cyberbabooshka/MNLP_M3_document_encoder
09
1---2tags:3- sentence-transformers4- sentence-similarity5- feature-extraction6- generated_from_trainer7- dataset_size:17608- loss:MultipleNegativesRankingLoss9base_model: WhereIsAI/UAE-Large-V110widget:11- source_sentence: What is the relationship between the x- and y-coordinates in a12 linear relationship, and how can this relationship be represented visually on13 a graph?14 sentences:15 - '"A linear relationship is a relationship between variables such that when plotted16 on a coordinate plane, the points lie on a line." Additionally, "You can think17 of a line, then, as a collection of an infinite number of individual points that18 share the same mathematical relationship."'19 - '"A ''model'' is a situation-specific description of a phenomenon based on a theory,20 that allows us to make a specific prediction." and "In physics, it is particularly21 important to distinguish between these two terms. A model provides an immediate22 understanding of something based on a theory."'23 - '"Use capital letters to denote sets, $A,B, C, X, Y$ etc. [...] if you stick with24 these conventions people reading your work (including the person marking your25 exams) will know — ''Oh $A$ is that set they are talking about'' and ''$a$ is26 an element of that set.''"'27- source_sentence: What factors influence whether thin-film interference results in28 constructive or destructive interference?29 sentences:30 - '"For nonrelativistic velocities, an observer moving along at the same velocity31 as an Ohmic conductor measures the usual Ohm''s law in his reference frame, $\textbf{J}_{f}''32 = \sigma \textbf{E}''$... the current density in all inertial frames is the same33 so that (3) in (4) gives us the generalized Ohm''s law as $\textbf{J}_{f}'' =34 \textbf{J}_{f} = \sigma (\textbf{E} + \textbf{v} \times \textbf{B})$ where v is35 the velocity of the conductor."'36 - '"Thin-film interference thus depends on film thickness, the wavelength of light,37 and the refractive indices."'38 - '"A summary of the properties of concave mirrors is shown below: • converging39 • real image • inverted • image in front of mirror. A summary of the properties40 of convex mirrors is shown below: • diverging • virtual image • upright • image41 behind mirror."'42- source_sentence: How do non-conservative forces affect the total energy change in43 a system undergoing an irreversible process?44 sentences:45 - '"Energy is conserved but some mechanical energy has been transferred into nonrecoverable46 energy $W_{\mathrm{nc}}$. We shall refer to processes in which there is non-zero47 nonrecoverable energy as irreversible processes."'48 - '"Hamilton’s equations give $2s$ first-order differential equations for $p_{k},q_{k}$49 for each of the $s=n-m$ degrees of freedom. Lagrange’s equations give $s$ second-order50 differential equations for the $s$ independent generalized coordinates $q_{k},\dot{q}_{k}."'51 - '"Determine what happens as $\Delta x$ approaches 0."'52- source_sentence: What are the conditions under which a mutant virus is likely to53 replace a wildtype virus in a population, according to the SIR model of disease54 dynamics?55 sentences:56 - '"In the limit of high Reynolds number, viscosity disappears from the problem57 and the drag force should