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1_Pooling/config.json

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+{
+  "word_embedding_dimension": 384,
+  "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
+}

README.md

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+---
+base_model: sentence-transformers/all-MiniLM-L6-v2
+language:
+- en
+library_name: sentence-transformers
+license: apache-2.0
+pipeline_tag: sentence-similarity
+tags:
+- sentence-transformers
+- sentence-similarity
+- feature-extraction
+- generated_from_trainer
+- dataset_size:9023897
+- loss:CoSENTLoss
+widget:
+- source_sentence: skin care set
+  sentences:
+  - doormat
+  - electronic game
+  - wet cat food
+- source_sentence: cns medicine
+  sentences:
+  - hair mask
+  - anti-infective medicine
+  - allergy medicine
+- source_sentence: face toner
+  sentences:
+  - eye treatment
+  - haircare set
+  - baby mattress
+- source_sentence: baby swing
+  sentences:
+  - acne
+  - escalope
+  - lens solution
+- source_sentence: face treatment
+  sentences:
+  - robot
+  - sanitizer
+  - hair dye
+---
+
+# all-MiniLM-L6-v21-pair_score
+
+This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [sentence-transformers/all-MiniLM-L6-v2](https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2). It maps sentences & paragraphs to a 384-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more.
+
+## Model Details
+
+### Model Description
+- **Model Type:** Sentence Transformer
+- **Base model:** [sentence-transformers/all-MiniLM-L6-v2](https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2) <!-- at revision c9745ed1d9f207416be6d2e6f8de32d1f16199bf -->
+- **Maximum Sequence Length:** 256 tokens
+- **Output Dimensionality:** 384 tokens
+- **Similarity Function:** Cosine Similarity
+<!-- - **Training Dataset:** Unknown -->
+- **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': 256, 'do_lower_case': False}) with Transformer model: BertModel 
+  (1): Pooling({'word_embedding_dimension': 384, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
+  (2): Normalize()
+)
+```
+
+## Usage
+
+### Direct Usage (Sentence Transformers)
+
+First install the Sentence Transformers library:
+
+```bash
+pip install -U sentence-transformers
+```
+
+Then you can load this model and run inference.
+```python
+from sentence_transformers import SentenceTransformer
+
+# Download from the 🤗 Hub
+model = SentenceTransformer("sentence_transformers_model_id")
+# Run inference
+sentences = [
+    'face treatment',
+    'sanitizer',
+    'robot',
+]
+embeddings = model.encode(sentences)
+print(embeddings.shape)
+# [3, 384]
+
+# Get the similarity scores for the embeddings
+similarities = model.similarity(embeddings, embeddings)
+print(similarities.shape)
+# [3, 3]
+```
+
+<!--
+### Direct Usage (Transformers)
+
+<details><summary>Click to see the direct usage in Transformers</summary>
+
+</details>
+-->
+
+<!--
+### Downstream Usage (Sentence Transformers)
+
+You can finetune this model on your own dataset.
+
+<details><summary>Click to expand</summary>
+
+</details>
+-->
+
+<!--
+### Out-of-Scope Use
+
+*List how the model may foreseeably be misused and address what users ought not to do with the model.*
+-->
+
+<!--
+## Bias, Risks and Limitations
+
+*What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.*
+-->
+
+<!--
+### Recommendations
+
+*What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*
+-->
+
+## Training Details
+
+### Training Hyperparameters
+#### Non-Default Hyperparameters
+
+- `eval_strategy`: steps
+- `per_device_train_batch_size`: 128
+- `per_device_eval_batch_size`: 128
+- `learning_rate`: 2e-05
+- `num_train_epochs`: 2
+- `warmup_ratio`: 0.1
+- `fp16`: True
+
+#### All Hyperparameters
+<details><summary>Click to expand</summary>
+
+- `overwrite_output_dir`: False
+- `do_predict`: False
+- `eval_strategy`: steps
+- `prediction_loss_only`: True
+- `per_device_train_batch_size`: 128
+- `per_device_eval_batch_size`: 128
+- `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`: 2
+- `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
+- `eval_do_concat_batches`: True
+- `fp16_backend`: auto
+- `push_to_hub_model_id`: None
+- `push_to_hub_organization`: None
+- `mp_parameters`: 
+- `auto_find_batch_size`: False
+- `full_determinism`: False
+- `torchdynamo`: None
+- `ray_scope`: last
+- `ddp_timeout`: 1800
+- `torch_compile`: False
+- `torch_compile_backend`: None
+- `torch_compile_mode`: None
+- `dispatch_batches`: None
+- `split_batches`: None
+- `include_tokens_per_second`: False
+- `include_num_input_tokens_seen`: False
+- `neftune_noise_alpha`: None
+- `optim_target_modules`: None
+- `batch_eval_metrics`: False
+- `eval_on_start`: False
+- `use_liger_kernel`: False
+- `eval_use_gather_object`: False
+- `batch_sampler`: batch_sampler
+- `multi_dataset_batch_sampler`: proportional
+
+</details>
+
+### Training Logs
+<details><summary>Click to expand</summary>
+
+| Epoch  | Step   | Training Loss |
+|:------:|:------:|:-------------:|
+| 0.0014 | 100    | 13.1926       |
+| 0.0028 | 200    | 12.7965       |
+| 0.0043 | 300    | 13.0186       |
+| 0.0057 | 400    | 12.592        |
+| 0.0071 | 500    | 12.1638       |
+| 0.0085 | 600    | 11.8915       |
+| 0.0099 | 700    | 11.3471       |
+| 0.0113 | 800    | 10.7371       |
+| 0.0128 | 900    | 10.3852       |
+| 0.0142 | 1000   | 10.063        |
+| 0.0156 | 1100   | 9.8313        |
+| 0.0170 | 1200   | 9.4219        |
+| 0.0184 | 1300   | 9.1946        |
+| 0.0199 | 1400   | 8.9783        |
+| 0.0213 | 1500   | 8.7999        |
+| 0.0227 | 1600   | 8.6779        |
+| 0.0241 | 1700   | 8.6218        |
+| 0.0255 | 1800   | 8.5675        |
+| 0.0270 | 1900   | 8.5168        |
+| 0.0284 | 2000   | 8.4996        |
+| 0.0298 | 2100   | 8.4476        |
+| 0.0312 | 2200   | 8.4191        |
+| 0.0326 | 2300   | 8.406         |
+| 0.0340 | 2400   | 8.386         |
+| 0.0355 | 2500   | 8.3749        |
+| 0.0369 | 2600   | 8.3491        |
+| 0.0383 | 2700   | 8.3128        |
+| 0.0397 | 2800   | 8.3038        |
+| 0.0411 | 2900   | 8.3037        |
+| 0.0426 | 3000   | 8.2735        |
+| 0.0440 | 3100   | 8.2638        |
+| 0.0454 | 3200   | 8.2546        |
+| 0.0468 | 3300   | 8.2439        |
+| 0.0482 | 3400   | 8.2059        |
+| 0.0496 | 3500   | 8.2128        |
+| 0.0511 | 3600   | 8.1799        |
+| 0.0525 | 3700   | 8.1863        |
+| 0.0539 | 3800   | 8.1623        |
+| 0.0553 | 3900   | 8.1668        |
+| 0.0567 | 4000   | 8.1375        |
+| 0.0582 | 4100   | 8.1484        |
+| 0.0596 | 4200   | 8.1301        |
+| 0.0610 | 4300   | 8.1205        |
+| 0.0624 | 4400   | 8.132         |
+| 0.0638 | 4500   | 8.1021        |
+| 0.0652 | 4600   | 8.0993        |
+| 0.0667 | 4700   | 8.0933        |
+| 0.0681 | 4800   | 8.0866        |
+| 0.0695 | 4900   | 8.0852        |
+| 0.0709 | 5000   | 8.0674        |
+| 0.0723 | 5100   | 8.0485        |
+| 0.0738 | 5200   | 8.0453        |
+| 0.0752 | 5300   | 8.0494        |
+| 0.0766 | 5400   | 8.0396        |
+| 0.0780 | 5500   | 8.0254        |
+| 0.0794 | 5600   | 8.0223        |
+| 0.0809 | 5700   | 8.0241        |
+| 0.0823 | 5800   | 8.0161        |
+| 0.0837 | 5900   | 7.9888        |
+| 0.0851 | 6000   | 8.0131        |
+| 0.0865 | 6100   | 7.9777        |
+| 0.0879 | 6200   | 8.0133        |
+| 0.0894 | 6300   | 7.9891        |
+| 0.0908 | 6400   | 7.9665        |
+| 0.0922 | 6500   | 7.9621        |
+| 0.0936 | 6600   | 7.9568        |
+| 0.0950 | 6700   | 7.9671        |
+| 0.0965 | 6800   | 7.9379        |
+| 0.0979 | 6900   | 7.9467        |
+| 0.0993 | 7000   | 7.954         |
+| 0.1007 | 7100   | 7.9413        |
+| 0.1021 | 7200   | 7.9499        |
+| 0.1035 | 7300   | 7.9286        |
+| 0.1050 | 7400   | 7.9186        |
+| 0.1064 | 7500   | 7.945         |
+| 0.1078 | 7600   | 7.9161        |
+| 0.1092 | 7700   | 7.9335        |
+| 0.1106 | 7800   | 7.8967        |
+| 0.1121 | 7900   | 7.899         |
+| 0.1135 | 8000   | 7.914         |
+| 0.1149 | 8100   | 7.8768        |
+| 0.1163 | 8200   | 7.8898        |
+| 0.1177 | 8300   | 7.8854        |
+| 0.1191 | 8400   | 7.8742        |
+| 0.1206 | 8500   | 7.8869        |
+| 0.1220 | 8600   | 7.8585        |
+| 0.1234 | 8700   | 7.8731        |
+| 0.1248 | 8800   | 7.8791        |
