0048 | - | - | - | - | - | | 0.4222 | 1330 | 0.002 | - | - | - | - | - | | 0.4254 | 1340 | 0.0002 | - | - | - | - | - | | 0.4286 | 1350 | 0.0091 | - | - | - | - | - | | 0.4317 | 1360 | 0.0002 | - | - | - | - | - | | 0.4349 | 1370 | 0.0137 | - | - | - | - | - | | 0.4381 | 1380 | 0.017 | - | - | - | - | - | | 0.4413 | 1390 | 0.0007 | - | - | - | - | - | | 0.4444 | 1400 | 0.001 | - | - | - | - | - | | 0.4476 | 1410 | 0.0015 | - | - | - | - | - | | 0.4508 | 1420 | 0.0015 | - | - | - | - | - | | 0.4540 | 1430 | 0.0002 | - | - | - | - | - | | 0.4571 | 1440 | 0.125 | - | - | - | - | - | | 0.4603 | 1450 | 0.0014 | - | - | - | - | - | | 0.4635 | 1460 | 0.0019 | - | - | - | - | - | | 0.4667 | 1470 | 0.0061 | - | - | - | - | - | | 0.4698 | 1480 | 0.0019 | - | - | - | - | - | | 0.4730 | 1490 | 0.0045 | - | - | - | - | - | | 0.4762 | 1500 | 0.004 | - | - | - | - | - | | 0.4794 | 1510 | 0.0003 | - | - | - | - | - | | 0.4825 | 1520 | 0.0002 | - | - | - | - | - | | 0.4857 | 1530 | 0.0053 | - | - | - | - | - | | 0.4889 | 1540 | 0.0042 | - | - | - | - | - | | 0.4921 | 1550 | 0.0005 | - | - | - | - | - | | 0.4952 | 1560 | 0.0026 | - | - | - | - | - | | 0.4984 | 1570 | 0.0081 | - | - | - | - | - | | 0.5016 | 1580 | 0.0094 | - | - | - | - | - | | 0.5048 | 1590 | 0.0003 | - | - | - | - | - | | 0.5079 | 1600 | 0.0075 | - | - | - | - | - | | 0.5111 | 1610 | 0.0002 | - | - | - | - | - | | 0.5143 | 1620 | 0.001 | - | - | - | - | - | | 0.5175 | 1630 | 0.0015 | - | - | - | - | - | | 0.5206 | 1640 | 0.0015 | - | - | - | - | - | | 0.5238 | 1650 | 0.3041 | - | - | - | - | - | | 0.5270 | 1660 | 0.0328 | - | - | - | - | - | | 0.5302 | 1670 | 0.0138 | - | - | - | - | - | | 0.5333 | 1680 | 0.0007 | - | - | - | - | - | | 0.5365 | 1690 | 0.0008 | - | - | - | - | - | | 0.5397 | 1700 | 0.0011 | - | - | - | - | - | | 0.5429 | 1710 | 0.0013 | - | - | - | - | - | | 0.5460 | 1720 | 0.0011 | - | - | - | - | - | | 0.5492 | 1730 | 0.2332 | - | - | - | - | - | | 0.5524 | 1740 | 0.0021 | - | - | - | - | - | | 0.5556 | 1750 | 0.8243 | - | - | - | - | - | | 0.5587 | 1760 | 0.0199 | - | - | - | - | - | | 0.5619 | 1770 | 0.0118 | - | - | - | - | - | | 0.5651 | 1780 | 0.0425 | - | - | - | - | - | | 0.5683 | 1790 | 0.003 | - | - | - | - | - | | 0.5714 | 1800 | 0.0024 | - | - | - | - | - | | 0.5746 | 1810 | 0.0002 | - | - | - | - | - | | 0.5778 | 1820 | 0.0459 | - | - | - | - | - | | 0.5810 | 1830 | 0.0018 | - | - | - | - | - | | 0.5841 | 1840 | 0.0009 | - | - | - | - | - | | 0.5873 | 1850 | 0.0007 | - | - | - | - | - | | 0.5905 | 1860 | 0.0112 | - | - | - | - | - | | 0.5937 | 1870 | 0.0302 | - | - | - | - | - | | 0.5968 | 1880 | 0.0101 | - | - | - | - | - | | 0.6 | 1890 | 0.0098 | - | - | - | - | - | | 0.6032 | 1900 | 0.0332 | - | - | - | - | - | | 0.6063 | 1910 | 0.0017 | - | - | - | - | - | | 0.6095 | 1920 | 0.007 | - | - | - | - | - | | 0.6127 | 1930 | 0.0012 | - | - | - | - | - | | 0.6159 | 1940 | 0.0971 | - | - | - | - | - | | 0.6190 | 1950 | 0.0009 | - | - | - | - | - | | 0.6222 | 1960 | 0.0001 | - | - | - | - | - | | 0.6254 | 1970 | 0.0041 | - | - | - | - | - | | 0.6286 | 1980 | 0.0021 | - | - | - | - | - | | 0.6317 | 1990 | 0.0044 | - | - | - | - | - | | 0.6349 | 2000 | 0.0004 | - | - | - | - | - | | 0.6381 | 2010 | 0.0077 | - | - | - | - | - | | 0.6413 | 2020 | 0.0002 | - | - | - | - | - | | 0.6444 | 2030 | 0.0006 | - | - | - | - | - | | 0.6476 | 2040 | 0.0008 | - | - | - | - | - | | 0.6508 | 2050 | 0.0004 | - | - | - | - | - | | 0.6540 | 2060 | 0.0013 | - | - | - | - | - | | 0.6571 | 2070 | 0.0009 | - | - | - | - | - | | 0.6603 | 2080 | 0.0015 | - | - | - | - | - | | 0.6635 | 2090 | 0.0002 | - | - | - | - | - | | 0.6667 | 2100 | 0.0028 | - | - | - | - | - | | 0.6698 | 2110 | 0.0008 | - | - | - | - | - | | 0.6730 | 2120 | 0.0094 | - | - | - | - | - | | 0.6762 | 2130 | 0.5743 | - | - | - | - | - | | 0.6794 | 2140 | 0.0002 | - | - | - | - | - | | 0.6825 | 2150 | 0.0006 | - | - | - | - | - | | 0.6857 | 2160 | 0.0005 | - | - | - | - | - | | 0.6889 | 2170 | 0.0002 | - | - | - | - | - | | 0.6921 | 2180 | 0.0032 | - | - | - | - | - | | 0.6952 | 2190 | 0.0006 | - | - | - | - | - | | 0.6984 | 2200 | 0.0012 | - | - | - | - | - | | 0.7016 | 2210 | 0.0598 | - | - | - | - | - | | 0.7048 | 2220 | 0.0 | - | - | - | - | - | | 0.7079 | 2230 | 0.0001 | - | - | - | - | - | | 0.7111 | 2240 | 0.0001 | - | - | - | - | - | | 0.7143 | 2250 | 0.0082 | - | - | - | - | - | | 0.7175 | 2260 | 0.0033 | - | - | - | - | - | | 0.7206 | 2270 | 0.0004 | - | - | - | - | - | | 0.7238 | 2280 | 0.0132 | - | - | - | - | - | | 0.7270 | 2290 | 0.0004 | - | - | - | - | - | | 0.7302 | 2300 | 0.0107 | - | - | - | - | - | | 0.7333 | 2310 | 0.0018 | - | - | - | - | - | | 0.7365 | 2320 | 0.0255 | - | - | - | - | - | | 0.7397 | 2330 | 0.0001 | - | - | - | - | - | | 0.7429 | 2340 | 0.0025 | - | - | - | - | - | | 0.7460 | 2350 | 0.3299 | - | - | - | - | - | | 0.7492 | 2360 | 0.0039 | - | - | - | - | - | | 0.7524 | 2370 | 0.0511 | - | - | - | - | - | | 0.7556 | 2380 | 0.0001 | - | - | - | - | - | | 0.7587 | 2390 | 0.0002 | - | - | - | - | - | | 0.7619 | 2400 | 0.0001 | - | - | - | - | - | | 0.7651 | 2410 | 0.0002 | - | - | - | - | - | | 0.7683 | 2420 | 0.0072 | - | - | - | - | - | | 0.7714 | 2430 | 0.0453 | - | - | - | - | - | | 0.7746 | 2440 | 0.0003 | - | - | - | - | - | | 0.7778 | 2450 | 0.0224 | - | - | - | - | - | | 0.7810 | 2460 | 0.0035 | - | - | - | - | - | | 0.7841 | 2470 | 0.001 | - | - | - | - | - | | 0.7873 | 2480 | 0.0003 | - | - | - | - | - | | 0.7905 | 2490 | 0.0001 | - | - | - | - | - | | 0.7937 | 2500 | 0.0002 | - | - | - | - | - | | 0.7968 | 2510 | 0.0489 | - | - | - | - | - | | 0.8 | 2520 | 0.0001 | - | - | - | - | - | | 0.8032 | 2530 | 0.0128 | - | - | - | - | - | | 0.8063 | 2540 | 0.0009 | - | - | - | - | - | | 0.8095 | 2550 | 0.0022 | - | - | - | - | - | | 0.8127 | 2560 | 0.0002 | - | - | - | - | - | | 0.8159 | 2570 | 0.0525 | - | - | - | - | - | | 0.8190 | 2580 | 0.0005 | - | - | - | - | - | | 0.8222 | 2590 | 0.2441 | - | - | - | - | - | | 0.8254 | 2600 | 0.0002 | - | - | - | - | - | | 0.8286 | 2610 | 0.0002 | - | - | - | - | - | | 0.8317 | 2620 | 0.0004 | - | - | - | - | - | | 0.8349 | 2630 | 0.0007 | - | - | - | - | - | | 0.8381 | 2640 | 0.01 | - | - | - | - | - | | 0.8413 | 2650 | 1.0383 | - | - | - | - | - | | 0.8444 | 2660 | 0.2035 | - | - | - | - | - | | 0.8476 | 2670 | 0.0246 | - | - | - | - | - | | 0.8508 | 2680 | 0.056 | - | - | - | - | - | | 0.8540 | 2690 | 0.0 | - | - | - | - | - | | 0.8571 | 2700 | 0.0 | - | - | - | - | - | | 0.8603 | 2710 | 0.378 | - | - | - | - | - | | 0.8635 | 2720 | 0.0076 | - | - | - | - | - | | 0.8667 | 2730 | 0.0108 | - | - | - | - | - | | 0.8698 | 2740 | 0.0066 | - | - | - | - | - | | 0.8730 | 2750 | 0.0146 | - | - | - | - | - | | 0.8762 | 2760 | 0.0002 | - | - | - | - | - | | 