not depend on viscosity. This reasoning contains several58 subtle untruths, yet its conclusion is mostly correct. ... To make \( F \) independent59 of viscosity, \( F \) must be independent of Reynolds number!"'60 - '"A more mathematically rigorous name would be the renormalization monoid."'61 - '"I^{\prime}$ increases exponentially if $\frac{\beta^{\prime}(d+c+\gamma)}{\beta}-\left(d+c^{\prime}+\gamma^{\prime}\right)>0$62 or after some elementary algebra, $\frac{\beta^{\prime}}{d+c^{\prime}+\gamma^{\prime}}>\frac{\beta}{d+c+\gamma}$."63 Additionally, "our result (4.6.8) suggests that endemic viruses (or other microorganisms)64 will tend to evolve (i) to be more easily transmitted between people $\left(\beta^{\prime}>\beta\right)65 ;$ (ii) to make people sick longer $\left(\gamma^{\prime}<\gamma\right)$, and;66 (iii) to be less deadly $c^{\prime}<c$."'67- source_sentence: What is the relationship between the smallest perturbation of a68 matrix and its rank, as established in theorems regarding matrix perturbations?69 sentences:70 - '"Suppose $A \in C^{m \times n}$ has full column rank (= n). Then $\min _{\Delta71 \in \mathbb{C}^{m \times n}}\left\{\|\Delta\|_{2} \mid A+\Delta \text { has rank72 }<n\right\}=\sigma_{n}(A)$."'73 - '"Complementary angles have measures that add up to 90 degrees."'74 - '"If a beam of light enters and then exits the elevator, the observer on Earth75 and the one accelerating in empty space must observe the same thing, since they76 cannot distinguish between being on Earth or accelerating in space. The observer77 in space, who is accelerating, will observe that the beam of light bends as it78 crosses the elevator... that means that if the path of a beam of light is curved79 near Earth, it must be because space itself is curved in the presence of a gravitational80 field!"'81pipeline_tag: sentence-similarity82library_name: sentence-transformers83metrics:84- cosine_accuracy@185- cosine_accuracy@386- cosine_accuracy@587- cosine_accuracy@1088- cosine_precision@189- cosine_precision@390- cosine_precision@591- cosine_precision@1092- cosine_recall@193- cosine_recall@394- cosine_recall@595- cosine_recall@1096- cosine_ndcg@1097- cosine_mrr@1098- cosine_map@10099model-index:100- name: SentenceTransformer based on WhereIsAI/UAE-Large-V1101 results:102 - task:103 type: information-retrieval104 name: Information Retrieval105 dataset:106 name: eval107 type: eval108 metrics:109 - type: cosine_accuracy@1110 value: 0.6142857142857143111 name: Cosine Accuracy@1112 - type: cosine_accuracy@3113 value: 0.7357142857142858114 name: Cosine Accuracy@3115 - type: cosine_accuracy@5116 value: 0.7833333333333333117 name: Cosine Accuracy@5118 - type: cosine_accuracy@10119 value: 0.8380952380952381120 name: Cosine Accuracy@10121 - type: cosine_precision@1122 value: 0.6142857142857143123 name: Cosine Precision@1124 - type: cosine_precision@3125 value: 0.24523809523809523126 name: Cosine Precision@3127 - type: cosine_precision@5128 value: 0.15666666666666665129 name: Cosine Precision@5130 - type: cosine_precision@10131 value: 0.08380952380952378132 name: Cosine Precision@10133 - type: cosine_recall@1134 value: 0.6142857142857143135 name: Cosine Recall@1136 - type: cosine_recall@3137 value: 0.7357142857142858138 name: Cosine Recall@3139 - type: cosine_recall@5140 value: 0.7833333333333333141 name: Cosine Recall@5142 - type: cosine_recall@10143 value: 0.8380952380952381144 name: Cosine Recall@10145 - type: cosine_ndcg@10146 value: 0.7234956246301203147 name: Cosine Ndcg@10148 - type: cosine_mrr@10149 value: 0.6871305744520029150 name: Cosine Mrr@10151 - type: cosine_map@100152 value: 0.6925322242948972153 name: Cosine Map@100154---155 156# SentenceTransformer based on WhereIsAI/UAE-Large-V1157 158This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [WhereIsAI/UAE-Large-V1](https://huggingface.co/WhereIsAI/UAE-Large-V1). It maps sentences & paragraphs to a 1024-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more.159 160## Model Details161 162### Model Description163- **Model Type:** Sentence Transformer164- **Base model:** [WhereIsAI/UAE-Large-V1](https://huggingface.co/WhereIsAI/UAE-Large-V1) <!-- at revision f4264cd240f4e46a527f9f57a70cda6c2a12d248 -->165- **Maximum Sequence Length:** 512 tokens166- **Output Dimensionality:** 1024 dimensions167- **Similarity Function:** Cosine Similarity168<!-- - **Training Dataset:** Unknown -->169<!-- - **Language:** Unknown -->170<!-- - **License:** Unknown -->171 172### Model Sources173 174- **Documentation:** [Sentence Transformers Documentation](https://sbert.net)175- **Repository:** [Sentence Transformers on GitHub](https://github.com/UKPLab/sentence-transformers)176- **Hugging Face:** [Sentence Transformers on Hugging Face](https://huggingface.co/models?library=sentence-transformers)177 178### Full Model Architecture179 180```181SentenceTransformer(182 (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel 183 (1): Pooling({'word_embedding_dimension': 1024, '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})184)185```186 187## Usage188 189### Direct Usage (Sentence Transformers)190 191First install the Sentence Transformers library:192 193```bash194pip install -U sentence-transformers195```196 197Then you can load this model and run inference.198```python199from sentence_transformers import SentenceTransformer200 201# Download from the 🤗 Hub202model = SentenceTransformer("cyberbabooshka/uae_large_ft1")203# Run inference204sentences = [205 'What is the relationship between the smallest perturbation of a matrix and its rank, as established in theorems regarding matrix perturbations?',206 '"Suppose $A \\in C^{m \\times n}$ has full column rank (= n). Then $\\min _{\\Delta \\in \\mathbb{C}^{m \\times n}}\\left\\{\\|\\Delta\\|_{2} \\mid A+\\Delta \\text { has rank }<n\\right\\}=\\sigma_{n}(A)$."',207 '"If a beam of light enters and then exits the elevator, the observer on Earth and the one accelerating in empty space must observe the same thing, since they cannot distinguish between being on Earth or accelerating in space. The observer in space, who is accelerating, will observe that the beam of light bends as it crosses the elevator... that means that if the path of a beam of light is curved near Earth, it must be because space itself is curved in the presence of a gravitational field!"',208]209embeddings = model.encode(sentences)210print(embeddings.shape)211# [3, 1024]212 213# Get the similarity scores for the embeddings214similarities = model.similarity(embeddings, embeddings)215print(similarities.shape)216# [3, 3]217```218 219<!