+| 0.1262 | 8900   | 7.8838        |
+| 0.1277 | 9000   | 7.8344        |
+| 0.1291 | 9100   | 7.8813        |
+| 0.1305 | 9200   | 7.8482        |
+| 0.1319 | 9300   | 7.8605        |
+| 0.1333 | 9400   | 7.84          |
+| 0.1348 | 9500   | 7.8331        |
+| 0.1362 | 9600   | 7.8232        |
+| 0.1376 | 9700   | 7.8043        |
+| 0.1390 | 9800   | 7.8339        |
+| 0.1404 | 9900   | 7.8262        |
+| 0.1418 | 10000  | 7.8093        |
+| 0.1433 | 10100  | 7.8055        |
+| 0.1447 | 10200  | 7.8286        |
+| 0.1461 | 10300  | 7.7943        |
+| 0.1475 | 10400  | 7.8559        |
+| 0.1489 | 10500  | 7.8121        |
+| 0.1504 | 10600  | 7.7787        |
+| 0.1518 | 10700  | 7.8017        |
+| 0.1532 | 10800  | 7.7884        |
+| 0.1546 | 10900  | 7.7895        |
+| 0.1560 | 11000  | 7.7691        |
+| 0.1574 | 11100  | 7.7967        |
+| 0.1589 | 11200  | 7.8325        |
+| 0.1603 | 11300  | 7.7863        |
+| 0.1617 | 11400  | 7.818         |
+| 0.1631 | 11500  | 7.8287        |
+| 0.1645 | 11600  | 7.7717        |
+| 0.1660 | 11700  | 7.7722        |
+| 0.1674 | 11800  | 7.783         |
+| 0.1688 | 11900  | 7.7608        |
+| 0.1702 | 12000  | 7.7524        |
+| 0.1716 | 12100  | 7.7639        |
+| 0.1730 | 12200  | 7.731         |
+| 0.1745 | 12300  | 7.7499        |
+| 0.1759 | 12400  | 7.7599        |
+| 0.1773 | 12500  | 7.7632        |
+| 0.1787 | 12600  | 7.7825        |
+| 0.1801 | 12700  | 7.7823        |
+| 0.1816 | 12800  | 7.7447        |
+| 0.1830 | 12900  | 7.7455        |
+| 0.1844 | 13000  | 7.7233        |
+| 0.1858 | 13100  | 7.7437        |
+| 0.1872 | 13200  | 7.7554        |
+| 0.1887 | 13300  | 7.7031        |
+| 0.1901 | 13400  | 7.7725        |
+| 0.1915 | 13500  | 7.7337        |
+| 0.1929 | 13600  | 7.7325        |
+| 0.1943 | 13700  | 7.7488        |
+| 0.1957 | 13800  | 7.7266        |
+| 0.1972 | 13900  | 7.6917        |
+| 0.1986 | 14000  | 7.6886        |
+| 0.2    | 14100  | 7.6839        |
+| 0.2014 | 14200  | 7.6947        |
+| 0.2028 | 14300  | 7.7174        |
+| 0.2043 | 14400  | 7.6882        |
+| 0.2057 | 14500  | 7.7202        |
+| 0.2071 | 14600  | 7.7566        |
+| 0.2085 | 14700  | 7.699         |
+| 0.2099 | 14800  | 7.702         |
+| 0.2113 | 14900  | 7.671         |
+| 0.2128 | 15000  | 7.687         |
+| 0.2142 | 15100  | 7.7349        |
+| 0.2156 | 15200  | 7.7308        |
+| 0.2170 | 15300  | 7.6846        |
+| 0.2184 | 15400  | 7.6872        |
+| 0.2199 | 15500  | 7.6688        |
+| 0.2213 | 15600  | 7.7193        |
+| 0.2227 | 15700  | 7.6603        |
+| 0.2241 | 15800  | 7.7124        |
+| 0.2255 | 15900  | 7.658         |
+| 0.2270 | 16000  | 7.708         |
+| 0.2284 | 16100  | 7.6993        |
+| 0.2298 | 16200  | 7.6786        |
+| 0.2312 | 16300  | 7.6509        |
+| 0.2326 | 16400  | 7.6592        |
+| 0.2340 | 16500  | 7.6347        |
+| 0.2355 | 16600  | 7.6557        |
+| 0.2369 | 16700  | 7.6833        |
+| 0.2383 | 16800  | 7.6439        |
+| 0.2397 | 16900  | 7.6878        |
+| 0.2411 | 17000  | 7.6573        |
+| 0.2426 | 17100  | 7.6726        |
+| 0.2440 | 17200  | 7.6749        |
+| 0.2454 | 17300  | 7.6618        |
+| 0.2468 | 17400  | 7.6341        |
+| 0.2482 | 17500  | 7.692         |
+| 0.2496 | 17600  | 7.6604        |
+| 0.2511 | 17700  | 7.6435        |
+| 0.2525 | 17800  | 7.6627        |
+| 0.2539 | 17900  | 7.6613        |
+| 0.2553 | 18000  | 7.631         |
+| 0.2567 | 18100  | 7.6401        |
+| 0.2582 | 18200  | 7.6423        |
+| 0.2596 | 18300  | 7.6891        |
+| 0.2610 | 18400  | 7.6624        |
+| 0.2624 | 18500  | 7.6234        |
+| 0.2638 | 18600  | 7.6601        |
+| 0.2652 | 18700  | 7.6392        |
+| 0.2667 | 18800  | 7.6069        |
+| 0.2681 | 18900  | 7.6199        |
+| 0.2695 | 19000  | 7.6209        |
+| 0.2709 | 19100  | 7.5967        |
+| 0.2723 | 19200  | 7.6222        |
+| 0.2738 | 19300  | 7.6262        |
+| 0.2752 | 19400  | 7.6529        |
+| 0.2766 | 19500  | 7.5978        |
+| 0.2780 | 19600  | 7.6217        |
+| 0.2794 | 19700  | 7.6253        |
+| 0.2809 | 19800  | 7.6321        |
+| 0.2823 | 19900  | 7.6352        |
+| 0.2837 | 20000  | 7.6366        |
+| 0.2851 | 20100  | 7.6022        |
+| 0.2865 | 20200  | 7.5817        |
+| 0.2879 | 20300  | 7.642         |
+| 0.2894 | 20400  | 7.6274        |
+| 0.2908 | 20500  | 7.6394        |
+| 0.2922 | 20600  | 7.6288        |
+| 0.2936 | 20700  | 7.6059        |
+| 0.2950 | 20800  | 7.6016        |
+| 0.2965 | 20900  | 7.6527        |
+| 0.2979 | 21000  | 7.6101        |
+| 0.2993 | 21100  | 7.537         |
+| 0.3007 | 21200  | 7.5946        |
+| 0.3021 | 21300  | 7.5853        |
+| 0.3035 | 21400  | 7.6598        |
+| 0.3050 | 21500  | 7.6054        |
+| 0.3064 | 21600  | 7.5602        |
+| 0.3078 | 21700  | 7.6165        |
+| 0.3092 | 21800  | 7.5782        |
+| 0.3106 | 21900  | 7.6019        |
+| 0.3121 | 22000  | 7.5393        |
+| 0.3135 | 22100  | 7.5868        |
+| 0.3149 | 22200  | 7.6434        |
+| 0.3163 | 22300  | 7.5713        |
+| 0.3177 | 22400  | 7.6273        |
+| 0.3191 | 22500  | 7.5923        |
+| 0.3206 | 22600  | 7.5879        |
+| 0.3220 | 22700  | 7.5742        |
+| 0.3234 | 22800  | 7.5607        |
+| 0.3248 | 22900  | 7.6186        |
+| 0.3262 | 23000  | 7.5912        |
+| 0.3277 | 23100  | 7.5993        |
+| 0.3291 | 23200  | 7.5842        |
+| 0.3305 | 23300  | 7.6018        |
+| 0.3319 | 23400  | 7.546         |
+| 0.3333 | 23500  | 7.5828        |
+| 0.3348 | 23600  | 7.5476        |
+| 0.3362 | 23700  | 7.5416        |
+| 0.3376 | 23800  | 7.5567        |
+| 0.3390 | 23900  | 7.56          |
+| 0.3404 | 24000  | 7.5953        |
+| 0.3418 | 24100  | 7.5539        |
+| 0.3433 | 24200  | 7.6377        |
+| 0.3447 | 24300  | 7.5183        |
+| 0.3461 | 24400  | 7.5869        |
+| 0.3475 | 24500  | 7.5998        |
+| 0.3489 | 24600  | 7.5344        |
+| 0.3504 | 24700  | 7.5907        |
+| 0.3518 | 24800  | 7.5223        |
+| 0.3532 | 24900  | 7.5677        |
+| 0.3546 | 25000  | 7.5836        |
+| 0.3560 | 25100  | 7.6285        |
+| 0.3574 | 25200  | 7.577         |
+| 0.3589 | 25300  | 7.5204        |
+| 0.3603 | 25400  | 7.6041        |
+| 0.3617 | 25500  | 7.5132        |
+| 0.3631 | 25600  | 7.6004        |
+| 0.3645 | 25700  | 7.618         |
+| 0.3660 | 25800  | 7.5518        |
+| 0.3674 | 25900  | 7.5001        |
+| 0.3688 | 26000  | 7.5266        |
+| 0.3702 | 26100  | 7.5333        |
+| 0.3716 | 26200  | 7.6075        |
+| 0.3730 | 26300  | 7.5061        |
+| 0.3745 | 26400  | 7.5303        |
+| 0.3759 | 26500  | 7.5301        |
+| 0.3773 | 26600  | 7.5022        |
+| 0.3787 | 26700  | 7.5075        |
+| 0.3801 | 26800  | 7.5522        |
+| 0.3816 | 26900  | 7.5112        |
+| 0.3830 | 27000  | 7.5784        |
+| 0.3844 | 27100  | 7.5146        |
+| 0.3858 | 27200  | 7.5445        |
+| 0.3872 | 27300  | 7.5492        |
+| 0.3887 | 27400  | 7.4975        |
+| 0.3901 | 27500  | 7.5075        |
+| 0.3915 | 27600  | 7.5115        |
+| 0.3929 | 27700  | 7.4821        |
+| 0.3943 | 27800  | 7.5776        |
+| 0.3957 | 27900  | 7.5531        |
+| 0.3972 | 28000  | 7.6073        |
+| 0.3986 | 28100  | 7.5666        |
+| 0.4    | 28200  | 7.5001        |
+| 0.4014 | 28300  | 7.5225        |
+| 0.4028 | 28400  | 7.5137        |
+| 0.4043 | 28500  | 7.5351        |
+| 0.4057 | 28600  | 7.4937        |
+| 0.4071 | 28700  | 7.5395        |
+| 0.4085 | 28800  | 7.4923        |
+| 0.4099 | 28900  | 7.5133        |
+| 0.4113 | 29000  | 7.4948        |
+| 0.4128 | 29100  | 7.5055        |
+| 0.4142 | 29200  | 7.5511        |
+| 0.4156 | 29300  | 7.5725        |
+| 0.4170 | 29400  | 7.6092        |
+| 0.4184 | 29500  | 7.5414        |
+| 0.4199 | 29600  | 7.5168        |
+| 0.4213 | 29700  | 7.5362        |
+| 0.4227 | 29800  | 7.5131        |
+| 0.4241 | 29900  | 7.5356        |
+| 0.4255 | 30000  | 7.5324        |
+| 0.4270 | 30100  | 7.5002        |
+| 0.4284 | 30200  | 7.5711        |
+| 0.4298 | 30300  | 7.5307        |
+| 0.4312 | 30400  | 7.5115        |
+| 0.4326 | 30500  | 7.535         |
+| 0.4340 | 30600  | 7.4797        |
+| 0.4355 | 30700  | 7.4996        |
+| 0.4369 | 30800  | 7.5144        |
+| 0.4383 | 30900  | 7.6262        |
+| 0.4397 | 31000  | 7.5492        |
+| 0.4411 | 31100  | 7.5129        |
+| 0.4426 | 31200  | 7.4567        |