0.8794 | 2770 | 0.0005 | - | - | - | - | - | | 0.8825 | 2780 | 0.0001 | - | - | - | - | - | | 0.8857 | 2790 | 0.0001 | - | - | - | - | - | | 0.8889 | 2800 | 0.006 | - | - | - | - | - | | 0.8921 | 2810 | 0.0021 | - | - | - | - | - | | 0.8952 | 2820 | 0.0314 | - | - | - | - | - | | 0.8984 | 2830 | 0.0008 | - | - | - | - | - | | 0.9016 | 2840 | 0.0004 | - | - | - | - | - | | 0.9048 | 2850 | 0.0024 | - | - | - | - | - | | 0.9079 | 2860 | 0.0004 | - | - | - | - | - | | 0.9111 | 2870 | 0.0004 | - | - | - | - | - | | 0.9143 | 2880 | 0.0001 | - | - | - | - | - | | 0.9175 | 2890 | 0.0017 | - | - | - | - | - | | 0.9206 | 2900 | 0.0004 | - | - | - | - | - | | 0.9238 | 2910 | 0.0016 | - | - | - | - | - | | 0.9270 | 2920 | 0.0004 | - | - | - | - | - | | 0.9302 | 2930 | 0.0029 | - | - | - | - | - | | 0.9333 | 2940 | 0.0011 | - | - | - | - | - | | 0.9365 | 2950 | 0.0015 | - | - | - | - | - | | 0.9397 | 2960 | 0.0128 | - | - | - | - | - | | 0.9429 | 2970 | 0.311 | - | - | - | - | - | | 0.9460 | 2980 | 0.0244 | - | - | - | - | - | | 0.9492 | 2990 | 0.0278 | - | - | - | - | - | | 0.9524 | 3000 | 0.0016 | - | - | - | - | - | | 0.9556 | 3010 | 0.0005 | - | - | - | - | - | | 0.9587 | 3020 | 0.0008 | - | - | - | - | - | | 0.9619 | 3030 | 0.0005 | - | - | - | - | - | | 0.9651 | 3040 | 0.0 | - | - | - | - | - | | 0.9683 | 3050 | 0.0103 | - | - | - | - | - | | 0.9714 | 3060 | 0.0019 | - | - | - | - | - | | 0.9746 | 3070 | 0.0011 | - | - | - | - | - | | 0.9778 | 3080 | 0.0005 | - | - | - | - | - | | 0.9810 | 3090 | 0.0377 | - | - | - | - | - | | 0.9841 | 3100 | 0.0006 | - | - | - | - | - | | 0.9873 | 3110 | 0.7692 | - | - | - | - | - | | 0.9905 | 3120 | 0.0005 | - | - | - | - | - | | 0.9937 | 3130 | 0.0006 | - | - | - | - | - | | 0.9968 | 3140 | 0.0062 | - | - | - | - | - | | 1.0 | 3150 | 0.0161 | 0.7705 | 0.7679 | 0.7597 | 0.7425 | 0.7233 | | 1.0032 | 3160 | 0.0032 | - | - | - | - | - | | 1.0063 | 3170 | 0.0 | - | - | - | - | - | | 1.0095 | 3180 | 0.0016 | - | - | - | - | - | | 1.0127 | 3190 | 0.0001 | - | - | - | - | - | | 1.0159 | 3200 | 0.0221 | - | - | - | - | - | | 1.0190 | 3210 | 0.0004 | - | - | - | - | - | | 1.0222 | 3220 | 0.0008 | - | - | - | - | - | | 1.0254 | 3230 | 0.0001 | - | - | - | - | - | | 1.0286 | 3240 | 0.0004 | - | - | - | - | - | | 1.0317 | 3250 | 0.0004 | - | - | - | - | - | | 1.0349 | 3260 | 0.0004 | - | - | - | - | - | | 1.0381 | 3270 | 0.0 | - | - | - | - | - | | 1.0413 | 3280 | 0.0001 | - | - | - | - | - | | 1.0444 | 3290 | 0.2183 | - | - | - | - | - | | 1.0476 | 3300 | 0.045 | - | - | - | - | - | | 1.0508 | 3310 | 0.0002 | - | - | - | - | - | | 1.0540 | 3320 | 0.0001 | - | - | - | - | - | | 1.0571 | 3330 | 0.0167 | - | - | - | - | - | | 1.0603 | 3340 | 0.0043 | - | - | - | - | - | | 1.0635 | 3350 | 0.0012 | - | - | - | - | - | | 1.0667 | 3360 | 0.0006 | - | - | - | - | - | | 1.0698 | 3370 | 0.0029 | - | - | - | - | - | | 1.0730 | 3380 | 0.0004 | - | - | - | - | - | | 1.0762 | 3390 | 0.0024 | - | - | - | - | - | | 1.0794 | 3400 | 0.0019 | - | - | - | - | - | | 1.0825 | 3410 | 0.2129 | - | - | - | - | - | | 1.0857 | 3420 | 0.06 | - | - | - | - | - | | 1.0889 | 3430 | 0.0001 | - | - | - | - | - | | 1.0921 | 3440 | 0.0008 | - | - | - | - | - | | 1.0952 | 3450 | 0.0 | - | - | - | - | - | | 1.0984 | 3460 | 0.0006 | - | - | - | - | - | | 1.1016 | 3470 | 0.0001 | - | - | - | - | - | | 1.1048 | 3480 | 0.0009 | - | - | - | - | - | | 1.1079 | 3490 | 0.0016 | - | - | - | - | - | | 1.1111 | 3500 | 0.0002 | - | - | - | - | - | | 1.1143 | 3510 | 0.0001 | - | - | - | - | - | | 1.1175 | 3520 | 0.0198 | - | - | - | - | - | | 1.1206 | 3530 | 0.0018 | - | - | - | - | - | | 1.1238 | 3540 | 0.0 | - | - | - | - | - | | 1.1270 | 3550 | 0.0001 | - | - | - | - | - | | 1.1302 | 3560 | 0.0003 | - | - | - | - | - | | 1.1333 | 3570 | 0.0021 | - | - | - | - | - | | 1.1365 | 3580 | 0.0 | - | - | - | - | - | | 1.1397 | 3590 | 0.0007 | - | - | - | - | - | | 1.1429 | 3600 | 0.0 | - | - | - | - | - | | 1.1460 | 3610 | 0.0016 | - | - | - | - | - | | 1.1492 | 3620 | 0.0005 | - | - | - | - | - | | 1.1524 | 3630 | 0.001 | - | - | - | - | - | | 1.1556 | 3640 | 0.0042 | - | - | - | - | - | | 1.1587 | 3650 | 0.0008 | - | - | - | - | - | | 1.1619 | 3660 | 0.0002 | - | - | - | - | - | | 1.1651 | 3670 | 0.0004 | - | - | - | - | - | | 1.1683 | 3680 | 0.1335 | - | - | - | - | - | | 1.1714 | 3690 | 0.0014 | - | - | - | - | - | | 1.1746 | 3700 | 0.0009 | - | - | - | - | - | | 1.1778 | 3710 | 0.0017 | - | - | - | - | - | | 1.1810 | 3720 | 0.0088 | - | - | - | - | - | | 1.1841 | 3730 | 0.0002 | - | - | - | - | - | | 1.1873 | 3740 | 0.0122 | - | - | - | - | - | | 1.1905 | 3750 | 0.0001 | - | - | - | - | - | | 1.1937 | 3760 | 0.0 | - | - | - | - | - | | 1.1968 | 3770 | 0.0017 | - | - | - | - | - | | 1.2 | 3780 | 0.0031 | - | - | - | - | - | | 1.2032 | 3790 | 0.0026 | - | - | - | - | - | | 1.2063 | 3800 | 0.0001 | - | - | - | - | - | | 1.2095 | 3810 | 0.026 | - | - | - | - | - | | 1.2127 | 3820 | 0.0002 | - | - | - | - | - | | 1.2159 | 3830 | 0.0053 | - | - | - | - | - | | 1.2190 | 3840 | 0.0004 | - | - | - | - | - | | 1.2222 | 3850 | 0.2406 | - | - | - | - | - | | 1.2254 | 3860 | 0.0069 | - | - | - | - | - | | 1.2286 | 3870 | 0.0098 | - | - | - | - | - | | 1.2317 | 3880 | 0.0005 | - | - | - | - | - | | 1.2349 | 3890 | 0.0056 | - | - | - | - | - | | 1.2381 | 3900 | 0.0 | - | - | - | - | - | | 1.2413 | 3910 | 0.0001 | - | - | - | - | - | | 1.2444 | 3920 | 0.0003 | - | - | - | - | - | | 1.2476 | 3930 | 0.0007 | - | - | - | - | - | | 1.2508 | 3940 | 0.0029 | - | - | - | - | - | | 1.2540 | 3950 | 0.0001 | - | - | - | - | - | | 1.2571 | 3960 | 0.0022 | - | - | - | - | - | | 1.2603 | 3970 | 0.0021 | - | - | - | - | - | | 1.2635 | 3980 | 0.0001 | - | - | - | - | - | | 1.2667 | 3990 | 0.0006 | - | - | - | - | - | | 1.2698 | 4000 | 0.0 | - | - | - | - | - | | 1.2730 | 4010 | 0.0 | - | - | - | - | - | | 1.2762 | 4020 | 0.0003 | - | - | - | - | - | | 1.2794 | 4030 | 0.525 | - | - | - | - | - | | 1.2825 | 4040 | 0.0001 | - | - | - | - | - | | 1.2857 | 4050 | 0.0001 | - | - | - | - | - | | 1.2889 | 4060 | 0.0003 | - | - | - | - | - | | 1.2921 | 4070 | 0.0001 | - | - | - | - | - | | 1.2952 | 4080 | 0.0002 | - | - | - | - | - | | 1.2984 | 4090 | 0.0001 | - | - | - | - | - | | 1.3016 | 4100 | 0.0006 | - | - | - | - | - | | 1.3048 | 4110 | 0.0003 | - | - | - | - | - | | 1.3079 | 4120 | 0.0162 | - | - | - | - | - | | 1.3111 | 4130 | 0.0002 | - | - | - | - | - | | 1.3143 | 4140 | 0.008 | - | - | - | - | - | | 1.3175 | 4150 | 0.6283 | - | - | - | - | - | | 1.3206 | 4160 | 0.0 | - | - | - | - | - | | 1.3238 | 4170 | 0.0004 | - | - | - | - | - | | 1.3270 | 4180 | 0.0002 | - | - | - | - | - | | 1.3302 | 4190 | 0.0 | - | - | - | - | - | | 1.3333 | 4200 | 0.0002 | - | - | - | - | - | | 1.3365 | 4210 | 0.0002 | - | - | - | - | - | | 1.3397 | 4220 | 0.0001 | - | - | - | - | - | | 1.3429 | 4230 | 0.0023 | - | - | - | - | - | | 1.3460 | 4240 | 0.0002 | - | - | - | - | - | | 1.3492 | 4250 | 0.0 | - | - | - | - | - | | 1.3524 | 4260 | 0.0 | - | - | - | - | - | | 1.3556 | 4270 | 0.0 | - | - | - | - | - | | 1.3587 | 4280 | 0.002 | - | - | - | - | - | | 1.3619 | 4290 | 0.0019 | - | - | - | - | - | | 1.3651 | 4300 | 0.0012 | - | - | - | - | - | | 1.3683 | 4310 | 0.0061 | - | - | - | - | - | | 1.3714 | 4320 | 0.0677 | - | - | - | - | - | | 1.3746 | 4330 | 0.0 | - | - | - | - | - | | 1.3778 | 4340 | 0.0 | - | - | - | - | - | | 1.3810 | 4350 | 0.0784 | - | - | - | - | - | | 1.3841 | 4360 | 0.0001 | - | - | - | - | - | | 1.3873 | 4370 | 0.0097 | - | - | - | - | - | | 1.3905 | 4380 | 0.0004 | - | - | - | - | - | | 1.3937 | 4390 | 0.0001 | - | - | - | - | - | | 1.3968 | 4400 | 0.0065 | - | - | - | - | - | | 1.4 | 4410 | 0.0002 | - | - | - | - | - | | 1.4032 | 4420 | 0.0128 | - | - | - | - | - | | 1.4063 | 4430 | 0.0001 | - | - | - | - | - | | 1.4095 | 4440 | 0.0006 | - | - | - | - | - | | 1.4127 | 4450 | 0.0002 | - | - | - | - | - | | 1.4159 | 4460 | 0.0008 | - | - | - | - | - | | 1.4190 | 4470 | 0.0001 | - | - | - | - | - | | 1.4222 | 4480 | 0.0001 | - | - | - | - | - | | 1.4254 | 4490 | 0.0001 | - | - | - | - | - | | 1.4286 | 4500 | 0.0511 | - | - | - | - | - | | 1.4317 | 4510 | 0.0001 | - | - | - | - | - | | 1.4349 | 4520 | 0.0001 | - | - | - | - | - | | 1.4381 | 4530 | 0.0044 | - | - | - | - | - | | 1.4413 | 4540 | 0.0025 | - | - | - | - | - | | 1.4444 | 4550 | 0.0001 | - | - | - | - | - | | 1.4476 | 4560 | 0.0001 | - | - | - | - | - | | 1.4508 | 4570 | 0.015 | - | - | - | - | - | | 1.4540 | 4580 | 0.0002 | - | - | - | - | - | | 1.4571 | 4590 | 0.0001 | - | - | - | - | - | | 1.4603 | 4600 | 0.0308 | - | - | - | - | - | | 1.4635 | 4610 | 0.0005 | - | - | - | - | - | | 1.4667 | 4620 | 0.0101 | - | - | - | - | - | | 1.4698 | 4630 | 0.0012 | - | - | - | - | - | | 1.4730 | 4640 | 0.0023 | - | - | - | - | - | | 1.4762 | 4650 | 0.0003 | - | - | - | - | - | | 1.4794 | 4660 | 0.0313 | - | - | - | - | - | | 1.4825 | 4670 | 0.0048 | - | - | - | - | - | | 1.4857 | 4680 | 0.0013 | - | - | - | - | - | | 1.4889 | 4690 | 0.0008 | - | - | - | - | - | | 1.4921 | 4700 | 0.0001 | - | - | - | - | - | | 1.4952 | 4710 | 0.0007 | - | - | - | - | - | | 1.4984 | 4720 | 0.0 | - | - | - | - | - | | 1.5016 | 4730 | 0.0002 | - | - | - | - | - | | 1.5048 | 4740 | 0.0019 | - | - | - | - | - | | 1.5079 | 4750 | 0.0491 | - | - | - | - | - | | 1.5111 | 4760 | 0.0272 | - | - | - | - | - | | 1.5143 | 4770 | 0.0003 | - | - | - | - | - | | 1.5175 | 4780 | 0.0003 | - | - | - | - | - | | 1.5206 | 4790 | 0.0 | - | - | - | - | - | | 1.5238 | 4800 | 0.0001 | - | - | - | - | - | | 1.5270 | 4810 | 0.0006 | - | - | - | - | - | | 1.5302 | 4820 | 0.0001 | - | - | - | - | - | | 1.5333 | 4830 | 0.0011 | - | - | - | - | - | | 1.5365 | 4840 | 0.0001 | - | - | - | - | - | | 1.5397 | 4850 | 0.0004 | - | - | - | - | - | | 1.5429 | 4860 | 0.002 | - | - | - | - | - | | 1.5460 | 4870 | 0.8482 | - | - | - | - | - | | 1.5492 | 4880 | 0.0001 | - | - | - | - | - | | 1.5524 | 4890 | 0.0001 | - | - | - | - | - | | 1.5556 | 4900 | 0.0004 | - | - | - | - | - | | 1.5587 | 4910 | 0.0084 | - | - | - | - | - | | 1.5619 | 4920 | 0.0006 | - | - | - | - | - | | 1.5651 | 4930 | 0.3809 | - | - | - | - | - | | 1.5683 | 4940 | 0.0007 | - | - | - | - | - | | 1.5714 | 4950 | 0.0 | - | - | - | - | - | | 1.5746 | 4960 | 0.002 | - | - | - | - | - | | 1.5778 | 4970 | 0.0021 | - | - | - | - | - | | 1.5810 | 4980 | 0.3699 | - | - | - | - | - | | 1.5841 | 4990 | 0.0022 | - | - | - | - | - | | 1.5873 | 5000 | 0.0022 | - | - | - | - | - | | 1.5905 | 5010 | 0.0043 | - | - | - | - | - | | 1.5937 | 5020 | 0.0001 | - | - | - | - | - | | 1.5968 | 5030 | 0.0001 | - | - | - | - | - | | 1.6 | 5040 | 0.0016 | - | - | - | - | - | | 1.6032 | 5050 | 0.0004 | - | - | - | - | - | | 1.6063 | 5060 | 0.0003 | - | - | - | - | - | | 1.6095 | 5070 | 0.0017 | - | - | - | - | - | | 1.6127 | 5080 | 0.0016 | - | - | - | - | - | | 1.6159 | 5090 | 0.0001 | - | - | - | - | - | | 1.6190 | 5100 | 0.0051 | - | - | - | - | - | | 1.6222 | 5110 | 0.0 | - | - | - | - | - | | 1.6254 | 5120 | 0.0214 | - | - | - | - | - | | 1.6286 | 5130 | 0.0031 | - | - | - | - | - | | 1.6317 | 5140 | 0.0011 | - | - | - | - | - | | 1.6349 | 5150 | 0.0 | - | - | - | - | - | | 1.6381 | 5160 | 0.0001 | - | - | - | - | - | | 1.6413 | 5170 | 0.0001 | - | - | - | - | - | | 1.6444 | 5180 | 0.0015 | - | - | - | - | - | | 1.6476 | 5190 | 0.0002 | - | - | - | - | - | | 1.6508 | 5200 | 0.0001 | - | - | - | - | - | | 1.6540 | 5210 | 0.0023 | - | - | - | - | - | | 1.6571 | 5220 | 0.2279 | - | - | - | - | - | | 1.6603 | 5230 | 0.0787 | - | - | - | - | - | | 1.6635 | 5240 | 0.0002 | - | - | - | - | - | | 1.6667 | 5250 | 0.0015 | - | - | - | - | - | | 1.6698 | 5260 | 0.0 | - | - | - | - | - | | 1.6730 | 5270 | 0.0004 | - | - | - | - | - | | 1.6762 | 5280 | 0.0011 | - | - | - | - | - | | 1.6794 | 5290 | 0.0003 | - | - | - | - | - | | 1.6825 | 5300 | 0.0017 | - | - | - | - | - | | 1.6857 | 5310 | 0.0002 | - | - | - | - | - | | 1.6889 | 5320 | 0.0 | - | - | - | - | - | | 1.6921 | 5330 | 0.001 | - | - | - | - | - | | 1.6952 | 5340 | 0.0003 | - | - | - | - | - | | 1.6984 | 5350 | 0.0004 | - | - | - | - | - | | 1.7016 | 5360 | 0.0294 | - | - | - | - | - | | 1.7048 | 5370 | 0.0005 | - | - | - | - | - | | 1.7079 | 5380 | 0.0123 | - | - | - | - | - | | 1.7111 | 5390 | 0.0053 | - | - | - | - | - | | 1.7143 | 5400 | 0.2908 | - | - | - | - | - | | 1.7175 | 5410 | 0.0001 | - | - | - | - | - | | 1.7206 | 5420 | 0.0005 | - | - | - | - | - | | 1.7238 | 5430 | 0.0004 | - | - | - | - | - | | 1.7270 | 5440 | 0.0384 | - | - | - | - | - | | 1.7302 | 5450 | 0.2805 | - | - | - | - | - | | 1.7333 | 5460 | 0.0004 | - | - | - | - | - | | 1.7365 | 5470 | 0.0013 | - | - | - | - | - | | 1.7397 | 5480 | 0.0002 | - | - | - | - | - | | 1.7429 | 5490 | 1.5794 | - | - | - | - | - | | 1.7460 | 5500 | 0.0125 | - | - | - | - | - | | 1.7492 | 5510 | 0.0029 | - | - | - | - | - | | 1.7524 | 5520 | 0.0 | - | - | - | - | - | | 1.7556 | 5530 | 0.0001 | - | - | - | - | - | | 1.7587 | 5540 | 0.0025 | - | - | - | - | - | | 1.7619 | 5550 | 0.0446 | - | - | - | - | - | | 1.7651 | 5560 | 0.0023 | - | - | - | - | - | | 1.7683 | 5570 | 0.0001 | - | - | - | - | - | | 1.7714 | 5580 | 0.0004 | - | - | - | - | - | | 1.7746 | 5590 | 0.0003 | - | - | - | - | - | | 1.7778 | 5600 | 0.0002 | - | - | - | - | - | | 1.7810 | 5610 | 0.0002 | - | - | - | - | - | | 1.7841 | 5620 | 0.1482 | - | - | - | - | - | | 1.7873 | 5630 | 0.0632 | - | - | - | - | - | | 1.7905 | 5640 | 0.0009 | - | - | - | - | - | | 1.7937 | 5650 | 0.0027 | - | - | - | - | - | | 1.7968 | 5660 | 0.0011 | - | - | - | - | - | | 1.8 | 5670 | 0.0001 | - | - | - | - | - | | 1.8032 | 5680 | 0.0 | - | - | - | - | - | | 1.8063 | 5690 | 0.0029 | - | - | - | - | - | | 1.8095 | 5700 | 0.0004 | - | - | - | - | - | | 1.8127 | 5710 | 0.0019 | - | - | - | - | - | | 1.8159 | 5720 | 0.1265 | - | - | - | - | - | | 1.8190 | 5730 | 0.0004 | - | - | - | - | - | | 1.8222 | 5740 | 0.0012 | - | - | - | - | - | | 1.8254 | 5750 | 0.0001 | - | - | - | - | - | | 1.8286 | 5760 | 0.0047 | - | - | - | - | - | | 1.8317 | 5770 | 0.0227 | - | - | - | - | - | | 1.8349 | 5780 | 0.0003 | - | - | - | - | - | | 1.8381 | 5790 | 0.0001 | - | - | - | - | - | | 1.8413 | 5800 | 0.0044 | - | - | - | - | - | | 1.8444 | 5810 | 0.0001 | - | - | - | - | - | | 1.8476 | 5820 | 0.0004 | - | - | - | - | - | | 1.8508 | 5830 | 0.0005 | - | - | - | - | - | | 1.8540 | 5840 | 0.0009 | - | - | - | - | - | | 1.8571 | 5850 | 0.0027 | - | - | - | - | - | | 1.8603 | 5860 | 0.0003 | - | - | - | - | - | | 1.8635 | 5870 | 0.0 | - | - | - | - | - | | 1.8667 | 5880 | 0.0001 | - | - | - | - | - | | 1.8698 | 5890 | 0.0002 | - | - | - | - | - | | 1.8730 | 5900 | 0.0 | - | - | - | - | - | | 1.8762 | 5910 | 0.0002 | - | - | - | - | - | | 1.8794 | 5920 | 0.001 | - | - | - | - | - | | 1.8825 | 5930 | 0.0001 | - | - | - | - | - | | 1.8857 | 5940 | 0.0001 | - | - | - | - | - | | 1.8889 | 5950 | 0.0049 | - | - | - | - | - | | 1.8921 | 5960 | 0.0 | - | - | - | - | - | | 1.8952 | 5970 | 0.0023 | - | - | - | - | - | | 1.8984 | 5980 | 0.0001 | - | - | - | - | - | | 1.9016 | 5990 | 0.0002 | - | - | - | - | - | | 1.9048 | 6000 | 0.0371 | - | - | - | - | - | | 1.9079 | 6010 | 0.0 | - | - | - | - | - | | 1.9111 | 6020 | 0.0001 | - | - | - | - | - | | 1.9143 | 6030 | 0.0116 | - | - | - | - | - | | 1.9175 | 6040 | 0.0 | - | - | - | - | - | | 1.9206 | 6050 | 0.0 | - | - | - | - | - | | 1.9238 | 6060 | 0.0 | - | - | - | - | - | | 1.9270 | 6070 | 0.0001 | - | - | - | - | - | | 1.9302 | 6080 | 0.0001 | - | - | - | - | - | | 1.9333 | 6090 | 0.0002 | - | - | - | - | - | | 1.9365 | 6100 | 0.4081 | - | - | - | - | - | | 1.9397 | 6110 | 0.0309 | - | - | - | - | - | | 1.9429 | 6120 | 0.0009 | - | - | - | - | - | | 1.9460 | 6130 | 0.0018 | - | - | - | - | - | | 1.9492 | 6140 | 0.0005 | - | - | - | - | - | | 1.9524 | 6150 | 0.0058 | - | - | - | - | - | | 1.9556 | 6160 | 0.0 | - | - | - | - | - | | 1.9587 | 6170 | 0.0215 | - | - | - | - | - | | 1.9619 | 6180 | 0.0007 | - | - | - | - | - | | 1.9651 | 6190 | 0.0072 | - | - | - | - | - | | 1.9683 | 6200 | 0.0002 | - | - | - | - | - | | 1.9714 | 6210 | 0.0001 | - | - | - | - | - | | 1.9746 | 6220 | 0.0002 | - | - | - | - | - | | 1.9778 | 6230 | 0.0001 | - | - | - | - | - | | 1.9810 | 6240 | 0.0005 | - | - | - | - | - | | 1.9841 | 6250 | 0.0011 | - | - | - | - | - | | 1.9873 | 6260 | 0.0027 | - | - | - | - | - | | 1.9905 | 6270 | 0.0016 | - | - | - | - | - | | 1.9937 | 6280 | 0.0364 | - | - | - | - | - | | 1.9968 | 6290 | 0.0016 | - | - | - | - | - | | 2.0 | 6300 | 0.0001 | 0.7724 | 0.7705 | 0.7673 | 0.7579 | 0.7396 | | 2.0032 | 6310 | 0.0 | - | - | - | - | - | | 2.0063 | 6320 | 0.0391 | - | - | - | - | - | | 2.0095 | 6330 | 0.0009 | - | - | - | - | - | | 2.0127 | 6340 | 0.0045 | - | - | - | - | - | | 2.0159 | 6350 | 0.0002 | - | - | - | - | - | | 2.0190 | 6360 | 0.0224 | - | - | - | - | - | | 2.0222 | 6370 | 0.007 | - | - | - | - | - | | 2.0254 | 6380 | 0.0011 | - | - | - | - | - | | 2.0286 | 6390 | 0.0 | - | - | - | - | - | | 2.0317 | 6400 | 0.001 | - | - | - | - | - | | 2.0349 | 6410 | 0.0004 | - | - | - | - | - | | 2.0381 | 6420 | 0.0 | - | - | - | - | - | | 2.0413 | 6430 | 0.1194 | - | - | - | - | - | | 2.0444 | 6440 | 0.0023 | - | - | - | - | - | | 2.0476 | 6450 | 0.0004 | - | - | - | - | - | | 2.0508 | 6460 | 0.0 | - | - | - | - | - | | 2.0540 | 6470 | 0.0007 | - | - | - | - | - | | 2.0571 | 6480 | 0.0001 | - | - | - | - | - | | 2.0603 | 6490 | 0.0 | - | - | - | - | - | | 2.0635 | 6500 | 0.0063 | - | - | - | - | - | | 2.0667 | 6510 | 0.0 | - | - | - | - | - | | 2.0698 | 6520 | 0.0047 | - | - | - | - | - | | 2.0730 | 6530 | 0.0001 | - | - | - | - | - | | 2.0762 | 6540 | 0.0 | - | - | - | - | - | | 2.0794 | 6550 | 0.0001 | - | - | - | - | - | | 2.0825 | 6560 | 0.0 | - | - | - | - | - | | 2.0857 | 6570 | 0.0 | - | - | - | - | - | | 2.0889 | 6580 | 0.0078 | - | - | - | - | - | | 2.0921 | 6590 | 0.0016 | - | - | - | - | - | | 2.0952 | 6600 | 0.0014 | - | - | - | - | - | | 2.0984 | 6610 | 0.0001 | - | - | - | - | - | | 2.1016 | 6620 | 0.0001 | - | - | - | - | - | | 2.1048 | 6630 | 0.0001 | - | - | - | - | - | | 2.1079 | 6640 | 0.0047 | - | - | - | - | - | | 2.1111 | 6650 | 0.0009 | - | - | - | - | - | | 2.1143 | 6660 | 0.0001 | - | - | - | - | - | | 2.1175 | 6670 | 0.0003 | - | - | - | - | - | | 2.1206 | 6680 | 0.0 | - | - | - | - | - | | 2.1238 | 6690 | 0.0001 | - | - | - | - | - | | 2.1270 | 6700 | 0.0 | - | - | - | - | - | | 2.1302 | 6710 | 0.2378 | - | - | - | - | - | | 2.1333 | 6720 | 0.0001 | - | - | - | - | - | | 2.1365 | 6730 | 0.0 | - | - | - | - | - | | 2.1397 | 6740 | 0.0011 | - | - | - | - | - | | 2.1429 | 6750 | 0.0012 | - | - | - | - | - | | 2.1460 | 6760 | 0.0001 | - | - | - | - | - | | 2.1492 | 6770 | 0.0005 | - | - | - | - | - | | 2.1524 | 6780 | 0.0 | - | - | - | - | - | | 2.1556 | 6790 | 0.0318 | - | - | - | - | - | | 2.1587 | 6800 | 0.0002 | - | - | - | - | - | | 2.1619 | 6810 | 0.0004 | - | - | - | - | - | | 2.1651 | 6820 | 0.0004 | - | - | - | - | - | | 2.1683 | 6830 | 0.005 | - | - | - | - | - | | 2.1714 | 6840 | 0.0003 | - | - | - | - | - | | 2.1746 | 6850 | 0.0002 | - | - | - | - | - | | 2.1778 | 6860 | 0.0008 | - | - | - | - | - | | 2.1810 | 6870 | 0.0002 | - | - | - | - | - | | 2.1841 | 6880 | 0.0003 | - | - | - | - | - | | 2.1873 | 6890 | 0.0 | - | - | - | - | - | | 2.1905 | 6900 | 0.0001 | - | - | - | - | - | | 2.1937 | 6910 | 0.0 | - | - | - | - | - | | 2.1968 | 6920 | 0.001 | - | - | - | - | - | | 2.2 | 6930 | 0.1066 | - | - | - | - | - | | 2.2032 | 6940 | 0.002 | - | - | - | - | - | | 2.2063 | 6950 | 0.0006 | - | - | - | - | - | | 2.2095 | 6960 | 0.0006 | - | - | - | - | - | | 2.2127 | 6970 | 0.0 | - | - | - | - | - | | 2.2159 | 6980 | 0.0005 | - | - | - | - | - | | 2.2190 | 6990 | 0.0006 | - | - | - | - | - | | 2.2222 | 7000 | 0.0002 | - | - | - | - | - | | 2.2254 | 7010 | 0.0001 | - | - | - | - | - | | 2.2286 | 7020 | 0.0357 | - | - | - | - | - | | 2.2317 | 7030 | 0.0014 | - | - | - | - | - | | 2.2349 | 7040 | 0.0007 | - | - | - | - | - | | 2.2381 | 7050 | 0.0004 | - | - | - | - | - | | 2.2413 | 7060 | 0.0003 | - | - | - | - | - | | 2.2444 | 7070 | 0.0018 | - | - | - | - | - | | 2.2476 | 7080 | 0.07 | - | - | - | - | - | | 2.2508 | 7090 | 0.0001 | - | - | - | - | - | | 2.2540 | 7100 | 0.0001 | - | - | - | - | - | | 2.2571 | 7110 | 0.0002 | - | - | - | - | - | | 