--220### Direct Usage (Transformers)221 222<details><summary>Click to see the direct usage in Transformers</summary>223 224</details>225-->226 227<!--228### Downstream Usage (Sentence Transformers)229 230You can finetune this model on your own dataset.231 232<details><summary>Click to expand</summary>233 234</details>235-->236 237<!--238### Out-of-Scope Use239 240*List how the model may foreseeably be misused and address what users ought not to do with the model.*241-->242 243## Evaluation244 245### Metrics246 247#### Information Retrieval248 249* Dataset: `eval`250* Evaluated with [<code>InformationRetrievalEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.InformationRetrievalEvaluator)251 252| Metric | Value |253|:--------------------|:-----------|254| cosine_accuracy@1 | 0.6143 |255| cosine_accuracy@3 | 0.7357 |256| cosine_accuracy@5 | 0.7833 |257| cosine_accuracy@10 | 0.8381 |258| cosine_precision@1 | 0.6143 |259| cosine_precision@3 | 0.2452 |260| cosine_precision@5 | 0.1567 |261| cosine_precision@10 | 0.0838 |262| cosine_recall@1 | 0.6143 |263| cosine_recall@3 | 0.7357 |264| cosine_recall@5 | 0.7833 |265| cosine_recall@10 | 0.8381 |266| **cosine_ndcg@10** | **0.7235** |267| cosine_mrr@10 | 0.6871 |268| cosine_map@100 | 0.6925 |269 270<!--271## Bias, Risks and Limitations272 273*What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.*274-->275 276<!--277### Recommendations278 279*What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*280-->281 282## Training Details283 284### Training Dataset285 286#### Unnamed Dataset287 288* Size: 1,760 training samples289* Columns: <code>anchor</code> and <code>positive</code>290* Approximate statistics based on the first 1000 samples:291 | | anchor | positive |292 |:--------|:----------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|293 | type | string | string |294 | details | <ul><li>min: 9 tokens</li><li>mean: 24.87 tokens</li><li>max: 70 tokens</li></ul> | <ul><li>min: 11 tokens</li><li>mean: 68.37 tokens</li><li>max: 500 tokens</li></ul> |295* Samples:296 | anchor | positive |297 |:---------------------------------------------------------------------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|298 | <code>How is a proper coloring of a graph defined in the context of vertices and edges?</code> | <code>"A coloring is called proper if for each edge joining two distinct vertices, the two vertices it joins have different colors."</code> |299 | <code>What is the relationship between the first excited state of the box model and the p orbitals in a hydrogen atom?</code> | <code>"The p orbitals are similar to the first excited state of the box, i.e. $(n_{x},n_{y},n_{z})=(2,1,1)$ is similar to a $p_{x}$ orbital, $(n_{x},n_{y},n_{z})=(1,2,1)$ is similar to a $p_{y}$ orbital and $(n_{x},n_{y},n_{z})=(1,1,2)$ is similar to a $p_{z}$ orbital."</code> |300 | <code>How can the behavior of the derivative \( f'(x) \) indicate the presence of a local maximum or minimum at a critical point \( x=a \)?