+| 0.4440 | 31300  | 7.462         |
+| 0.4454 | 31400  | 7.4654        |
+| 0.4468 | 31500  | 7.5414        |
+| 0.4482 | 31600  | 7.5087        |
+| 0.4496 | 31700  | 7.4987        |
+| 0.4511 | 31800  | 7.5223        |
+| 0.4525 | 31900  | 7.5589        |
+| 0.4539 | 32000  | 7.5093        |
+| 0.4553 | 32100  | 7.5167        |
+| 0.4567 | 32200  | 7.4632        |
+| 0.4582 | 32300  | 7.4998        |
+| 0.4596 | 32400  | 7.4559        |
+| 0.4610 | 32500  | 7.4844        |
+| 0.4624 | 32600  | 7.586         |
+| 0.4638 | 32700  | 7.5281        |
+| 0.4652 | 32800  | 7.4701        |
+| 0.4667 | 32900  | 7.4929        |
+| 0.4681 | 33000  | 7.5465        |
+| 0.4695 | 33100  | 7.506         |
+| 0.4709 | 33200  | 7.5596        |
+| 0.4723 | 33300  | 7.4181        |
+| 0.4738 | 33400  | 7.5174        |
+| 0.4752 | 33500  | 7.487         |
+| 0.4766 | 33600  | 7.523         |
+| 0.4780 | 33700  | 7.4432        |
+| 0.4794 | 33800  | 7.5235        |
+| 0.4809 | 33900  | 7.4662        |
+| 0.4823 | 34000  | 7.527         |
+| 0.4837 | 34100  | 7.5106        |
+| 0.4851 | 34200  | 7.5687        |
+| 0.4865 | 34300  | 7.4932        |
+| 0.4879 | 34400  | 7.5147        |
+| 0.4894 | 34500  | 7.5173        |
+| 0.4908 | 34600  | 7.528         |
+| 0.4922 | 34700  | 7.5241        |
+| 0.4936 | 34800  | 7.4627        |
+| 0.4950 | 34900  | 7.4977        |
+| 0.4965 | 35000  | 7.475         |
+| 0.4979 | 35100  | 7.425         |
+| 0.4993 | 35200  | 7.5461        |
+| 0.5007 | 35300  | 7.4329        |
+| 0.5021 | 35400  | 7.4677        |
+| 0.5035 | 35500  | 7.446         |
+| 0.5050 | 35600  | 7.5136        |
+| 0.5064 | 35700  | 7.499         |
+| 0.5078 | 35800  | 7.4542        |
+| 0.5092 | 35900  | 7.5076        |
+| 0.5106 | 36000  | 7.5057        |
+| 0.5121 | 36100  | 7.4773        |
+| 0.5135 | 36200  | 7.4421        |
+| 0.5149 | 36300  | 7.4906        |
+| 0.5163 | 36400  | 7.3963        |
+| 0.5177 | 36500  | 7.468         |
+| 0.5191 | 36600  | 7.512         |
+| 0.5206 | 36700  | 7.4673        |
+| 0.5220 | 36800  | 7.4828        |
+| 0.5234 | 36900  | 7.5092        |
+| 0.5248 | 37000  | 7.4725        |
+| 0.5262 | 37100  | 7.5191        |
+| 0.5277 | 37200  | 7.4546        |
+| 0.5291 | 37300  | 7.5097        |
+| 0.5305 | 37400  | 7.4875        |
+| 0.5319 | 37500  | 7.518         |
+| 0.5333 | 37600  | 7.4315        |
+| 0.5348 | 37700  | 7.4724        |
+| 0.5362 | 37800  | 7.4255        |
+| 0.5376 | 37900  | 7.4805        |
+| 0.5390 | 38000  | 7.5031        |
+| 0.5404 | 38100  | 7.4222        |
+| 0.5418 | 38200  | 7.4945        |
+| 0.5433 | 38300  | 7.4264        |
+| 0.5447 | 38400  | 7.4426        |
+| 0.5461 | 38500  | 7.4948        |
+| 0.5475 | 38600  | 7.4579        |
+| 0.5489 | 38700  | 7.4756        |
+| 0.5504 | 38800  | 7.6029        |
+| 0.5518 | 38900  | 7.4873        |
+| 0.5532 | 39000  | 7.4669        |
+| 0.5546 | 39100  | 7.4513        |
+| 0.5560 | 39200  | 7.4522        |
+| 0.5574 | 39300  | 7.4544        |
+| 0.5589 | 39400  | 7.4581        |
+| 0.5603 | 39500  | 7.4162        |
+| 0.5617 | 39600  | 7.4203        |
+| 0.5631 | 39700  | 7.4348        |
+| 0.5645 | 39800  | 7.4467        |
+| 0.5660 | 39900  | 7.407         |
+| 0.5674 | 40000  | 7.4431        |
+| 0.5688 | 40100  | 7.4367        |
+| 0.5702 | 40200  | 7.4587        |
+| 0.5716 | 40300  | 7.3733        |
+| 0.5730 | 40400  | 7.5482        |
+| 0.5745 | 40500  | 7.456         |
+| 0.5759 | 40600  | 7.5009        |
+| 0.5773 | 40700  | 7.5035        |
+| 0.5787 | 40800  | 7.4635        |
+| 0.5801 | 40900  | 7.4623        |
+| 0.5816 | 41000  | 7.4451        |
+| 0.5830 | 41100  | 7.4141        |
+| 0.5844 | 41200  | 7.4855        |
+| 0.5858 | 41300  | 7.406         |
+| 0.5872 | 41400  | 7.4292        |
+| 0.5887 | 41500  | 7.494         |
+| 0.5901 | 41600  | 7.4258        |
+| 0.5915 | 41700  | 7.4412        |
+| 0.5929 | 41800  | 7.4179        |
+| 0.5943 | 41900  | 7.4424        |
+| 0.5957 | 42000  | 7.4882        |
+| 0.5972 | 42100  | 7.4944        |
+| 0.5986 | 42200  | 7.3424        |
+| 0.6    | 42300  | 7.5249        |
+| 0.6014 | 42400  | 7.413         |
+| 0.6028 | 42500  | 7.4411        |
+| 0.6043 | 42600  | 7.4715        |
+| 0.6057 | 42700  | 7.4828        |
+| 0.6071 | 42800  | 7.5002        |
+| 0.6085 | 42900  | 7.463         |
+| 0.6099 | 43000  | 7.3597        |
+| 0.6113 | 43100  | 7.4367        |
+| 0.6128 | 43200  | 7.5433        |
+| 0.6142 | 43300  | 7.4771        |
+| 0.6156 | 43400  | 7.4954        |
+| 0.6170 | 43500  | 7.4272        |
+| 0.6184 | 43600  | 7.4325        |
+| 0.6199 | 43700  | 7.4745        |
+| 0.6213 | 43800  | 7.4508        |
+| 0.6227 | 43900  | 7.3977        |
+| 0.6241 | 44000  | 7.5164        |
+| 0.6255 | 44100  | 7.4729        |
+| 0.6270 | 44200  | 7.5065        |
+| 0.6284 | 44300  | 7.483         |
+| 0.6298 | 44400  | 7.438         |
+| 0.6312 | 44500  | 7.4311        |
+| 0.6326 | 44600  | 7.4824        |
+| 0.6340 | 44700  | 7.4421        |
+| 0.6355 | 44800  | 7.47          |
+| 0.6369 | 44900  | 7.3865        |
+| 0.6383 | 45000  | 7.4264        |
+| 0.6397 | 45100  | 7.4468        |
+| 0.6411 | 45200  | 7.3725        |
+| 0.6426 | 45300  | 7.3888        |
+| 0.6440 | 45400  | 7.4234        |
+| 0.6454 | 45500  | 7.4253        |
+| 0.6468 | 45600  | 7.4953        |
+| 0.6482 | 45700  | 7.451         |
+| 0.6496 | 45800  | 7.4424        |
+| 0.6511 | 45900  | 7.3959        |
+| 0.6525 | 46000  | 7.4706        |
+| 0.6539 | 46100  | 7.4002        |
+| 0.6553 | 46200  | 7.3839        |
+| 0.6567 | 46300  | 7.4296        |
+| 0.6582 | 46400  | 7.4449        |
+| 0.6596 | 46500  | 7.3793        |
+| 0.6610 | 46600  | 7.463         |
+| 0.6624 | 46700  | 7.4034        |
+| 0.6638 | 46800  | 7.4178        |
+| 0.6652 | 46900  | 7.4174        |
+| 0.6667 | 47000  | 7.4481        |
+| 0.6681 | 47100  | 7.5285        |
+| 0.6695 | 47200  | 7.3878        |
+| 0.6709 | 47300  | 7.3894        |
+| 0.6723 | 47400  | 7.4658        |
+| 0.6738 | 47500  | 7.4161        |
+| 0.6752 | 47600  | 7.4127        |
+| 0.6766 | 47700  | 7.4215        |
+| 0.6780 | 47800  | 7.3838        |
+| 0.6794 | 47900  | 7.4643        |
+| 0.6809 | 48000  | 7.4168        |
+| 0.6823 | 48100  | 7.4078        |
+| 0.6837 | 48200  | 7.4339        |
+| 0.6851 | 48300  | 7.3993        |
+| 0.6865 | 48400  | 7.4831        |
+| 0.6879 | 48500  | 7.4778        |
+| 0.6894 | 48600  | 7.4498        |
+| 0.6908 | 48700  | 7.3906        |
+| 0.6922 | 48800  | 7.4844        |
+| 0.6936 | 48900  | 7.4273        |
+| 0.6950 | 49000  | 7.402         |
+| 0.6965 | 49100  | 7.4395        |
+| 0.6979 | 49200  | 7.3888        |
+| 0.6993 | 49300  | 7.372         |
+| 0.7007 | 49400  | 7.4587        |
+| 0.7021 | 49500  | 7.5481        |
+| 0.7035 | 49600  | 7.4094        |
+| 0.7050 | 49700  | 7.4186        |
+| 0.7064 | 49800  | 7.3886        |
+| 0.7078 | 49900  | 7.3778        |
+| 0.7092 | 50000  | 7.4144        |
+| 0.7106 | 50100  | 7.4409        |
+| 0.7121 | 50200  | 7.4089        |
+| 0.7135 | 50300  | 7.4795        |
+| 0.7149 | 50400  | 7.3671        |
+| 0.7163 | 50500  | 7.4154        |
+| 0.7177 | 50600  | 7.4991        |
+| 0.7191 | 50700  | 7.4587        |
+| 0.7206 | 50800  | 7.4723        |
+| 0.7220 | 50900  | 7.3638        |
+| 0.7234 | 51000  | 7.3765        |
+| 0.7248 | 51100  | 7.3947        |
+| 0.7262 | 51200  | 7.4181        |
+| 0.7277 | 51300  | 7.3822        |
+| 0.7291 | 51400  | 7.4111        |
+| 0.7305 | 51500  | 7.4081        |
+| 0.7319 | 51600  | 7.4102        |
+| 0.7333 | 51700  | 7.4177        |
+| 0.7348 | 51800  | 7.4462        |
+| 0.7362 | 51900  | 7.3557        |
+| 0.7376 | 52000  | 7.4572        |
+| 0.7390 | 52100  | 7.4117        |
+| 0.7404 | 52200  | 7.4284        |
+| 0.7418 | 52300  | 7.4234        |
+| 0.7433 | 52400  | 7.3917        |
+| 0.7447 | 52500  | 7.3467        |
+| 0.7461 | 52600  | 7.3821        |
+| 0.7475 | 52700  | 7.4541        |
+| 0.7489 | 52800  | 7.4189        |
+| 0.7504 | 52900  | 7.4509        |
+| 0.7518 | 53000  | 7.3829        |
+| 0.7532 | 53100  | 7.3373        |
+| 0.7546 | 53200  | 7.3314        |
+| 0.7560 | 53300  | 7.4043        |
+| 0.7574 | 53400  | 7.4792        |
+| 0.7589 | 53500  | 7.4152        |
+| 0.7603 | 53600  | 7.404         |