2.2603 | 7120 | 0.024 | - | - | - | - | - | | 2.2635 | 7130 | 0.0034 | - | - | - | - | - | | 2.2667 | 7140 | 0.0025 | - | - | - | - | - | | 2.2698 | 7150 | 0.0001 | - | - | - | - | - | | 2.2730 | 7160 | 0.0006 | - | - | - | - | - | | 2.2762 | 7170 | 0.0 | - | - | - | - | - | | 2.2794 | 7180 | 0.0015 | - | - | - | - | - | | 2.2825 | 7190 | 0.0024 | - | - | - | - | - | | 2.2857 | 7200 | 0.2618 | - | - | - | - | - | | 2.2889 | 7210 | 0.0006 | - | - | - | - | - | | 2.2921 | 7220 | 0.0001 | - | - | - | - | - | | 2.2952 | 7230 | 0.0008 | - | - | - | - | - | | 2.2984 | 7240 | 0.0001 | - | - | - | - | - | | 2.3016 | 7250 | 0.0 | - | - | - | - | - | | 2.3048 | 7260 | 0.0016 | - | - | - | - | - | | 2.3079 | 7270 | 0.0 | - | - | - | - | - | | 2.3111 | 7280 | 0.0482 | - | - | - | - | - | | 2.3143 | 7290 | 0.0001 | - | - | - | - | - | | 2.3175 | 7300 | 0.0 | - | - | - | - | - | | 2.3206 | 7310 | 0.0 | - | - | - | - | - | | 2.3238 | 7320 | 0.0259 | - | - | - | - | - | | 2.3270 | 7330 | 0.0005 | - | - | - | - | - | | 2.3302 | 7340 | 0.0008 | - | - | - | - | - | | 2.3333 | 7350 | 0.0063 | - | - | - | - | - | | 2.3365 | 7360 | 0.0003 | - | - | - | - | - | | 2.3397 | 7370 | 0.0025 | - | - | - | - | - | | 2.3429 | 7380 | 0.0215 | - | - | - | - | - | | 2.3460 | 7390 | 0.1826 | - | - | - | - | - | | 2.3492 | 7400 | 0.001 | - | - | - | - | - | | 2.3524 | 7410 | 0.0006 | - | - | - | - | - | | 2.3556 | 7420 | 0.0 | - | - | - | - | - | | 2.3587 | 7430 | 0.0 | - | - | - | - | - | | 2.3619 | 7440 | 0.005 | - | - | - | - | - | | 2.3651 | 7450 | 0.004 | - | - | - | - | - | | 2.3683 | 7460 | 0.0 | - | - | - | - | - | | 2.3714 | 7470 | 0.0003 | - | - | - | - | - | | 2.3746 | 7480 | 0.0002 | - | - | - | - | - | | 2.3778 | 7490 | 0.0001 | - | - | - | - | - | | 2.3810 | 7500 | 0.0024 | - | - | - | - | - | | 2.3841 | 7510 | 0.0 | - | - | - | - | - | | 2.3873 | 7520 | 0.0001 | - | - | - | - | - | | 2.3905 | 7530 | 0.0036 | - | - | - | - | - | | 2.3937 | 7540 | 0.0007 | - | - | - | - | - | | 2.3968 | 7550 | 0.0 | - | - | - | - | - | | 2.4 | 7560 | 0.0001 | - | - | - | - | - | | 2.4032 | 7570 | 0.0196 | - | - | - | - | - | | 2.4063 | 7580 | 0.0003 | - | - | - | - | - | | 2.4095 | 7590 | 0.0042 | - | - | - | - | - | | 2.4127 | 7600 | 0.0185 | - | - | - | - | - | | 2.4159 | 7610 | 0.2535 | - | - | - | - | - | | 2.4190 | 7620 | 0.0 | - | - | - | - | - | | 2.4222 | 7630 | 0.1162 | - | - | - | - | - | | 2.4254 | 7640 | 0.0 | - | - | - | - | - | | 2.4286 | 7650 | 0.0006 | - | - | - | - | - | | 2.4317 | 7660 | 0.0003 | - | - | - | - | - | | 2.4349 | 7670 | 0.0004 | - | - | - | - | - | | 2.4381 | 7680 | 0.0 | - | - | - | - | - | | 2.4413 | 7690 | 0.0 | - | - | - | - | - | | 2.4444 | 7700 | 0.0003 | - | - | - | - | - | | 2.4476 | 7710 | 0.0001 | - | - | - | - | - | | 2.4508 | 7720 | 0.0016 | - | - | - | - | - | | 2.4540 | 7730 | 0.0 | - | - | - | - | - | | 2.4571 | 7740 | 0.001 | - | - | - | - | - | | 2.4603 | 7750 | 0.0042 | - | - | - | - | - | | 2.4635 | 7760 | 0.0011 | - | - | - | - | - | | 2.4667 | 7770 | 0.0 | - | - | - | - | - | | 2.4698 | 7780 | 0.0002 | - | - | - | - | - | | 2.4730 | 7790 | 0.0 | - | - | - | - | - | | 2.4762 | 7800 | 0.0 | - | - | - | - | - | | 2.4794 | 7810 | 0.0002 | - | - | - | - | - | | 2.4825 | 7820 | 0.0003 | - | - | - | - | - | | 2.4857 | 7830 | 0.0072 | - | - | - | - | - | | 2.4889 | 7840 | 0.0003 | - | - | - | - | - | | 2.4921 | 7850 | 0.0006 | - | - | - | - | - | | 2.4952 | 7860 | 0.005 | - | - | - | - | - | | 2.4984 | 7870 | 0.0243 | - | - | - | - | - | | 2.5016 | 7880 | 0.0 | - | - | - | - | - | | 2.5048 | 7890 | 0.0 | - | - | - | - | - | | 2.5079 | 7900 | 0.0001 | - | - | - | - | - | | 2.5111 | 7910 | 0.0006 | - | - | - | - | - | | 2.5143 | 7920 | 0.0002 | - | - | - | - | - | | 2.5175 | 7930 | 0.0019 | - | - | - | - | - | | 2.5206 | 7940 | 0.0014 | - | - | - | - | - | | 2.5238 | 7950 | 0.0001 | - | - | - | - | - | | 2.5270 | 7960 | 0.0043 | - | - | - | - | - | | 2.5302 | 7970 | 0.0002 | - | - | - | - | - | | 2.5333 | 7980 | 0.0 | - | - | - | - | - | | 2.5365 | 7990 | 0.0044 | - | - | - | - | - | | 2.5397 | 8000 | 0.001 | - | - | - | - | - | | 2.5429 | 8010 | 0.0155 | - | - | - | - | - | | 2.5460 | 8020 | 0.0011 | - | - | - | - | - | | 2.5492 | 8030 | 0.002 | - | - | - | - | - | | 2.5524 | 8040 | 0.0 | - | - | - | - | - | | 2.5556 | 8050 | 0.0048 | - | - | - | - | - | | 2.5587 | 8060 | 0.0043 | - | - | - | - | - | | 2.5619 | 8070 | 0.0 | - | - | - | - | - | | 2.5651 | 8080 | 0.0001 | - | - | - | - | - | | 2.5683 | 8090 | 0.001 | - | - | - | - | - | | 2.5714 | 8100 | 0.0004 | - | - | - | - | - | | 2.5746 | 8110 | 0.0002 | - | - | - | - | - | | 2.5778 | 8120 | 0.0002 | - | - | - | - | - | | 2.5810 | 8130 | 0.1305 | - | - | - | - | - | | 2.5841 | 8140 | 0.0001 | - | - | - | - | - | | 2.5873 | 8150 | 0.0 | - | - | - | - | - | | 2.5905 | 8160 | 0.0018 | - | - | - | - | - | | 2.5937 | 8170 | 0.002 | - | - | - | - | - | | 2.5968 | 8180 | 0.0001 | - | - | - | - | - | | 2.6 | 8190 | 0.0007 | - | - | - | - | - | | 2.6032 | 8200 | 0.0002 | - | - | - | - | - | | 2.6063 | 8210 | 0.0004 | - | - | - | - | - | | 2.6095 | 8220 | 0.0005 | - | - | - | - | - | | 2.6127 | 8230 | 0.0 | - | - | - | - | - | | 2.6159 | 8240 | 0.0001 | - | - | - | - | - | | 2.6190 | 8250 | 0.0257 | - | - | - | - | - | | 2.6222 | 8260 | 0.0001 | - | - | - | - | - | | 2.6254 | 8270 | 0.0 | - | - | - | - | - | | 2.6286 | 8280 | 0.0001 | - | - | - | - | - | | 2.6317 | 8290 | 0.0001 | - | - | - | - | - | | 2.6349 | 8300 | 0.0009 | - | - | - | - | - | | 2.6381 | 8310 | 0.0013 | - | - | - | - | - | | 2.6413 | 8320 | 0.0001 | - | - | - | - | - | | 2.6444 | 8330 | 0.0 | - | - | - | - | - | | 2.6476 | 8340 | 0.0 | - | - | - | - | - | | 2.6508 | 8350 | 0.0 | - | - | - | - | - | | 2.6540 | 8360 | 0.0003 | - | - | - | - | - | | 2.6571 | 8370 | 0.0001 | - | - | - | - | - | | 2.6603 | 8380 | 0.0013 | - | - | - | - | - | | 2.6635 | 8390 | 0.0001 | - | - | - | - | - | | 2.6667 | 8400 | 0.0 | - | - | - | - | - | | 2.6698 | 8410 | 0.0073 | - | - | - | - | - | | 2.6730 | 8420 | 0.0001 | - | - | - | - | - | | 2.6762 | 8430 | 0.0003 | - | - | - | - | - | | 2.6794 | 8440 | 0.0006 | - | - | - | - | - | | 2.6825 | 8450 | 0.0002 | - | - | - | - | - | | 2.6857 | 8460 | 0.0004 | - | - | - | - | - | | 2.6889 | 8470 | 0.0369 | - | - | - | - | - | | 2.6921 | 8480 | 0.001 | - | - | - | - | - | | 2.6952 | 8490 | 0.0002 | - | - | - | - | - | | 2.6984 | 8500 | 0.0 | - | - | - | - | - | | 2.7016 | 8510 | 0.002 | - | - | - | - | - | | 2.7048 | 8520 | 0.002 | - | - | - | - | - | | 2.7079 | 8530 | 0.0025 | - | - | - | - | - | | 2.7111 | 8540 | 0.0 | - | - | - | - | - | | 2.7143 | 8550 | 0.0014 | - | - | - | - | - | | 2.7175 | 8560 | 0.0 | - | - | - | - | - | | 2.7206 | 8570 | 0.0001 | - | - | - | - | - | | 2.7238 | 8580 | 0.0007 | - | - | - | - | - | | 2.7270 | 8590 | 0.0001 | - | - | - | - | - | | 2.7302 | 8600 | 0.0003 | - | - | - | - | - | | 2.7333 | 8610 | 0.0007 | - | - | - | - | - | | 2.7365 | 8620 | 0.0 | - | - | - | - | - | | 2.7397 | 8630 | 0.0011 | - | - | - | - | - | | 2.7429 | 8640 | 0.0 | - | - | - | - | - | | 2.7460 | 8650 | 0.0002 | - | - | - | - | - | | 2.7492 | 8660 | 0.0115 | - | - | - | - | - | | 2.7524 | 8670 | 0.0003 | - | - | - | - | - | | 2.7556 | 8680 | 0.0 | - | - | - | - | - | | 2.7587 | 8690 | 0.0097 | - | - | - | - | - | | 2.7619 | 8700 | 0.0199 | - | - | - | - | - | | 2.7651 | 8710 | 0.0832 | - | - | - | - | - | | 2.7683 | 8720 | 0.0007 | - | - | - | - | - | | 2.7714 | 8730 | 0.0011 | - | - | - | - | - | | 2.7746 | 8740 | 0.0001 | - | - | - | - | - | | 2.7778 | 8750 | 0.0002 | - | - | - | - | - | | 2.7810 | 8760 | 0.1405 | - | - | - | - | - | | 2.7841 | 8770 | 0.0002 | - | - | - | - | - | | 2.7873 | 8780 | 0.0001 | - | - | - | - | - | | 2.7905 | 8790 | 0.0013 | - | - | - | - | - | | 2.7937 | 8800 | 0.0001 | - | - | - | - | - | | 2.7968 | 8810 | 0.0631 | - | - | - | - | - | | 2.8 | 8820 | 0.0004 | - | - | - | - | - | | 2.8032 | 8830 | 0.0 | - | - | - | - | - | | 2.8063 | 8840 | 0.0 | - | - | - | - | - | | 2.8095 | 8850 | 0.0 | - | - | - | - | - | | 2.8127 | 8860 | 0.0 | - | - | - | - | - | | 2.8159 | 8870 | 0.0012 | - | - | - | - | - | | 2.8190 | 8880 | 0.0 | - | - | - | - | - | | 2.8222 | 8890 | 0.0002 | - | - | - | - | - | | 2.8254 | 8900 | 0.0069 | - | - | - | - | - | | 2.8286 | 8910 | 0.0132 | - | - | - | - | - | | 2.8317 | 8920 | 0.0001 | - | - | - | - | - | | 2.8349 | 8930 | 0.0005 | - | - | - | - | - | | 2.8381 | 8940 | 0.0019 | - | - | - | - | - | | 2.8413 | 8950 | 0.0001 | - | - | - | - | - | | 2.8444 | 8960 | 0.001 | - | - | - | - | - | | 2.8476 | 8970 | 0.0 | - | - | - | - | - | | 2.8508 | 8980 | 0.0 | - | - | - | - | - | | 2.8540 | 8990 | 0.0009 | - | - | - | - | - | | 2.8571 | 9000 | 0.0049 | - | - | - | - | - | | 2.8603 | 9010 | 0.0018 | - | - | - | - | - | | 2.8635 | 9020 | 0.0 | - | - | - | - | - | | 2.8667 | 9030 | 0.0002 | - | - | - | - | - | | 2.8698 | 9040 | 0.0006 | - | - | - | - | - | | 2.8730 | 9050 | 0.0012 | - | - | - | - | - | | 2.8762 | 9060 | 0.1402 | - | - | - | - | - | | 2.8794 | 9070 | 0.0005 | - | - | - | - | - | | 2.8825 | 9080 | 0.0001 | - | - | - | - | - | | 2.8857 | 9090 | 0.0 | - | - | - | - | - | | 2.8889 | 9100 | 0.0001 | - | - | - | - | - | | 2.8921 | 9110 | 0.0035 | - | - | - | - | - | | 2.8952 | 9120 | 0.0001 | - | - | - | - | - | | 2.8984 | 9130 | 0.0141 | - | - | - | - | - | | 2.9016 | 9140 | 0.0456 | - | - | - | - | - | | 2.9048 | 9150 | 0.0001 | - | - | - | - | - | | 2.9079 | 9160 | 0.0 | - | - | - | - | - | | 2.9111 | 9170 | 0.0001 | - | - | - | - | - | | 2.9143 | 9180 | 0.0001 | - | - | - | - | - | | 2.9175 | 9190 | 0.0 | - | - | - | - | - | | 2.9206 | 9200 | 0.0 | - | - | - | - | - | | 2.9238 | 9210 | 0.0007 | - | - | - | - | - | | 2.9270 | 9220 | 0.0002 | - | - | - | - | - | | 2.9302 | 9230 | 0.0 | - | - | - | - | - | | 2.9333 | 9240 | 0.0001 | - | - | - | - | - | | 2.9365 | 9250 | 0.0006 | - | - | - | - | - | | 2.9397 | 9260 | 0.0005 | - | - | - | - | - | | 2.9429 | 9270 | 0.0 | - | - | - | - | - | | 2.9460 | 9280 | 0.0001 | - | - | - | - | - | | 2.9492 | 9290 | 0.0 | - | - | - | - | - | | 2.9524 | 9300 | 0.0002 | - | - | - | - | - | | 2.9556 | 9310 | 0.0 | - | - | - | - | - | | 2.9587 | 9320 | 0.0004 | - | - | - | - | - | | 2.9619 | 9330 | 0.0002 | - | - | - | - | - | | 2.9651 | 9340 | 0.0006 | - | - | - | - | - | | 2.9683 | 9350 | 0.0 | - | - | - | - | - | | 2.9714 | 9360 | 0.0001 | - | - | - | - | - | | 2.9746 | 9370 | 0.0012 | - | - | - | - | - | | 2.9778 | 9380 | 0.009 | - | - | - | - | - | | 2.9810 | 9390 | 0.0 | - | - | - | - | - | | 2.9841 | 9400 | 0.02 | - | - | - | - | - | | 2.9873 | 9410 | 0.0001 | - | - | - | - | - | | 2.9905 | 9420 | 0.0003 | - | - | - | - | - | | 2.9937 | 9430 | 0.0 | - | - | - | - | - | | 2.9968 | 9440 | 0.0006 | - | - | - | - | - | | **3.0** | **9450** | **0.0001** | **0.7783** | **0.7725** | **0.7705** | **0.7601** | **0.7515** | | 3.0032 | 9460 | 0.0 | - | - | - | - | - | | 3.0063 | 9470 | 0.0 | - | - | - | - | - | | 3.0095 | 9480 | 0.0 | - | - | - | - | - | | 3.0127 | 9490 | 0.0 | - | - | - | - | - | | 3.0159 | 9500 | 0.0 | - | - | - | - | - | | 3.0190 | 9510 | 0.0017 | - | - | - | - | - | | 3.0222 | 9520 | 0.0018 | - | - | - | - | - | | 3.0254 | 9530 | 0.0001 | - | - | - | - | - | | 3.0286 | 9540 | 0.0001 | - | - | - | - | - | | 3.0317 | 9550 | 0.0088 | - | - | - | - | - | | 3.0349 | 9560 | 0.0 | - | - | - | - | - | | 3.0381 | 9570 | 0.0 | - | - | - | - | - | | 3.0413 | 9580 | 0.0002 | - | - | - | - | - | | 3.0444 | 9590 | 0.0001 | - | - | - | - | - | | 3.0476 | 9600 | 0.0001 | - | - | - | - | - | | 3.0508 | 9610 | 0.0001 | - | - | - | - | - | | 3.0540 | 9620 | 0.509 | - | - | - | - | - | | 3.0571 | 9630 | 0.0 | - | - | - | - | - | | 3.0603 | 9640 | 0.0 | - | - | - | - | - | | 3.0635 | 9650 | 0.0003 | - | - | - | - | - | | 3.0667 | 9660 | 0.0 | - | - | - | - | - | | 3.0698 | 9670 | 0.0 | - | - | - | - | - | | 3.0730 | 9680 | 0.0 | - | - | - | - | - | | 3.0762 | 9690 | 0.0028 | - | - | - | - | - | | 3.0794 | 9700 | 0.0015 | - | - | - | - | - | | 3.0825 | 9710 | 0.2634 | - | - | - | - | - | | 3.0857 | 9720 | 0.007 | - | - | - | - | - | | 3.0889 | 9730 | 0.0002 | - | - | - | - | - | | 3.0921 | 9740 | 0.0001 | - | - | - | - | - | | 3.0952 | 9750 | 0.0001 | - | - | - | - | - | | 3.0984 | 9760 | 0.0 | - | - | - | - | - | | 3.1016 | 9770 | 0.0001 | - | - | - | - | - | | 3.1048 | 9780 | 0.0065 | - | - | - | - | - | | 3.1079 | 9790 | 0.0001 | - | - | - | - | - | | 3.1111 | 9800 | 0.0 | - | - | - | - | - | | 3.1143 | 9810 | 0.0001 | - | - | - | - | - | | 3.1175 | 9820 | 0.0001 | - | - | - | - | - | | 3.1206 | 9830 | 0.0002 | - | - | - | - | - | | 3.1238 | 9840 | 0.0 | - | - | - | - | - | | 3.1270 | 9850 | 0.0001 | - | - | - | - | - | | 3.1302 | 9860 | 0.0 | - | - | - | - | - | | 3.1333 | 9870 | 0.0008 | - | - | - | - | - | | 3.1365 | 9880 | 0.0002 | - | - | - | - | - | | 3.1397 | 9890 | 0.0 | - | - | - | - | - | | 3.1429 | 9900 | 0.0001 | - | - | - | - | - | | 3.1460 | 9910 | 0.0001 | - | - | - | - | - | | 3.1492 | 9920 | 0.0002 | - | - | - | - | - | | 3.1524 | 9930 | 0.0 | - | - | - | - | - | | 3.1556 | 9940 | 0.0005 | - | - | - | - | - | | 3.1587 | 9950 | 0.0 | - | - | - | - | - | | 3.1619 | 9960 | 0.0001 | - | - | - | - | - | | 3.1651 | 9970 | 0.0 | - | - | - | - | - | | 3.1683 | 9980 | 0.0 | - | - | - | - | - | | 3.1714 | 9990 | 0.0005 | - | - | - | - | - | | 3.1746 | 10000 | 0.0009 | - | - | - | - | - | | 3.1778 | 10010 | 0.0001 | - | - | - | - | - | | 3.1810 | 10020 | 0.0013 | - | - | - | - | - | | 3.1841 | 10030 | 0.0002 | - | - | - | - | - | | 3.1873 | 