</code> | <code>"If there is a local maximum when \( x=a \), the function must be lower near \( x=a \) than it is right at \( x=a \). If the derivative exists near \( x=a \), this means \( f'(x)>0 \) when \( x \) is near \( a \) and \( x < a \), because the function must 'slope up' just to the left of \( a \). Similarly, \( f'(x) < 0 \) when \( x \) is near \( a \) and \( x>a \), because \( f \) slopes down from the local maximum as we move to the right. Using the same reasoning, if there is a local minimum at \( x=a \), the derivative of \( f \) must be negative just to the left of \( a \) and positive just to the right."</code> |301* Loss: [<code>MultipleNegativesRankingLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#multiplenegativesrankingloss) with these parameters:302 ```json303 {304 "scale": 20.0,305 "similarity_fct": "cos_sim"306 }307 ```308 309### Evaluation Dataset310 311#### Unnamed Dataset312 313* Size: 420 evaluation samples314* Columns: <code>anchor</code> and <code>positive</code>315* Approximate statistics based on the first 420 samples:316 | | anchor | positive |317 |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|318 | type | string | string |319 | details | <ul><li>min: 12 tokens</li><li>mean: 24.97 tokens</li><li>max: 66 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 68.52 tokens</li><li>max: 452 tokens</li></ul> |320* Samples:321 | anchor | positive |322 |:------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|323 | <code>What are the two central classes mentioned in the FileSystem framework and what do they represent?</code> | <code>"The class `FileReference` is the most important entry point to the framework." and "FileSystem is a powerful and elegant library to manipulate files."</code> |324 | <code>What is the significance of Turing's work in the context of PDE-based models for self-organization of complex systems?</code> | <code>"Turing’s monumental work on the chemical basis of morphogenesis played an important role in igniting researchers’ attention to the PDE-based continuous field models as a mathematical framework to study self-organization of complex systems."</code> |325 | <code>What are the two options for reducing accelerations as discussed in the passage?</code> | <code>"From the above definitions we see that there are really two options for reducing accelerations. We can reduce the amount that velocity changes, or we can increase the time over which the velocity changes (or both)."</code> |326* Loss: [<code>MultipleNegativesRankingLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#multiplenegativesrankingloss) with these parameters:327 ```json328 {329 "scale": 20.0,330 "similarity_fct": "cos_sim"331 }332 ```333 334### Training Hyperparameters335#### Non-Default Hyperparameters336 337- `eval_strategy`: epoch338- `per_device_train_batch_size`: 16339- `per_device_eval_batch_size`: 16340- `learning_rate`: 2e-05341- `weight_decay`: 0.05342- `num_train_epochs`: 10343- `warmup_ratio`: 0.1344- `fp16`: True345- `eval_on_start`: True346 347#### All Hyperparameters348<details><summary>Click to expand</summary>349 350- `overwrite_output_dir`: False351- `do_predict`: False352- `eval_strategy`: epoch353- `prediction_loss_only`: True354- `per_device_train_batch_size`: 16355- `per_device_eval_batch_size`: 16356- `per_gpu_train_batch_size`: None357- `per_gpu_eval_batch_size`: None358- `gradient_accumulation_steps`: 1359- `eval_accumulation_steps`: None360- `torch_empty_cache_steps`: None361- `learning_rate`: 2e-05362- `weight_decay`: 0.05363- `adam_beta1`: 0.9364- `adam_beta2`: 