+| 0.7617 | 53700  | 7.4486        |
+| 0.7631 | 53800  | 7.3498        |
+| 0.7645 | 53900  | 7.3969        |
+| 0.7660 | 54000  | 7.3918        |
+| 0.7674 | 54100  | 7.3876        |
+| 0.7688 | 54200  | 7.3964        |
+| 0.7702 | 54300  | 7.4086        |
+| 0.7716 | 54400  | 7.416         |
+| 0.7730 | 54500  | 7.4601        |
+| 0.7745 | 54600  | 7.37          |
+| 0.7759 | 54700  | 7.4409        |
+| 0.7773 | 54800  | 7.3761        |
+| 0.7787 | 54900  | 7.3773        |
+| 0.7801 | 55000  | 7.4095        |
+| 0.7816 | 55100  | 7.415         |
+| 0.7830 | 55200  | 7.417         |
+| 0.7844 | 55300  | 7.3764        |
+| 0.7858 | 55400  | 7.4076        |
+| 0.7872 | 55500  | 7.4049        |
+| 0.7887 | 55600  | 7.3818        |
+| 0.7901 | 55700  | 7.366         |
+| 0.7915 | 55800  | 7.398         |
+| 0.7929 | 55900  | 7.427         |
+| 0.7943 | 56000  | 7.3833        |
+| 0.7957 | 56100  | 7.3616        |
+| 0.7972 | 56200  | 7.396         |
+| 0.7986 | 56300  | 7.3264        |
+| 0.8    | 56400  | 7.4165        |
+| 0.8014 | 56500  | 7.5058        |
+| 0.8028 | 56600  | 7.3736        |
+| 0.8043 | 56700  | 7.3962        |
+| 0.8057 | 56800  | 7.384         |
+| 0.8071 | 56900  | 7.3815        |
+| 0.8085 | 57000  | 7.3507        |
+| 0.8099 | 57100  | 7.3604        |
+| 0.8113 | 57200  | 7.4224        |
+| 0.8128 | 57300  | 7.3843        |
+| 0.8142 | 57400  | 7.4532        |
+| 0.8156 | 57500  | 7.4106        |
+| 0.8170 | 57600  | 7.3154        |
+| 0.8184 | 57700  | 7.4465        |
+| 0.8199 | 57800  | 7.378         |
+| 0.8213 | 57900  | 7.4425        |
+| 0.8227 | 58000  | 7.381         |
+| 0.8241 | 58100  | 7.3555        |
+| 0.8255 | 58200  | 7.3051        |
+| 0.8270 | 58300  | 7.4611        |
+| 0.8284 | 58400  | 7.3804        |
+| 0.8298 | 58500  | 7.4109        |
+| 0.8312 | 58600  | 7.3147        |
+| 0.8326 | 58700  | 7.3951        |
+| 0.8340 | 58800  | 7.3367        |
+| 0.8355 | 58900  | 7.4197        |
+| 0.8369 | 59000  | 7.3802        |
+| 0.8383 | 59100  | 7.4018        |
+| 0.8397 | 59200  | 7.3135        |
+| 0.8411 | 59300  | 7.3565        |
+| 0.8426 | 59400  | 7.3591        |
+| 0.8440 | 59500  | 7.4112        |
+| 0.8454 | 59600  | 7.4384        |
+| 0.8468 | 59700  | 7.4535        |
+| 0.8482 | 59800  | 7.2803        |
+| 0.8496 | 59900  | 7.3927        |
+| 0.8511 | 60000  | 7.3394        |
+| 0.8525 | 60100  | 7.376         |
+| 0.8539 | 60200  | 7.4899        |
+| 0.8553 | 60300  | 7.3667        |
+| 0.8567 | 60400  | 7.3682        |
+| 0.8582 | 60500  | 7.482         |
+| 0.8596 | 60600  | 7.4628        |
+| 0.8610 | 60700  | 7.4207        |
+| 0.8624 | 60800  | 7.3217        |
+| 0.8638 | 60900  | 7.514         |
+| 0.8652 | 61000  | 7.4524        |
+| 0.8667 | 61100  | 7.3489        |
+| 0.8681 | 61200  | 7.3895        |
+| 0.8695 | 61300  | 7.3907        |
+| 0.8709 | 61400  | 7.3386        |
+| 0.8723 | 61500  | 7.3769        |
+| 0.8738 | 61600  | 7.3689        |
+| 0.8752 | 61700  | 7.3252        |
+| 0.8766 | 61800  | 7.3877        |
+| 0.8780 | 61900  | 7.3726        |
+| 0.8794 | 62000  | 7.3994        |
+| 0.8809 | 62100  | 7.3763        |
+| 0.8823 | 62200  | 7.4137        |
+| 0.8837 | 62300  | 7.3515        |
+| 0.8851 | 62400  | 7.3949        |
+| 0.8865 | 62500  | 7.3789        |
+| 0.8879 | 62600  | 7.3886        |
+| 0.8894 | 62700  | 7.3787        |
+| 0.8908 | 62800  | 7.3959        |
+| 0.8922 | 62900  | 7.3803        |
+| 0.8936 | 63000  | 7.4508        |
+| 0.8950 | 63100  | 7.3858        |
+| 0.8965 | 63200  | 7.361         |
+| 0.8979 | 63300  | 7.3594        |
+| 0.8993 | 63400  | 7.4251        |
+| 0.9007 | 63500  | 7.3099        |
+| 0.9021 | 63600  | 7.3997        |
+| 0.9035 | 63700  | 7.3899        |
+| 0.9050 | 63800  | 7.2831        |
+| 0.9064 | 63900  | 7.3826        |
+| 0.9078 | 64000  | 7.5137        |
+| 0.9092 | 64100  | 7.4258        |
+| 0.9106 | 64200  | 7.4195        |
+| 0.9121 | 64300  | 7.4142        |
+| 0.9135 | 64400  | 7.3062        |
+| 0.9149 | 64500  | 7.2996        |
+| 0.9163 | 64600  | 7.4322        |
+| 0.9177 | 64700  | 7.3144        |
+| 0.9191 | 64800  | 7.4039        |
+| 0.9206 | 64900  | 7.2989        |
+| 0.9220 | 65000  | 7.3177        |
+| 0.9234 | 65100  | 7.3395        |
+| 0.9248 | 65200  | 7.3534        |
+| 0.9262 | 65300  | 7.457         |
+| 0.9277 | 65400  | 7.3587        |
+| 0.9291 | 65500  | 7.3916        |
+| 0.9305 | 65600  | 7.3288        |
+| 0.9319 | 65700  | 7.4309        |
+| 0.9333 | 65800  | 7.4627        |
+| 0.9348 | 65900  | 7.4091        |
+| 0.9362 | 66000  | 7.4049        |
+| 0.9376 | 66100  | 7.341         |
+| 0.9390 | 66200  | 7.362         |
+| 0.9404 | 66300  | 7.3172        |
+| 0.9418 | 66400  | 7.3683        |
+| 0.9433 | 66500  | 7.3487        |
+| 0.9447 | 66600  | 7.3346        |
+| 0.9461 | 66700  | 7.3146        |
+| 0.9475 | 66800  | 7.4002        |
+| 0.9489 | 66900  | 7.4141        |
+| 0.9504 | 67000  | 7.3986        |
+| 0.9518 | 67100  | 7.3521        |
+| 0.9532 | 67200  | 7.4079        |
+| 0.9546 | 67300  | 7.3378        |
+| 0.9560 | 67400  | 7.3006        |
+| 0.9574 | 67500  | 7.3506        |
+| 0.9589 | 67600  | 7.3671        |
+| 0.9603 | 67700  | 7.4017        |
+| 0.9617 | 67800  | 7.3573        |
+| 0.9631 | 67900  | 7.2843        |
+| 0.9645 | 68000  | 7.3528        |
+| 0.9660 | 68100  | 7.3296        |
+| 0.9674 | 68200  | 7.3433        |
+| 0.9688 | 68300  | 7.3529        |
+| 0.9702 | 68400  | 7.2929        |
+| 0.9716 | 68500  | 7.3289        |
+| 0.9730 | 68600  | 7.4613        |
+| 0.9745 | 68700  | 7.4588        |
+| 0.9759 | 68800  | 7.3326        |
+| 0.9773 | 68900  | 7.2601        |
+| 0.9787 | 69000  | 7.3314        |
+| 0.9801 | 69100  | 7.3782        |
+| 0.9816 | 69200  | 7.4445        |
+| 0.9830 | 69300  | 7.3459        |
+| 0.9844 | 69400  | 7.4281        |
+| 0.9858 | 69500  | 7.3766        |
+| 0.9872 | 69600  | 7.3094        |
+| 0.9887 | 69700  | 7.2895        |
+| 0.9901 | 69800  | 7.3939        |
+| 0.9915 | 69900  | 7.2774        |
+| 0.9929 | 70000  | 7.423         |
+| 0.9943 | 70100  | 7.3437        |
+| 0.9957 | 70200  | 7.3873        |
+| 0.9972 | 70300  | 7.4257        |
+| 0.9986 | 70400  | 7.3397        |
+| 1.0    | 70500  | 7.3163        |
+| 1.0014 | 70600  | 7.2886        |
+| 1.0028 | 70700  | 7.2694        |
+| 1.0043 | 70800  | 7.4706        |
+| 1.0057 | 70900  | 7.3052        |
+| 1.0071 | 71000  | 7.346         |
+| 1.0085 | 71100  | 7.3441        |
+| 1.0099 | 71200  | 7.4934        |
+| 1.0113 | 71300  | 7.3228        |
+| 1.0128 | 71400  | 7.3612        |
+| 1.0142 | 71500  | 7.3146        |
+| 1.0156 | 71600  | 7.3954        |
+| 1.0170 | 71700  | 7.4023        |
+| 1.0184 | 71800  | 7.4032        |
+| 1.0199 | 71900  | 7.3061        |
+| 1.0213 | 72000  | 7.406         |
+| 1.0227 | 72100  | 7.243         |
+| 1.0241 | 72200  | 7.3334        |
+| 1.0255 | 72300  | 7.389         |
+| 1.0270 | 72400  | 7.3977        |
+| 1.0284 | 72500  | 7.2887        |
+| 1.0298 | 72600  | 7.2825        |
+| 1.0312 | 72700  | 7.2907        |
+| 1.0326 | 72800  | 7.3244        |
+| 1.0340 | 72900  | 7.4266        |
+| 1.0355 | 73000  | 7.3328        |
+| 1.0369 | 73100  | 7.3503        |
+| 1.0383 | 73200  | 7.3473        |
+| 1.0397 | 73300  | 7.3024        |
+| 1.0411 | 73400  | 7.3337        |
+| 1.0426 | 73500  | 7.3857        |
+| 1.0440 | 73600  | 7.3282        |
+| 1.0454 | 73700  | 7.2501        |
+| 1.0468 | 73800  | 7.3272        |
+| 1.0482 | 73900  | 7.4248        |
+| 1.0496 | 74000  | 7.4097        |
+| 1.0511 | 74100  | 7.2995        |
+| 1.0525 | 74200  | 7.3457        |
+| 1.0539 | 74300  | 7.3362        |
+| 1.0553 | 74400  | 7.3313        |
+| 1.0567 | 74500  | 7.3367        |
+| 1.0582 | 74600  | 7.2944        |
+| 1.0596 | 74700  | 7.3885        |
+| 1.0610 | 74800  | 7.304         |
+| 1.0624 | 74900  | 7.351         |
+| 1.0638 | 75000  | 7.3737        |
+| 1.0652 | 75100  | 7.3723        |
+| 1.0667 | 75200  | 7.4372        |
+| 1.0681 | 75300  | 7.2352        |
+| 1.0695 | 75400  | 7.3445        |
+| 1.0709 | 75500  | 7.3433        |
+| 1.0723 | 75600  | 7.3618        |
+| 1.0738 | 75700  | 7.3856        |
+| 1.0752 | 75800  | 7.3556        |
+| 1.0766 | 75900  | 7.3787        |
+| 1.0780 | 76000  | 7.3154        |