10040 | 0.0001 | - | - | - | - | - | | 3.1905 | 10050 | 0.0002 | - | - | - | - | - | | 3.1937 | 10060 | 0.0016 | - | - | - | - | - | | 3.1968 | 10070 | 0.0 | - | - | - | - | - | | 3.2 | 10080 | 0.0001 | - | - | - | - | - | | 3.2032 | 10090 | 0.0 | - | - | - | - | - | | 3.2063 | 10100 | 0.0021 | - | - | - | - | - | | 3.2095 | 10110 | 0.0005 | - | - | - | - | - | | 3.2127 | 10120 | 0.0323 | - | - | - | - | - | | 3.2159 | 10130 | 0.0011 | - | - | - | - | - | | 3.2190 | 10140 | 0.0005 | - | - | - | - | - | | 3.2222 | 10150 | 0.0001 | - | - | - | - | - | | 3.2254 | 10160 | 0.0001 | - | - | - | - | - | | 3.2286 | 10170 | 0.0002 | - | - | - | - | - | | 3.2317 | 10180 | 0.0013 | - | - | - | - | - | | 3.2349 | 10190 | 0.0002 | - | - | - | - | - | | 3.2381 | 10200 | 0.0003 | - | - | - | - | - | | 3.2413 | 10210 | 0.0 | - | - | - | - | - | | 3.2444 | 10220 | 0.0004 | - | - | - | - | - | | 3.2476 | 10230 | 0.0001 | - | - | - | - | - | | 3.2508 | 10240 | 0.1051 | - | - | - | - | - | | 3.2540 | 10250 | 0.0003 | - | - | - | - | - | | 3.2571 | 10260 | 0.0 | - | - | - | - | - | | 3.2603 | 10270 | 0.0005 | - | - | - | - | - | | 3.2635 | 10280 | 0.0065 | - | - | - | - | - | | 3.2667 | 10290 | 0.0001 | - | - | - | - | - | | 3.2698 | 10300 | 0.0004 | - | - | - | - | - | | 3.2730 | 10310 | 0.0001 | - | - | - | - | - | | 3.2762 | 10320 | 0.0009 | - | - | - | - | - | | 3.2794 | 10330 | 0.0 | - | - | - | - | - | | 3.2825 | 10340 | 0.0 | - | - | - | - | - | | 3.2857 | 10350 | 0.0 | - | - | - | - | - | | 3.2889 | 10360 | 0.0 | - | - | - | - | - | | 3.2921 | 10370 | 0.0 | - | - | - | - | - | | 3.2952 | 10380 | 0.003 | - | - | - | - | - | | 3.2984 | 10390 | 0.0668 | - | - | - | - | - | | 3.3016 | 10400 | 0.0 | - | - | - | - | - | | 3.3048 | 10410 | 0.0002 | - | - | - | - | - | | 3.3079 | 10420 | 0.0 | - | - | - | - | - | | 3.3111 | 10430 | 0.0 | - | - | - | - | - | | 3.3143 | 10440 | 0.0014 | - | - | - | - | - | | 3.3175 | 10450 | 0.0 | - | - | - | - | - | | 3.3206 | 10460 | 0.0 | - | - | - | - | - | | 3.3238 | 10470 | 0.0 | - | - | - | - | - | | 3.3270 | 10480 | 0.0003 | - | - | - | - | - | | 3.3302 | 10490 | 0.0001 | - | - | - | - | - | | 3.3333 | 10500 | 0.0 | - | - | - | - | - | | 3.3365 | 10510 | 0.0001 | - | - | - | - | - | | 3.3397 | 10520 | 0.0011 | - | - | - | - | - | | 3.3429 | 10530 | 0.0039 | - | - | - | - | - | | 3.3460 | 10540 | 0.0003 | - | - | - | - | - | | 3.3492 | 10550 | 0.0 | - | - | - | - | - | | 3.3524 | 10560 | 0.2692 | - | - | - | - | - | | 3.3556 | 10570 | 0.0007 | - | - | - | - | - | | 3.3587 | 10580 | 0.0001 | - | - | - | - | - | | 3.3619 | 10590 | 0.0008 | - | - | - | - | - | | 3.3651 | 10600 | 0.0002 | - | - | - | - | - | | 3.3683 | 10610 | 0.0 | - | - | - | - | - | | 3.3714 | 10620 | 0.0004 | - | - | - | - | - | | 3.3746 | 10630 | 0.0 | - | - | - | - | - | | 3.3778 | 10640 | 0.0001 | - | - | - | - | - | | 3.3810 | 10650 | 0.0001 | - | - | - | - | - | | 3.3841 | 10660 | 0.0163 | - | - | - | - | - | | 3.3873 | 10670 | 0.0097 | - | - | - | - | - | | 3.3905 | 10680 | 0.0003 | - | - | - | - | - | | 3.3937 | 10690 | 0.0 | - | - | - | - | - | | 3.3968 | 10700 | 0.0003 | - | - | - | - | - | | 3.4 | 10710 | 0.0311 | - | - | - | - | - | | 3.4032 | 10720 | 0.3813 | - | - | - | - | - | | 3.4063 | 10730 | 0.0001 | - | - | - | - | - | | 3.4095 | 10740 | 0.0001 | - | - | - | - | - | | 3.4127 | 10750 | 0.0001 | - | - | - | - | - | | 3.4159 | 10760 | 0.0 | - | - | - | - | - | | 3.4190 | 10770 | 0.0129 | - | - | - | - | - | | 3.4222 | 10780 | 0.0 | - | - | - | - | - | | 3.4254 | 10790 | 0.0 | - | - | - | - | - | | 3.4286 | 10800 | 0.0008 | - | - | - | - | - | | 3.4317 | 10810 | 0.0001 | - | - | - | - | - | | 3.4349 | 10820 | 0.0005 | - | - | - | - | - | | 3.4381 | 10830 | 0.0001 | - | - | - | - | - | | 3.4413 | 10840 | 0.0029 | - | - | - | - | - | | 3.4444 | 10850 | 0.0 | - | - | - | - | - | | 3.4476 | 10860 | 0.002 | - | - | - | - | - | | 3.4508 | 10870 | 0.0016 | - | - | - | - | - | | 3.4540 | 10880 | 0.0015 | - | - | - | - | - | | 3.4571 | 10890 | 0.0 | - | - | - | - | - | | 3.4603 | 10900 | 0.0001 | - | - | - | - | - | | 3.4635 | 10910 | 0.0004 | - | - | - | - | - | | 3.4667 | 10920 | 0.0 | - | - | - | - | - | | 3.4698 | 10930 | 0.0081 | - | - | - | - | - | | 3.4730 | 10940 | 0.0 | - | - | - | - | - | | 3.4762 | 10950 | 0.0001 | - | - | - | - | - | | 3.4794 | 10960 | 0.0 | - | - | - | - | - | | 3.4825 | 10970 | 0.0001 | - | - | - | - | - | | 3.4857 | 10980 | 0.0 | - | - | - | - | - | | 3.4889 | 10990 | 0.0002 | - | - | - | - | - | | 3.4921 | 11000 | 0.0001 | - | - | - | - | - | | 3.4952 | 11010 | 0.0 | - | - | - | - | - | | 3.4984 | 11020 | 0.0003 | - | - | - | - | - | | 3.5016 | 11030 | 0.0015 | - | - | - | - | - | | 3.5048 | 11040 | 0.0766 | - | - | - | - | - | | 3.5079 | 11050 | 0.0001 | - | - | - | - | - | | 3.5111 | 11060 | 0.0001 | - | - | - | - | - | | 3.5143 | 11070 | 0.0001 | - | - | - | - | - | | 3.5175 | 11080 | 0.0 | - | - | - | - | - | | 3.5206 | 11090 | 0.0 | - | - | - | - | - | | 3.5238 | 11100 | 0.0 | - | - | - | - | - | | 3.5270 | 11110 | 0.0001 | - | - | - | - | - | | 3.5302 | 11120 | 0.0621 | - | - | - | - | - | | 3.5333 | 11130 | 0.0065 | - | - | - | - | - | | 3.5365 | 11140 | 0.0001 | - | - | - | - | - | | 3.5397 | 11150 | 0.0002 | - | - | - | - | - | | 3.5429 | 11160 | 0.0016 | - | - | - | - | - | | 3.5460 | 11170 | 0.0009 | - | - | - | - | - | | 3.5492 | 11180 | 0.0008 | - | - | - | - | - | | 3.5524 | 11190 | 0.0063 | - | - | - | - | - | | 3.5556 | 11200 | 0.0001 | - | - | - | - | - | | 3.5587 | 11210 | 0.0 | - | - | - | - | - | | 3.5619 | 11220 | 0.0002 | - | - | - | - | - | | 3.5651 | 11230 | 0.0001 | - | - | - | - | - | | 3.5683 | 11240 | 0.0001 | - | - | - | - | - | | 3.5714 | 11250 | 0.0001 | - | - | - | - | - | | 3.5746 | 11260 | 0.0003 | - | - | - | - | - | | 3.5778 | 11270 | 0.0002 | - | - | - | - | - | | 3.5810 | 11280 | 0.0001 | - | - | - | - | - | | 3.5841 | 11290 | 0.0 | - | - | - | - | - | | 3.5873 | 11300 | 0.0044 | - | - | - | - | - | | 3.5905 | 11310 | 0.0003 | - | - | - | - | - | | 3.5937 | 11320 | 0.0001 | - | - | - | - | - | | 3.5968 | 11330 | 0.0012 | - | - | - | - | - | | 3.6 | 11340 | 0.0097 | - | - | - | - | - | | 3.6032 | 11350 | 0.0 | - | - | - | - | - | | 3.6063 | 11360 | 0.0 | - | - | - | - | - | | 3.6095 | 11370 | 0.0154 | - | - | - | - | - | | 3.6127 | 11380 | 0.0002 | - | - | - | - | - | | 3.6159 | 11390 | 0.0001 | - | - | - | - | - | | 3.6190 | 11400 | 0.0006 | - | - | - | - | - | | 3.6222 | 11410 | 0.0001 | - | - | - | - | - | | 3.6254 | 11420 | 0.0005 | - | - | - | - | - | | 3.6286 | 11430 | 0.0 | - | - | - | - | - | | 3.6317 | 11440 | 0.0003 | - | - | - | - | - | | 3.6349 | 11450 | 0.0003 | - | - | - | - | - | | 3.6381 | 11460 | 0.0017 | - | - | - | - | - | | 3.6413 | 11470 | 0.0 | - | - | - | - | - | | 