0.999365- `adam_epsilon`: 1e-08366- `max_grad_norm`: 1.0367- `num_train_epochs`: 10368- `max_steps`: -1369- `lr_scheduler_type`: linear370- `lr_scheduler_kwargs`: {}371- `warmup_ratio`: 0.1372- `warmup_steps`: 0373- `log_level`: passive374- `log_level_replica`: warning375- `log_on_each_node`: True376- `logging_nan_inf_filter`: True377- `save_safetensors`: True378- `save_on_each_node`: False379- `save_only_model`: False380- `restore_callback_states_from_checkpoint`: False381- `no_cuda`: False382- `use_cpu`: False383- `use_mps_device`: False384- `seed`: 42385- `data_seed`: None386- `jit_mode_eval`: False387- `use_ipex`: False388- `bf16`: False389- `fp16`: True390- `fp16_opt_level`: O1391- `half_precision_backend`: auto392- `bf16_full_eval`: False393- `fp16_full_eval`: False394- `tf32`: None395- `local_rank`: 0396- `ddp_backend`: None397- `tpu_num_cores`: None398- `tpu_metrics_debug`: False399- `debug`: []400- `dataloader_drop_last`: False401- `dataloader_num_workers`: 0402- `dataloader_prefetch_factor`: None403- `past_index`: -1404- `disable_tqdm`: False405- `remove_unused_columns`: True406- `label_names`: None407- `load_best_model_at_end`: False408- `ignore_data_skip`: False409- `fsdp`: []410- `fsdp_min_num_params`: 0411- `fsdp_config`: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}412- `fsdp_transformer_layer_cls_to_wrap`: None413- `accelerator_config`: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None}414- `deepspeed`: None415- `label_smoothing_factor`: 0.0416- `optim`: adamw_torch417- `optim_args`: None418- `adafactor`: False419- `group_by_length`: False420- `length_column_name`: length421- `ddp_find_unused_parameters`: None422- `ddp_bucket_cap_mb`: None423- `ddp_broadcast_buffers`: False424- `dataloader_pin_memory`: True425- `dataloader_persistent_workers`: False426- `skip_memory_metrics`: True427- `use_legacy_prediction_loop`: False428- `push_to_hub`: False429- `resume_from_checkpoint`: None430- `hub_model_id`: None431- `hub_strategy`: every_save432- `hub_private_repo`: None433- `hub_always_push`: False434- `gradient_checkpointing`: False435- `gradient_checkpointing_kwargs`: None436- `include_inputs_for_metrics`: False437- `include_for_metrics`: []438- `eval_do_concat_batches`: True439- `fp16_backend`: auto440- `push_to_hub_model_id`: None441- `push_to_hub_organization`: None442- `mp_parameters`: 443- `auto_find_batch_size`: False444- `full_determinism`: False445- `torchdynamo`: None446- `ray_scope`: last447- `ddp_timeout`: 1800448- `torch_compile`: False449- `torch_compile_backend`: None450- `torch_compile_mode`: None451- `include_tokens_per_second`: False452- `include_num_input_tokens_seen`: False453- `neftune_noise_alpha`: None454- `optim_target_modules`: None455- `batch_eval_metrics`: False456- `eval_on_start`: True457- `use_liger_kernel`: False458- `eval_use_gather_object`: False459- `average_tokens_across_devices`: False460- `prompts`: None461- `batch_sampler`: batch_sampler462- `multi_dataset_batch_sampler`: proportional463 464</details>465 466### Training Logs467<details><summary>Click to expand</summary>468 469| Epoch | Step | Training Loss | Validation Loss | eval_cosine_ndcg@10 |470|:------:|:----:|:-------------:|:---------------:|:-------------------:|471| 0 | 0 | - | 0.0971 | 0.6824 |472| 0.0091 | 1 | 0.1198 | - | - |473| 