+| 1.0794 | 76100  | 7.3646        |
+| 1.0809 | 76200  | 7.3179        |
+| 1.0823 | 76300  | 7.27          |
+| 1.0837 | 76400  | 7.2857        |
+| 1.0851 | 76500  | 7.3789        |
+| 1.0865 | 76600  | 7.2295        |
+| 1.0879 | 76700  | 7.3335        |
+| 1.0894 | 76800  | 7.3219        |
+| 1.0908 | 76900  | 7.3221        |
+| 1.0922 | 77000  | 7.4004        |
+| 1.0936 | 77100  | 7.3327        |
+| 1.0950 | 77200  | 7.3576        |
+| 1.0965 | 77300  | 7.3497        |
+| 1.0979 | 77400  | 7.4311        |
+| 1.0993 | 77500  | 7.2873        |
+| 1.1007 | 77600  | 7.3925        |
+| 1.1021 | 77700  | 7.256         |
+| 1.1035 | 77800  | 7.3704        |
+| 1.1050 | 77900  | 7.3758        |
+| 1.1064 | 78000  | 7.3813        |
+| 1.1078 | 78100  | 7.2789        |
+| 1.1092 | 78200  | 7.3123        |
+| 1.1106 | 78300  | 7.3435        |
+| 1.1121 | 78400  | 7.3492        |
+| 1.1135 | 78500  | 7.2986        |
+| 1.1149 | 78600  | 7.2842        |
+| 1.1163 | 78700  | 7.2871        |
+| 1.1177 | 78800  | 7.3348        |
+| 1.1191 | 78900  | 7.3022        |
+| 1.1206 | 79000  | 7.3909        |
+| 1.1220 | 79100  | 7.3           |
+| 1.1234 | 79200  | 7.415         |
+| 1.1248 | 79300  | 7.3909        |
+| 1.1262 | 79400  | 7.267         |
+| 1.1277 | 79500  | 7.3133        |
+| 1.1291 | 79600  | 7.3269        |
+| 1.1305 | 79700  | 7.2867        |
+| 1.1319 | 79800  | 7.3144        |
+| 1.1333 | 79900  | 7.3055        |
+| 1.1348 | 80000  | 7.4065        |
+| 1.1362 | 80100  | 7.3275        |
+| 1.1376 | 80200  | 7.3949        |
+| 1.1390 | 80300  | 7.3967        |
+| 1.1404 | 80400  | 7.2934        |
+| 1.1418 | 80500  | 7.3216        |
+| 1.1433 | 80600  | 7.3931        |
+| 1.1447 | 80700  | 7.375         |
+| 1.1461 | 80800  | 7.3385        |
+| 1.1475 | 80900  | 7.3662        |
+| 1.1489 | 81000  | 7.3692        |
+| 1.1504 | 81100  | 7.256         |
+| 1.1518 | 81200  | 7.286         |
+| 1.1532 | 81300  | 7.3671        |
+| 1.1546 | 81400  | 7.2735        |
+| 1.1560 | 81500  | 7.2919        |
+| 1.1574 | 81600  | 7.2323        |
+| 1.1589 | 81700  | 7.3409        |
+| 1.1603 | 81800  | 7.3005        |
+| 1.1617 | 81900  | 7.2951        |
+| 1.1631 | 82000  | 7.3804        |
+| 1.1645 | 82100  | 7.3677        |
+| 1.1660 | 82200  | 7.2892        |
+| 1.1674 | 82300  | 7.2788        |
+| 1.1688 | 82400  | 7.341         |
+| 1.1702 | 82500  | 7.3507        |
+| 1.1716 | 82600  | 7.4341        |
+| 1.1730 | 82700  | 7.2935        |
+| 1.1745 | 82800  | 7.3283        |
+| 1.1759 | 82900  | 7.3055        |
+| 1.1773 | 83000  | 7.2957        |
+| 1.1787 | 83100  | 7.287         |
+| 1.1801 | 83200  | 7.4028        |
+| 1.1816 | 83300  | 7.3504        |
+| 1.1830 | 83400  | 7.3796        |
+| 1.1844 | 83500  | 7.2504        |
+| 1.1858 | 83600  | 7.4789        |
+| 1.1872 | 83700  | 7.285         |
+| 1.1887 | 83800  | 7.3227        |
+| 1.1901 | 83900  | 7.296         |
+| 1.1915 | 84000  | 7.35          |
+| 1.1929 | 84100  | 7.2679        |
+| 1.1943 | 84200  | 7.333         |
+| 1.1957 | 84300  | 7.3939        |
+| 1.1972 | 84400  | 7.2432        |
+| 1.1986 | 84500  | 7.3441        |
+| 1.2    | 84600  | 7.2968        |
+| 1.2014 | 84700  | 7.2888        |
+| 1.2028 | 84800  | 7.3875        |
+| 1.2043 | 84900  | 7.3113        |
+| 1.2057 | 85000  | 7.2672        |
+| 1.2071 | 85100  | 7.2071        |
+| 1.2085 | 85200  | 7.3769        |
+| 1.2099 | 85300  | 7.3457        |
+| 1.2113 | 85400  | 7.2837        |
+| 1.2128 | 85500  | 7.296         |
+| 1.2142 | 85600  | 7.3517        |
+| 1.2156 | 85700  | 7.288         |
+| 1.2170 | 85800  | 7.319         |
+| 1.2184 | 85900  | 7.334         |
+| 1.2199 | 86000  | 7.256         |
+| 1.2213 | 86100  | 7.3348        |
+| 1.2227 | 86200  | 7.3671        |
+| 1.2241 | 86300  | 7.3484        |
+| 1.2255 | 86400  | 7.3802        |
+| 1.2270 | 86500  | 7.4165        |
+| 1.2284 | 86600  | 7.3639        |
+| 1.2298 | 86700  | 7.3104        |
+| 1.2312 | 86800  | 7.3015        |
+| 1.2326 | 86900  | 7.2736        |
+| 1.2340 | 87000  | 7.2733        |
+| 1.2355 | 87100  | 7.4366        |
+| 1.2369 | 87200  | 7.3102        |
+| 1.2383 | 87300  | 7.3026        |
+| 1.2397 | 87400  | 7.305         |
+| 1.2411 | 87500  | 7.2666        |
+| 1.2426 | 87600  | 7.3237        |
+| 1.2440 | 87700  | 7.2697        |
+| 1.2454 | 87800  | 7.3613        |
+| 1.2468 | 87900  | 7.2699        |
+| 1.2482 | 88000  | 7.3067        |
+| 1.2496 | 88100  | 7.4753        |
+| 1.2511 | 88200  | 7.3618        |
+| 1.2525 | 88300  | 7.3118        |
+| 1.2539 | 88400  | 7.3353        |
+| 1.2553 | 88500  | 7.3538        |
+| 1.2567 | 88600  | 7.3104        |
+| 1.2582 | 88700  | 7.366         |
+| 1.2596 | 88800  | 7.2524        |
+| 1.2610 | 88900  | 7.265         |
+| 1.2624 | 89000  | 7.3004        |
+| 1.2638 | 89100  | 7.284         |
+| 1.2652 | 89200  | 7.299         |
+| 1.2667 | 89300  | 7.2815        |
+| 1.2681 | 89400  | 7.3065        |
+| 1.2695 | 89500  | 7.2373        |
+| 1.2709 | 89600  | 7.2682        |
+| 1.2723 | 89700  | 7.3936        |
+| 1.2738 | 89800  | 7.1825        |
+| 1.2752 | 89900  | 7.3545        |
+| 1.2766 | 90000  | 7.2797        |
+| 1.2780 | 90100  | 7.317         |
+| 1.2794 | 90200  | 7.5024        |
+| 1.2809 | 90300  | 7.3189        |
+| 1.2823 | 90400  | 7.2759        |
+| 1.2837 | 90500  | 7.3078        |
+| 1.2851 | 90600  | 7.2482        |
+| 1.2865 | 90700  | 7.3459        |
+| 1.2879 | 90800  | 7.3925        |
+| 1.2894 | 90900  | 7.2866        |
+| 1.2908 | 91000  | 7.4288        |
+| 1.2922 | 91100  | 7.3249        |
+| 1.2936 | 91200  | 7.3204        |
+| 1.2950 | 91300  | 7.2658        |
+| 1.2965 | 91400  | 7.3711        |
+| 1.2979 | 91500  | 7.3255        |
+| 1.2993 | 91600  | 7.2959        |
+| 1.3007 | 91700  | 7.2292        |
+| 1.3021 | 91800  | 7.4353        |
+| 1.3035 | 91900  | 7.2374        |
+| 1.3050 | 92000  | 7.259         |
+| 1.3064 | 92100  | 7.2604        |
+| 1.3078 | 92200  | 7.3677        |
+| 1.3092 | 92300  | 7.3241        |
+| 1.3106 | 92400  | 7.2334        |
+| 1.3121 | 92500  | 7.3539        |
+| 1.3135 | 92600  | 7.4117        |
+| 1.3149 | 92700  | 7.4031        |
+| 1.3163 | 92800  | 7.274         |
+| 1.3177 | 92900  | 7.3847        |
+| 1.3191 | 93000  | 7.2802        |
+| 1.3206 | 93100  | 7.3394        |
+| 1.3220 | 93200  | 7.3119        |
+| 1.3234 | 93300  | 7.2213        |
+| 1.3248 | 93400  | 7.3513        |
+| 1.3262 | 93500  | 7.3586        |
+| 1.3277 | 93600  | 7.2746        |
+| 1.3291 | 93700  | 7.4017        |
+| 1.3305 | 93800  | 7.356         |
+| 1.3319 | 93900  | 7.2604        |
+| 1.3333 | 94000  | 7.3227        |
+| 1.3348 | 94100  | 7.2026        |
+| 1.3362 | 94200  | 7.326         |
+| 1.3376 | 94300  | 7.2314        |
+| 1.3390 | 94400  | 7.2839        |
+| 1.3404 | 94500  | 7.2059        |
+| 1.3418 | 94600  | 7.2935        |
+| 1.3433 | 94700  | 7.4495        |
+| 1.3447 | 94800  | 7.2253        |
+| 1.3461 | 94900  | 7.3141        |
+| 1.3475 | 95000  | 7.3476        |
+| 1.3489 | 95100  | 7.3569        |
+| 1.3504 | 95200  | 7.3161        |
+| 1.3518 | 95300  | 7.2797        |
+| 1.3532 | 95400  | 7.3661        |
+| 1.3546 | 95500  | 7.3076        |
+| 1.3560 | 95600  | 7.3267        |
+| 1.3574 | 95700  | 7.3302        |
+| 1.3589 | 95800  | 7.2281        |
+| 1.3603 | 95900  | 7.2545        |
+| 1.3617 | 96000  | 7.3984        |
+| 1.3631 | 96100  | 7.3806        |
+| 1.3645 | 96200  | 7.2286        |
+| 1.3660 | 96300  | 7.2284        |
+| 1.3674 | 96400  | 7.3688        |
+| 1.3688 | 96500  | 7.3673        |
+| 1.3702 | 96600  | 7.2965        |
+| 1.3716 | 96700  | 7.4199        |
+| 1.3730 | 96800  | 7.4159        |
+| 1.3745 | 96900  | 7.348         |
+| 1.3759 | 97000  | 7.3018        |
+| 1.3773 | 97100  | 7.3613        |
+| 1.3787 | 97200  | 7.3398        |
+| 1.3801 | 97300  | 7.3513        |
+| 1.3816 | 97400  | 7.288         |
+| 1.3830 | 97500  | 7.363         |
+| 1.3844 | 97600  | 7.2835        |
+| 1.3858 | 97700  | 7.2228        |
+| 1.3872 | 97800  | 7.333         |
+| 1.3887 | 97900  | 7.3071        |
+| 1.3901 | 98000  | 7.3316        |
+| 1.3915 | 98100  | 7.4089        |
+| 1.3929 | 98200  | 7.3146        |
+| 1.3943 | 98300  | 7.2549        |
+| 1.3957 | 98400  | 7.2979        |