3.6444 | 11480 | 0.0001 | - | - | - | - | - | | 3.6476 | 11490 | 0.0 | - | - | - | - | - | | 3.6508 | 11500 | 0.0029 | - | - | - | - | - | | 3.6540 | 11510 | 0.0031 | - | - | - | - | - | | 3.6571 | 11520 | 0.0023 | - | - | - | - | - | | 3.6603 | 11530 | 0.0001 | - | - | - | - | - | | 3.6635 | 11540 | 0.0024 | - | - | - | - | - | | 3.6667 | 11550 | 0.0 | - | - | - | - | - | | 3.6698 | 11560 | 0.0403 | - | - | - | - | - | | 3.6730 | 11570 | 0.0 | - | - | - | - | - | | 3.6762 | 11580 | 0.0 | - | - | - | - | - | | 3.6794 | 11590 | 0.0005 | - | - | - | - | - | | 3.6825 | 11600 | 0.0002 | - | - | - | - | - | | 3.6857 | 11610 | 0.0024 | - | - | - | - | - | | 3.6889 | 11620 | 0.0 | - | - | - | - | - | | 3.6921 | 11630 | 0.0011 | - | - | - | - | - | | 3.6952 | 11640 | 0.0 | - | - | - | - | - | | 3.6984 | 11650 | 0.0002 | - | - | - | - | - | | 3.7016 | 11660 | 0.0423 | - | - | - | - | - | | 3.7048 | 11670 | 0.0 | - | - | - | - | - | | 3.7079 | 11680 | 0.0 | - | - | - | - | - | | 3.7111 | 11690 | 0.0003 | - | - | - | - | - | | 3.7143 | 11700 | 0.0 | - | - | - | - | - | | 3.7175 | 11710 | 0.0001 | - | - | - | - | - | | 3.7206 | 11720 | 0.0002 | - | - | - | - | - | | 3.7238 | 11730 | 0.0015 | - | - | - | - | - | | 3.7270 | 11740 | 0.0 | - | - | - | - | - | | 3.7302 | 11750 | 0.0001 | - | - | - | - | - | | 3.7333 | 11760 | 0.0006 | - | - | - | - | - | | 3.7365 | 11770 | 0.0004 | - | - | - | - | - | | 3.7397 | 11780 | 0.0 | - | - | - | - | - | | 3.7429 | 11790 | 0.0002 | - | - | - | - | - | | 3.7460 | 11800 | 0.0004 | - | - | - | - | - | | 3.7492 | 11810 | 0.0029 | - | - | - | - | - | | 3.7524 | 11820 | 0.0001 | - | - | - | - | - | | 3.7556 | 11830 | 0.0001 | - | - | - | - | - | | 3.7587 | 11840 | 0.0 | - | - | - | - | - | | 3.7619 | 11850 | 0.0005 | - | - | - | - | - | | 3.7651 | 11860 | 0.0078 | - | - | - | - | - | | 3.7683 | 11870 | 0.0 | - | - | - | - | - | | 3.7714 | 11880 | 0.0001 | - | - | - | - | - | | 3.7746 | 11890 | 0.0003 | - | - | - | - | - | | 3.7778 | 11900 | 0.0 | - | - | - | - | - | | 3.7810 | 11910 | 0.0001 | - | - | - | - | - | | 3.7841 | 11920 | 0.0037 | - | - | - | - | - | | 3.7873 | 11930 | 0.0 | - | - | - | - | - | | 3.7905 | 11940 | 0.0 | - | - | - | - | - | | 3.7937 | 11950 | 0.298 | - | - | - | - | - | | 3.7968 | 11960 | 0.0 | - | - | - | - | - | | 3.8 | 11970 | 0.0006 | - | - | - | - | - | | 3.8032 | 11980 | 0.0003 | - | - | - | - | - | | 3.8063 | 11990 | 0.0002 | - | - | - | - | - | | 3.8095 | 12000 | 0.0001 | - | - | - | - | - | | 3.8127 | 12010 | 0.0835 | - | - | - | - | - | | 3.8159 | 12020 | 0.0054 | - | - | - | - | - | | 3.8190 | 12030 | 0.0026 | - | - | - | - | - | | 3.8222 | 12040 | 0.0289 | - | - | - | - | - | | 3.8254 | 12050 | 0.0004 | - | - | - | - | - | | 3.8286 | 12060 | 0.0003 | - | - | - | - | - | | 3.8317 | 12070 | 0.0 | - | - | - | - | - | | 3.8349 | 12080 | 0.0002 | - | - | - | - | - | | 3.8381 | 12090 | 0.0002 | - | - | - | - | - | | 3.8413 | 12100 | 0.0 | - | - | - | - | - | | 3.8444 | 12110 | 0.0156 | - | - | - | - | - | | 3.8476 | 12120 | 0.0633 | - | - | - | - | - | | 3.8508 | 12130 | 0.0 | - | - | - | - | - | | 3.8540 | 12140 | 0.0 | - | - | - | - | - | | 3.8571 | 12150 | 0.0 | - | - | - | - | - | | 3.8603 | 12160 | 0.0006 | - | - | - | - | - | | 3.8635 | 12170 | 0.0001 | - | - | - | - | - | | 3.8667 | 12180 | 0.0004 | - | - | - | - | - | | 3.8698 | 12190 | 0.0003 | - | - | - | - | - | | 3.8730 | 12200 | 0.0001 | - | - | - | - | - | | 3.8762 | 12210 | 0.0 | - | - | - | - | - | | 3.8794 | 12220 | 0.0001 | - | - | - | - | - | | 3.8825 | 12230 | 0.0001 | - | - | - | - | - | | 3.8857 | 12240 | 0.0003 | - | - | - | - | - | | 3.8889 | 12250 | 0.0 | - | - | - | - | - | | 3.8921 | 12260 | 0.0001 | - | - | - | - | - | | 3.8952 | 12270 | 0.1166 | - | - | - | - | - | | 3.8984 | 12280 | 0.3643 | - | - | - | - | - | | 3.9016 | 12290 | 0.0004 | - | - | - | - | - | | 3.9048 | 12300 | 0.0001 | - | - | - | - | - | | 3.9079 | 12310 | 0.0095 | - | - | - | - | - | | 3.9111 | 12320 | 0.0003 | - | - | - | - | - | | 3.9143 | 12330 | 0.0003 | - | - | - | - | - | | 3.9175 | 12340 | 0.0174 | - | - | - | - | - | | 3.9206 | 12350 | 0.0 | - | - | - | - | - | | 3.9238 | 12360 | 0.0 | - | - | - | - | - | | 3.9270 | 12370 | 0.0003 | - | - | - | - | - | | 3.9302 | 12380 | 0.0 | - | - | - | - | - | | 3.9333 | 12390 | 0.0001 | - | - | - | - | - | | 3.9365 | 12400 | 0.0 | - | - | - | - | - | | 3.9397 | 12410 | 0.0 | - | - | - | - | - | | 3.9429 | 12420 | 0.0 | - | - | - | - | - | | 3.9460 | 12430 | 0.0001 | - | - | - | - | - | | 3.9492 | 12440 | 0.0001 | - | - | - | - | - | | 3.9524 | 12450 | 0.0 | - | - | - | - | - | | 3.9556 | 12460 | 0.0 | - | - | - | - | - | | 3.9587 | 12470 | 0.0005 | - | - | - | - | - | | 3.9619 | 12480 | 0.0001 | - | - | - | - | - | | 3.9651 | 12490 | 0.0061 | - | - | - | - | - | | 3.9683 | 12500 | 0.0006 | - | - | - | - | - | | 3.9714 | 12510 | 0.0 | - | - | - | - | - | | 3.9746 | 12520 | 0.0005 | - | - | - | - | - | | 3.9778 | 12530 | 0.0001 | - | - | - | - | - | | 3.9810 | 12540 | 0.001 | - | - | - | - | - | | 3.9841 | 12550 | 0.0051 | - | - | - | - | - | | 3.9873 | 12560 | 0.0002 | - | - | - | - | - | | 3.9905 | 12570 | 0.0005 | - | - | - | - | - | | 3.9937 | 12580 | 0.0 | - | - | - | - | - | | 3.9968 | 12590 | 0.001 | - | - | - | - | - | | 4.0 | 12600 | 0.0002 | 0.7771 | 0.7739 | 0.7749 | 0.7568 | 0.7484 | * The bold row denotes the saved checkpoint.
### Framework Versions - Python: 3.11.11 - Sentence Transformers: 3.4.1 - Transformers: 4.48.3 - PyTorch: 2.5.1+cu124 - Accelerate: 1.3.0 - Datasets: 3.3.0 - Tokenizers: 0.21.0 ## Citation ### BibTeX #### Sentence Transformers ```bibtex @inproceedings{reimers-2019-sentence-bert, title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks", author = "Reimers, Nils and Gurevych, Iryna", booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing", month = "11", year = "2019", publisher = "Association for Computational Linguistics", url = "https://arxiv.org/abs/1908.10084", } ``` #### MatryoshkaLoss ```bibtex @misc{kusupati2024matryoshka, title={Matryoshka Representation Learning}, author={Aditya Kusupati and Gantavya Bhatt and Aniket Rege and Matthew Wallingford and Aditya Sinha and Vivek Ramanujan and William Howard-Snyder and Kaifeng Chen and Sham Kakade and Prateek Jain and Ali Farhadi}, year={2024}, eprint={2205.13147}, archivePrefix={arXiv}, primaryClass={cs.LG} } ``` #### MultipleNegativesRankingLoss ```bibtex @misc{henderson2017efficient, title={Efficient Natural Language Response Suggestion for Smart Reply}, author={Matthew Henderson and Rami Al-Rfou and Brian Strope and Yun-hsuan Sung and Laszlo Lukacs and Ruiqi Guo and Sanjiv Kumar and Balint Miklos and Ray Kurzweil}, year={2017}, eprint={1705.00652}, archivePrefix={arXiv}, primaryClass={cs.CL} } ```