0.0182 | 2 | 0.0787 | - | - |474| 0.0273 | 3 | 0.0614 | - | - |475| 0.0364 | 4 | 0.138 | - | - |476| 0.0455 | 5 | 0.1204 | - | - |477| 0.0545 | 6 | 0.1885 | - | - |478| 0.0636 | 7 | 0.0475 | - | - |479| 0.0727 | 8 | 0.1358 | - | - |480| 0.0818 | 9 | 0.1666 | - | - |481| 0.0909 | 10 | 0.0737 | - | - |482| 0.1 | 11 | 0.0997 | - | - |483| 0.1091 | 12 | 0.0795 | - | - |484| 0.1182 | 13 | 0.1071 | - | - |485| 0.1273 | 14 | 0.1224 | - | - |486| 0.1364 | 15 | 0.0499 | - | - |487| 0.1455 | 16 | 0.0806 | - | - |488| 0.1545 | 17 | 0.0353 | - | - |489| 0.1636 | 18 | 0.0542 | - | - |490| 0.1727 | 19 | 0.0412 | - | - |491| 0.1818 | 20 | 0.1375 | - | - |492| 0.1909 | 21 | 0.1124 | - | - |493| 0.2 | 22 | 0.0992 | - | - |494| 0.2091 | 23 | 0.0285 | - | - |495| 0.2182 | 24 | 0.0337 | - | - |496| 0.2273 | 25 | 0.0737 | - | - |497| 0.2364 | 26 | 0.2011 | - | - |498| 0.2455 | 27 | 0.0241 | - | - |499| 0.2545 | 28 | 0.1319 | - | - |500| 0.2636 | 29 | 0.0104 | - | - |501| 0.2727 | 30 | 0.0162 | - | - |502| 0.2818 | 31 | 0.3061 | - | - |503| 0.2909 | 32 | 0.0422 | - | - |504| 0.3 | 33 | 0.1893 | - | - |505| 0.3091 | 34 | 0.0207 | - | - |506| 0.3182 | 35 | 0.0744 | - | - |507| 0.3273 | 36 | 0.0246 | - | - |508| 0.3364 | 37 | 0.0079 | - | - |509| 0.3455 | 38 | 0.0256 | - | - |510| 0.3545 | 39 | 0.0224 | - | - |511| 0.3636 | 40 | 0.0151 | - | - |512| 0.3727 | 41 | 0.0738 | - | - |513| 0.3818 | 42 | 0.0239 | - | - |514| 0.3909 | 43 | 0.0169 | - | - |515| 0.4 | 44 | 0.0152 | - | - |516| 0.4091 | 45 | 0.0244 | - | - |517| 0.4182 | 46 | 0.1708 | - | - |518| 0.4273 | 47 | 0.0146 | - | - |519| 0.4364 | 48 | 0.1367 | - | - |520| 0.4455 | 49 | 0.049 | - | - |521| 0.4545 | 50 | 0.0211 | - | - |522| 0.4636 | 51 | 0.0135 | - | - |523| 0.4727 | 52 | 0.0668 | - | - |524| 0.4818 | 53 | 0.087 | - | - |525| 0.4909 | 54 | 0.0046 | - | - |526| 0.5 | 55 | 0.0032 | - | - |527| 0.5091 | 56 | 0.0133 | - | - |528| 0.5182 | 57 | 0.0109 | - | - |529| 0.5273 | 58 | 0.0396 | - | - |530| 0.5364 | 59 | 0.0291 | - | - |531| 0.5455 | 60 | 0.0299 | - | - |532| 0.5545 | 61 | 0.0134 | - | - |533| 0.5636 | 62 | 0.0135 | - | - |534| 0.5727 | 63 | 0.0049 | - | - |535| 0.5818 | 64 | 0.0199 | - | - |536| 0.5909 | 65 | 0.1533 | - | - |537| 0.6 | 66 | 0.3639 | - | - |538| 0.6091 | 67 | 0.0652 | - | - |539| 0.6182 | 68 | 0.0315 | - | - |540| 0.6273 | 69 | 0.0403 | - | - |541| 0.6364 | 70 | 0.011 | - | - |542| 0.6455 | 71 | 0.0265 | - | - |543| 0.6545 | 72 | 0.1146 | - | - |544| 0.6636 | 73 | 0.0932 | - | - |545| 0.6727 | 74 | 0.0234 | - | - |546| 0.6818 | 75 | 0.0581 | - | - |547| 0.6909 | 76 | 0.0132 | - | - |548| 0.7 | 77 | 0.1183 | - | - |549| 0.7091 | 78 | 0.0913 | - | - |550| 0.7182 | 79 | 0.0262 | - | - |551| 0.7273 | 80 | 0.0262 | - | - |552| 0.7364 | 81 | 0.0159 | - | - |553| 0.7455 | 82 | 0.0407 | - | - |554| 0.7545 | 83 | 0.0294 | - | - |555| 0.7636 | 84 | 0.0567 | - | - |556| 0.7727 | 85 | 0.0959 | - | - |557| 0.7818 | 86 | 0.033 | - | - |558| 0.7909 | 87 | 0.0234 | - | - |559| 0.8 | 88 | 0.0088 | - | - |560| 0.8091 | 89 | 0.0249 | - | - |561| 0.8182 | 90 | 0.0276 | - | - |562| 0.8273 | 91 | 0.0936 | - | - |563| 0.8364 | 92 | 0.0067 | - | - |564| 0.8455 | 93 | 0.0064 | - | - |565| 0.8545 | 94 | 0.0654 | - | - |566| 0.8636 | 95 | 0.0048 | - | - |567| 0.8727 | 96 | 0.0087 | - | - |568| 0.8818 | 97 | 