+| 1.3972 | 98500  | 7.4236        |
+| 1.3986 | 98600  | 7.3343        |
+| 1.4    | 98700  | 7.3174        |
+| 1.4014 | 98800  | 7.3408        |
+| 1.4028 | 98900  | 7.208         |
+| 1.4043 | 99000  | 7.3943        |
+| 1.4057 | 99100  | 7.22          |
+| 1.4071 | 99200  | 7.3581        |
+| 1.4085 | 99300  | 7.299         |
+| 1.4099 | 99400  | 7.4252        |
+| 1.4113 | 99500  | 7.2181        |
+| 1.4128 | 99600  | 7.2297        |
+| 1.4142 | 99700  | 7.2893        |
+| 1.4156 | 99800  | 7.2747        |
+| 1.4170 | 99900  | 7.2606        |
+| 1.4184 | 100000 | 7.2651        |
+| 1.4199 | 100100 | 7.2562        |
+| 1.4213 | 100200 | 7.249         |
+| 1.4227 | 100300 | 7.3054        |
+| 1.4241 | 100400 | 7.3037        |
+| 1.4255 | 100500 | 7.3588        |
+| 1.4270 | 100600 | 7.3149        |
+| 1.4284 | 100700 | 7.3758        |
+| 1.4298 | 100800 | 7.3864        |
+| 1.4312 | 100900 | 7.4638        |
+| 1.4326 | 101000 | 7.2794        |
+| 1.4340 | 101100 | 7.2966        |
+| 1.4355 | 101200 | 7.3062        |
+| 1.4369 | 101300 | 7.2816        |
+| 1.4383 | 101400 | 7.2954        |
+| 1.4397 | 101500 | 7.3452        |
+| 1.4411 | 101600 | 7.2929        |
+| 1.4426 | 101700 | 7.2642        |
+| 1.4440 | 101800 | 7.3821        |
+| 1.4454 | 101900 | 7.3166        |
+| 1.4468 | 102000 | 7.2659        |
+| 1.4482 | 102100 | 7.3312        |
+| 1.4496 | 102200 | 7.2996        |
+| 1.4511 | 102300 | 7.3012        |
+| 1.4525 | 102400 | 7.3341        |
+| 1.4539 | 102500 | 7.2815        |
+| 1.4553 | 102600 | 7.2468        |
+| 1.4567 | 102700 | 7.3448        |
+| 1.4582 | 102800 | 7.2618        |
+| 1.4596 | 102900 | 7.2916        |
+| 1.4610 | 103000 | 7.3198        |
+| 1.4624 | 103100 | 7.2993        |
+| 1.4638 | 103200 | 7.238         |
+| 1.4652 | 103300 | 7.3266        |
+| 1.4667 | 103400 | 7.3953        |
+| 1.4681 | 103500 | 7.2839        |
+| 1.4695 | 103600 | 7.2833        |
+| 1.4709 | 103700 | 7.2805        |
+| 1.4723 | 103800 | 7.3553        |
+| 1.4738 | 103900 | 7.2881        |
+| 1.4752 | 104000 | 7.2375        |
+| 1.4766 | 104100 | 7.2558        |
+| 1.4780 | 104200 | 7.2436        |
+| 1.4794 | 104300 | 7.3178        |
+| 1.4809 | 104400 | 7.2821        |
+| 1.4823 | 104500 | 7.3493        |
+| 1.4837 | 104600 | 7.3474        |
+| 1.4851 | 104700 | 7.3064        |
+| 1.4865 | 104800 | 7.2802        |
+| 1.4879 | 104900 | 7.2726        |
+| 1.4894 | 105000 | 7.3221        |
+| 1.4908 | 105100 | 7.3383        |
+| 1.4922 | 105200 | 7.3353        |
+| 1.4936 | 105300 | 7.415         |
+| 1.4950 | 105400 | 7.3037        |
+| 1.4965 | 105500 | 7.3238        |
+| 1.4979 | 105600 | 7.2854        |
+| 1.4993 | 105700 | 7.4297        |
+| 1.5007 | 105800 | 7.2565        |
+| 1.5021 | 105900 | 7.3095        |
+| 1.5035 | 106000 | 7.2194        |
+| 1.5050 | 106100 | 7.3561        |
+| 1.5064 | 106200 | 7.3007        |
+| 1.5078 | 106300 | 7.298         |
+| 1.5092 | 106400 | 7.2221        |
+| 1.5106 | 106500 | 7.2762        |
+| 1.5121 | 106600 | 7.4222        |
+| 1.5135 | 106700 | 7.3456        |
+| 1.5149 | 106800 | 7.2946        |
+| 1.5163 | 106900 | 7.3141        |
+| 1.5177 | 107000 | 7.2073        |
+| 1.5191 | 107100 | 7.3115        |
+| 1.5206 | 107200 | 7.299         |
+| 1.5220 | 107300 | 7.2877        |
+| 1.5234 | 107400 | 7.3435        |
+| 1.5248 | 107500 | 7.2616        |
+| 1.5262 | 107600 | 7.239         |
+| 1.5277 | 107700 | 7.1948        |
+| 1.5291 | 107800 | 7.3348        |
+| 1.5305 | 107900 | 7.2626        |
+| 1.5319 | 108000 | 7.2106        |
+| 1.5333 | 108100 | 7.231         |
+| 1.5348 | 108200 | 7.4347        |
+| 1.5362 | 108300 | 7.2649        |
+| 1.5376 | 108400 | 7.2664        |
+| 1.5390 | 108500 | 7.4036        |
+| 1.5404 | 108600 | 7.3337        |
+| 1.5418 | 108700 | 7.2822        |
+| 1.5433 | 108800 | 7.3242        |
+| 1.5447 | 108900 | 7.1992        |
+| 1.5461 | 109000 | 7.3179        |
+| 1.5475 | 109100 | 7.3148        |
+| 1.5489 | 109200 | 7.2751        |
+| 1.5504 | 109300 | 7.2676        |
+| 1.5518 | 109400 | 7.2261        |
+| 1.5532 | 109500 | 7.2873        |
+| 1.5546 | 109600 | 7.2813        |
+| 1.5560 | 109700 | 7.3457        |
+| 1.5574 | 109800 | 7.2529        |
+| 1.5589 | 109900 | 7.2515        |
+| 1.5603 | 110000 | 7.1842        |
+| 1.5617 | 110100 | 7.2605        |
+| 1.5631 | 110200 | 7.2466        |
+| 1.5645 | 110300 | 7.3674        |
+| 1.5660 | 110400 | 7.3491        |
+| 1.5674 | 110500 | 7.3087        |
+| 1.5688 | 110600 | 7.4266        |
+| 1.5702 | 110700 | 7.3286        |
+| 1.5716 | 110800 | 7.3473        |
+| 1.5730 | 110900 | 7.3397        |
+| 1.5745 | 111000 | 7.3314        |
+| 1.5759 | 111100 | 7.3542        |
+| 1.5773 | 111200 | 7.3942        |
+| 1.5787 | 111300 | 7.1907        |
+| 1.5801 | 111400 | 7.2817        |
+| 1.5816 | 111500 | 7.3582        |
+| 1.5830 | 111600 | 7.2846        |
+| 1.5844 | 111700 | 7.2151        |
+| 1.5858 | 111800 | 7.2562        |
+| 1.5872 | 111900 | 7.3986        |
+| 1.5887 | 112000 | 7.2814        |
+| 1.5901 | 112100 | 7.2669        |
+| 1.5915 | 112200 | 7.3615        |
+| 1.5929 | 112300 | 7.3814        |
+| 1.5943 | 112400 | 7.3346        |
+| 1.5957 | 112500 | 7.3731        |
+| 1.5972 | 112600 | 7.4307        |
+| 1.5986 | 112700 | 7.3539        |
+| 1.6    | 112800 | 7.2197        |
+| 1.6014 | 112900 | 7.2688        |
+| 1.6028 | 113000 | 7.1784        |
+| 1.6043 | 113100 | 7.2101        |
+| 1.6057 | 113200 | 7.3872        |
+| 1.6071 | 113300 | 7.2263        |
+| 1.6085 | 113400 | 7.1674        |
+| 1.6099 | 113500 | 7.3255        |
+| 1.6113 | 113600 | 7.3325        |
+| 1.6128 | 113700 | 7.2839        |
+| 1.6142 | 113800 | 7.1871        |
+| 1.6156 | 113900 | 7.1871        |
+| 1.6170 | 114000 | 7.2528        |
+| 1.6184 | 114100 | 7.2189        |
+| 1.6199 | 114200 | 7.3384        |
+| 1.6213 | 114300 | 7.411         |
+| 1.6227 | 114400 | 7.1913        |
+| 1.6241 | 114500 | 7.2633        |
+| 1.6255 | 114600 | 7.3221        |
+| 1.6270 | 114700 | 7.4802        |
+| 1.6284 | 114800 | 7.2717        |
+| 1.6298 | 114900 | 7.195         |
+| 1.6312 | 115000 | 7.2621        |
+| 1.6326 | 115100 | 7.3467        |
+| 1.6340 | 115200 | 7.3489        |
+| 1.6355 | 115300 | 7.3048        |
+| 1.6369 | 115400 | 7.2595        |
+| 1.6383 | 115500 | 7.26          |
+| 1.6397 | 115600 | 7.3985        |
+| 1.6411 | 115700 | 7.2256        |
+| 1.6426 | 115800 | 7.2053        |
+| 1.6440 | 115900 | 7.2553        |
+| 1.6454 | 116000 | 7.3956        |
+| 1.6468 | 116100 | 7.1892        |
+| 1.6482 | 116200 | 7.2961        |
+| 1.6496 | 116300 | 7.2112        |
+| 1.6511 | 116400 | 7.2105        |
+| 1.6525 | 116500 | 7.3504        |
+| 1.6539 | 116600 | 7.2846        |
+| 1.6553 | 116700 | 7.2816        |
+| 1.6567 | 116800 | 7.3106        |
+| 1.6582 | 116900 | 7.3241        |
+| 1.6596 | 117000 | 7.2676        |
+| 1.6610 | 117100 | 7.3273        |
+| 1.6624 | 117200 | 7.2255        |
+| 1.6638 | 117300 | 7.1656        |
+| 1.6652 | 117400 | 7.2605        |
+| 1.6667 | 117500 | 7.3947        |
+| 1.6681 | 117600 | 7.2524        |
+| 1.6695 | 117700 | 7.2978        |
+| 1.6709 | 117800 | 7.2155        |
+| 1.6723 | 117900 | 7.2345        |
+| 1.6738 | 118000 | 7.309         |
+| 1.6752 | 118100 | 7.3104        |
+| 1.6766 | 118200 | 7.428         |
+| 1.6780 | 118300 | 7.2632        |
+| 1.6794 | 118400 | 7.2035        |
+| 1.6809 | 118500 | 7.2805        |
+| 1.6823 | 118600 | 7.2375        |
+| 1.6837 | 118700 | 7.2614        |
+| 1.6851 | 118800 | 7.213         |
+| 1.6865 | 118900 | 7.2832        |
+| 1.6879 | 119000 | 7.2919        |
+| 1.6894 | 119100 | 7.3301        |
+| 1.6908 | 119200 | 7.3109        |
+| 1.6922 | 119300 | 7.254         |
+| 1.6936 | 119400 | 7.2372        |
+| 1.6950 | 119500 | 7.2079        |
+| 1.6965 | 119600 | 7.2195        |
+| 1.6979 | 119700 | 7.2375        |
+| 1.6993 | 119800 | 7.295         |
+| 1.7007 | 119900 | 7.2692        |
+| 1.7021 | 120000 | 7.337         |
+| 1.7035 | 120100 | 7.4117        |
+| 1.7050 | 120200 | 7.2755        |
+| 1.7064 | 120300 | 7.2673        |
+| 1.7078 | 120400 | 7.2525        |
+| 1.7092 | 120500 | 7.2735        |
+| 1.7106 | 120600 | 7.2824        |
+| 1.7121 | 120700 | 7.2272        |
+| 1.7135 | 120800 | 7.2679        |
+| 1.7149 | 120900 | 7.3994        |
+| 1.7163 | 121000 | 7.258         |
+| 1.7177 | 121100 | 7.2336        |
+| 1.7191 | 121200 | 7.3152        |
+| 1.7206 | 121300 | 7.3595        |
+| 1.7220 | 121400 | 7.2357        |
+| 1.7234 | 121500 | 7.2982        |
+| 1.7248 | 121600 | 7.2672        |
+| 1.7262 | 121700 | 7.3124        |
+| 1.7277 | 121800 | 7.2843        |
+| 1.7291 | 121900 | 7.3037        |
+| 1.7305 | 122000 | 7.2205        |
+| 1.7319 | 122100 | 7.3037        |
+| 1.7333 | 122200 | 7.4012        |
+| 1.7348 | 122300 | 7.1974        |
+| 1.7362 | 122400 | 7.3394        |
+| 1.7376 | 122500 | 7.3588        |
+| 1.7390 | 122600 | 7.2486        |
+| 1.7404 | 122700 | 7.2903        |
+| 1.7418 | 122800 | 7.2629        |
+| 1.7433 | 122900 | 7.2352        |
+| 1.7447 | 123000 | 7.2867        |
+| 1.7461 | 123100 | 7.2724        |
+| 1.7475 | 123200 | 7.2743        |
+| 1.7489 | 123300 | 7.1701        |
+| 1.7504 | 123400 | 7.2767        |
+| 1.7518 | 123500 | 7.2658        |
+| 1.7532 | 123600 | 7.209         |
+| 1.7546 | 123700 | 7.4533        |
+| 1.7560 | 123800 | 7.2698        |
+| 1.7574 | 123900 | 7.3682        |
+| 1.7589 | 124000 | 7.2511        |
+| 1.7603 | 124100 | 7.3568        |
+| 1.7617 | 124200 | 7.1904        |
+| 1.7631 | 124300 | 7.3823        |
+| 1.7645 | 124400 | 7.3067        |
+| 1.7660 | 124500 | 7.2547        |
+| 1.7674 | 124600 | 7.231         |
+| 1.7688 | 124700 | 7.323         |
+| 1.7702 | 124800 | 7.1907        |
+| 1.7716 | 124900 | 7.3493        |
+| 1.7730 | 125000 | 7.3784        |
+| 1.7745 | 125100 | 7.3131        |
+| 1.7759 | 125200 | 7.2577        |
+| 1.7773 | 125300 | 7.2976        |
+| 1.7787 | 125400 | 7.2856        |
+| 1.7801 | 125500 | 7.1852        |
+| 1.7816 | 125600 | 7.2779        |
+| 1.7830 | 125700 | 7.3044        |
+| 1.7844 | 125800 | 7.2735        |
+| 1.7858 | 125900 | 7.2157        |
+| 1.7872 | 126000 | 7.256         |
+| 1.7887 | 126100 | 7.2939        |
+| 1.7901 | 126200 | 7.2297        |
+| 1.7915 | 126300 | 7.2221        |
+| 1.7929 | 126400 | 7.277         |
+| 1.7943 | 126500 | 7.203         |
+| 1.7957 | 126600 | 7.2193        |
+| 1.7972 | 126700 | 7.3848        |
+| 1.7986 | 126800 | 7.2891        |
+| 1.8    | 126900 | 7.1958        |
+| 1.8014 | 127000 | 7.316         |
+| 1.8028 | 127100 | 7.2108        |
+| 1.8043 | 127200 | 7.2194        |
+| 1.8057 | 127300 | 7.1937        |
+| 1.8071 | 127400 | 7.4097        |
+| 1.8085 | 127500 | 7.2644        |
+| 1.8099 | 127600 | 7.3223        |
+| 1.8113 | 127700 | 7.2851        |
+| 1.8128 | 127800 | 7.2893        |
+| 1.8142 | 127900 | 7.2451        |
+| 1.8156 | 128000 | 7.2803        |
+| 1.8170 | 128100 | 7.3891        |
+| 1.8184 | 128200 | 7.3642        |
+| 1.8199 | 128300 | 7.2644        |
+| 1.8213 | 128400 | 7.1783        |
+| 1.8227 | 128500 | 7.2531        |
+| 1.8241 | 128600 | 7.1973        |
+| 1.8255 | 128700 | 7.2198        |
+| 1.8270 | 128800 | 7.2278        |
+| 1.8284 | 128900 | 7.2631        |
+| 1.8298 | 129000 | 7.3625        |
+| 1.8312 | 129100 | 7.2299        |
+| 1.8326 | 129200 | 7.3305        |
+| 1.8340 | 129300 | 7.2672        |
+| 1.8355 | 129400 | 7.3255        |
+| 1.8369 | 129500 | 7.1958        |
+| 1.8383 | 129600 | 7.3867        |
+| 1.8397 | 129700 | 7.2442        |
+| 1.8411 | 129800 | 7.2788        |
+| 1.8426 | 129900 | 7.3084        |
+| 1.8440 | 130000 | 7.1875        |
+| 1.8454 | 130100 | 7.2022        |
+| 1.8468 | 130200 | 7.215         |
+| 1.8482 | 130300 | 7.2596        |
+| 1.8496 | 130400 | 7.296         |
+| 1.8511 | 130500 | 7.2243        |
+| 1.8525 | 130600 | 7.2402        |
+| 1.8539 | 130700 | 7.2287        |
+| 1.8553 | 130800 | 7.3283        |
+| 1.8567 | 130900 | 7.2389        |
+| 1.8582 | 131000 | 7.2126        |
+| 1.8596 | 131100 | 7.3993        |
+| 1.8610 | 131200 | 7.3284        |
+| 1.8624 | 131300 | 7.2295        |
+| 1.8638 | 131400 | 7.1896        |
+| 1.8652 | 131500 | 7.2439        |
+| 1.8667 | 131600 | 7.2155        |
+| 1.8681 | 131700 | 7.2517        |
+| 1.8695 | 131800 | 7.173         |
+| 1.8709 | 131900 | 7.223         |
+| 1.8723 | 132000 | 7.295         |
+| 1.8738 | 132100 | 7.2234        |
+| 1.8752 | 132200 | 7.2243        |
+| 1.8766 | 132300 | 7.4691        |
+| 1.8780 | 132400 | 7.2485        |
+| 1.8794 | 132500 | 7.2275        |
+| 1.8809 | 132600 | 7.2277        |
+| 1.8823 | 132700 | 7.3274        |
+| 1.8837 | 132800 | 7.4069        |
+| 1.8851 | 132900 | 7.4662        |
+| 1.8865 | 133000 | 7.5294        |
+| 1.8879 | 133100 | 7.297         |
+| 1.8894 | 133200 | 7.2931        |
+| 1.8908 | 133300 | 7.3336        |
+| 1.8922 | 133400 | 7.3819        |
+| 1.8936 | 133500 | 7.2764        |
+| 1.8950 | 133600 | 7.1839        |
+| 1.8965 | 133700 | 7.1937        |
+| 1.8979 | 133800 | 7.2698        |
+| 1.8993 | 133900 | 7.2531        |
+| 1.9007 | 134000 | 7.2547        |
+| 1.9021 | 134100 | 7.2672        |
+| 1.9035 | 134200 | 7.2277        |
+| 1.9050 | 134300 | 7.33          |
+| 1.9064 | 134400 | 7.2678        |
+| 1.9078 | 134500 | 7.3316        |
+| 1.9092 | 134600 | 7.332         |
+| 1.9106 | 134700 | 7.2112        |
+| 1.9121 | 134800 | 7.2481        |
+| 1.9135 | 134900 | 7.2636        |
+| 1.9149 | 135000 | 7.3524        |
+| 1.9163 | 135100 | 7.3855        |
+| 1.9177 | 135200 | 7.1926        |
+| 1.9191 | 135300 | 7.2504        |
+| 1.9206 | 135400 | 7.3069        |
+| 1.9220 | 135500 | 7.2681        |
+| 1.9234 | 135600 | 7.2553        |
+| 1.9248 | 135700 | 7.261         |
+| 1.9262 | 135800 | 7.3087        |
+| 1.9277 | 135900 | 7.2479        |
+| 1.9291 | 136000 | 7.2079        |
+| 1.9305 | 136100 | 7.2997        |
+| 1.9319 | 136200 | 7.2686        |
+| 1.9333 | 136300 | 7.2194        |
+| 1.9348 | 136400 | 7.3456        |
+| 1.9362 | 136500 | 7.1871        |
+| 1.9376 | 136600 | 7.2906        |
+| 1.9390 | 136700 | 7.1882        |
+| 1.9404 | 136800 | 7.2256        |
+| 1.9418 | 136900 | 7.2947        |
+| 1.9433 | 137000 | 7.258         |
+| 1.9447 | 137100 | 7.2708        |
+| 1.9461 | 137200 | 7.2111        |
+| 1.9475 | 137300 | 7.2576        |
+| 1.9489 | 137400 | 7.2733        |
+| 1.9504 | 137500 | 7.2649        |
+| 1.9518 | 137600 | 7.2232        |
+| 1.9532 | 137700 | 7.3346        |
+| 1.9546 | 137800 | 7.2479        |
+| 1.9560 | 137900 | 7.2057        |
+| 1.9574 | 138000 | 7.2544        |
+| 1.9589 | 138100 | 7.2448        |
+| 1.9603 | 138200 | 7.3557        |
+| 1.9617 | 138300 | 7.2125        |
+| 1.9631 | 138400 | 7.2608        |
+| 1.9645 | 138500 | 7.2987        |
+| 1.9660 | 138600 | 7.1828        |
+| 1.9674 | 138700 | 7.3248        |
+| 1.9688 | 138800 | 7.3219        |
+| 1.9702 | 138900 | 7.3457        |
+| 1.9716 | 139000 | 7.2512        |
+| 1.9730 | 139100 | 7.3012        |
+| 1.9745 | 139200 | 7.2978        |
+| 1.9759 | 139300 | 7.2322        |
+| 1.9773 | 139400 | 7.2618        |
+| 1.9787 | 139500 | 7.2518        |
+| 1.9801 | 139600 | 7.2333        |
+| 1.9816 | 139700 | 7.2854        |
+| 1.9830 | 139800 | 7.2021        |
+| 1.9844 | 139900 | 7.4261        |
+| 1.9858 | 140000 | 7.2381        |
+| 1.9872 | 140100 | 7.3018        |
+| 1.9887 | 140200 | 7.2407        |
+| 1.9901 | 140300 | 7.1686        |
+| 1.9915 | 140400 | 7.4311        |
+| 1.9929 | 140500 | 7.3061        |
+| 1.9943 | 140600 | 7.2009        |
+| 1.9957 | 140700 | 7.2942        |
+| 1.9972 | 140800 | 7.2231        |
+| 1.9986 | 140900 | 7.3834        |
+| 2.0    | 141000 | 7.2203        |
+
+</details>
+
+### Framework Versions
+- Python: 3.8.10
+- Sentence Transformers: 3.1.1
+- Transformers: 4.45.2
+- PyTorch: 2.4.1+cu118
+- Accelerate: 1.0.1
+- Datasets: 3.0.1
+- Tokenizers: 0.20.3
+
+## 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",
+}
+```
+
+#### CoSENTLoss
+```bibtex
+@online{kexuefm-8847,
+    title={CoSENT: A more efficient sentence vector scheme than Sentence-BERT},
+    author={Su Jianlin},
+    year={2022},
+    month={Jan},
+    url={https://kexue.fm/archives/8847},
+}
+```
+
+<!--
+## Glossary
+
+*Clearly define terms in order to be accessible across audiences.*
+-->
+
+<!--
+## Model Card Authors
+
+*Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.*
+-->
+
+<!--
+## Model Card Contact
+
+*Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.*
+-->

config.json

@@ -0,0 +1,26 @@
+{
+  "_name_or_path": "sentence-transformers/all-MiniLM-L6-v2",
+  "architectures": [
+    "BertModel"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 384,
+  "initializer_range": 0.02,
+  "intermediate_size": 1536,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 6,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "torch_dtype": "float32",
+  "transformers_version": "4.45.2",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

config_sentence_transformers.json

@@ -0,0 +1,10 @@
+{
+  "__version__": {
+    "sentence_transformers": "3.1.1",
+    "transformers": "4.45.2",
+    "pytorch": "2.4.1+cu118"
+  },
+  "prompts": {},
+  "default_prompt_name": null,
+  "similarity_fn_name": null
+}

model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:af10f7be8f0cf5b2a3ef7ac8195327806ef1eeb0dadf67adc80748ad987d9de8
+size 90864192

modules.json

@@ -0,0 +1,20 @@
+[
+  {
+    "idx": 0,
+    "name": "0",
+    "path": "",
+    "type": "sentence_transformers.models.Transformer"
+  },
+  {
+    "idx": 1,
+    "name": "1",
+    "path": "1_Pooling",
+    "type": "sentence_transformers.models.Pooling"
+  },
+  {
+    "idx": 2,
+    "name": "2",
+    "path": "2_Normalize",
+    "type": "sentence_transformers.models.Normalize"
+  }
+]

sentence_bert_config.json

@@ -0,0 +1,4 @@
+{
+  "max_seq_length": 256,
+  "do_lower_case": false
+}

special_tokens_map.json

@@ -0,0 +1,37 @@
+{
+  "cls_token": {
+    "content": "[CLS]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "mask_token": {
+    "content": "[MASK]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "[PAD]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "sep_token": {
+    "content": "[SEP]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "[UNK]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer_config.json

@@ -0,0 +1,64 @@
+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "[PAD]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "100": {
+      "content": "[UNK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "101": {
+      "content": "[CLS]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "102": {
+      "content": "[SEP]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "103": {
+      "content": "[MASK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "clean_up_tokenization_spaces": false,
+  "cls_token": "[CLS]",
+  "do_basic_tokenize": true,
+  "do_lower_case": true,
+  "mask_token": "[MASK]",
+  "max_length": 128,
+  "model_max_length": 256,
+  "never_split": null,
+  "pad_to_multiple_of": null,
+  "pad_token": "[PAD]",
+  "pad_token_type_id": 0,
+  "padding_side": "right",
+  "sep_token": "[SEP]",
+  "stride": 0,
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "truncation_side": "right",
+  "truncation_strategy": "longest_first",
+  "unk_token": "[UNK]"
+}