0.0115 | - | - |569| 0.8909 | 98 | 0.0092 | - | - |570| 0.9 | 99 | 0.0514 | - | - |571| 0.9091 | 100 | 0.1856 | - | - |572| 0.9182 | 101 | 0.0364 | - | - |573| 0.9273 | 102 | 0.0455 | - | - |574| 0.9364 | 103 | 0.0057 | - | - |575| 0.9455 | 104 | 0.0038 | - | - |576| 0.9545 | 105 | 0.0209 | - | - |577| 0.9636 | 106 | 0.0247 | - | - |578| 0.9727 | 107 | 0.0735 | - | - |579| 0.9818 | 108 | 0.004 | - | - |580| 0.9909 | 109 | 0.0174 | - | - |581| 1.0 | 110 | 0.018 | 0.0282 | 0.7093 |582| 1.0091 | 111 | 0.0187 | - | - |583| 1.0182 | 112 | 0.0116 | - | - |584| 1.0273 | 113 | 0.0043 | - | - |585| 1.0364 | 114 | 0.0059 | - | - |586| 1.0455 | 115 | 0.0067 | - | - |587| 1.0545 | 116 | 0.0093 | - | - |588| 1.0636 | 117 | 0.0821 | - | - |589| 1.0727 | 118 | 0.0097 | - | - |590| 1.0818 | 119 | 0.0141 | - | - |591| 1.0909 | 120 | 0.0202 | - | - |592| 1.1 | 121 | 0.0034 | - | - |593| 1.1091 | 122 | 0.0025 | - | - |594| 1.1182 | 123 | 0.006 | - | - |595| 1.1273 | 124 | 0.004 | - | - |596| 1.1364 | 125 | 0.003 | - | - |597| 1.1455 | 126 | 0.0399 | - | - |598| 1.1545 | 127 | 0.0026 | - | - |599| 1.1636 | 128 | 0.0043 | - | - |600| 1.1727 | 129 | 0.1317 | - | - |601| 1.1818 | 130 | 0.0024 | - | - |602| 1.1909 | 131 | 0.0027 | - | - |603| 1.2 | 132 | 0.076 | - | - |604| 1.2091 | 133 | 0.0302 | - | - |605| 1.2182 | 134 | 0.0026 | - | - |606| 1.2273 | 135 | 0.1611 | - | - |607| 1.2364 | 136 | 0.0413 | - | - |608| 1.2455 | 137 | 0.0118 | - | - |609| 1.2545 | 138 | 0.0042 | - | - |610| 1.2636 | 139 | 0.0401 | - | - |611| 1.2727 | 140 | 0.0036 | - | - |612| 1.2818 | 141 | 0.0034 | - | - |613| 1.2909 | 142 | 0.0026 | - | - |614| 1.3 | 143 | 0.0044 | - | - |615| 1.3091 | 144 | 0.0024 | - | - |616| 1.3182 | 145 | 0.0036 | - | - |617| 1.3273 | 146 | 0.0242 | - | - |618| 1.3364 | 147 | 0.0015 | - | - |619| 1.3455 | 148 | 0.1008 | - | - |620| 1.3545 | 149 | 0.0057 | - | - |621| 1.3636 | 150 | 0.0062 | - | - |622| 1.3727 | 151 | 0.0048 | - | - |623| 1.3818 | 152 | 0.0026 | - | - |624| 1.3909 | 153 | 0.0045 | - | - |625| 1.4 | 154 | 0.0139 | - | - |626| 1.4091 | 155 | 0.0017 | - | - |627| 1.4182 | 156 | 0.0012 | - | - |628| 1.4273 | 157 | 0.0009 | - | - |629| 1.4364 | 158 | 0.006 | - | - |630| 1.4455 | 159 | 0.0618 | - | - |631| 1.4545 | 160 | 0.0889 | - | - |632| 1.4636 | 161 | 0.0034 | - | - |633| 1.4727 | 162 | 0.0184 | - | - |634| 1.4818 | 163 | 0.0035 | - | - |635| 1.4909 | 164 | 0.002 | - | - |636| 1.5 | 165 | 0.0115 | - | - |637| 1.5091 | 166 | 0.0008 | - | - |638| 1.5182 | 167 | 0.0113 | - | - |639| 1.5273 | 168 | 0.01 | - | - |640| 1.5364 | 169 | 0.0177 | - | - |641| 1.5455 | 170 | 0.0059 | - | - |642| 1.5545 | 171 | 0.0123 | - | - |643| 1.5636 | 172 | 0.0103 | - | - |644| 1.5727 | 173 | 0.008 | - | - |645| 1.5818 | 174 | 0.002 | - | - |646| 1.5909 | 175 | 0.0039 | - | - |647| 1.6 | 176 | 0.0174 | - | - |648| 1.6091 | 177 | 0.0191 | - | - |649| 1.6182 | 178 | 0.002 | - | - |650| 1.6273 | 179 | 0.0009 | - | - |651| 1.6364 | 180 | 0.0021 | - | - |652| 1.6455 | 181 | 0.0011 | - | - |653| 1.6545 | 182 | 0.0027 | - | - |654| 1.6636 | 183 | 0.0005 | - | - |655| 1.6727 | 184 | 0.0026 | - | - |656| 1.6818 | 185 | 0.0047 | - | - |657| 1.6909 | 186 | 0.0033 | - | - |658| 1.7 | 187 | 0.0402 | - | - |659| 1.7091 | 188 | 0.0128 | - | - |660| 1.7182 | 189 | 0.01 | - | - |661| 1.7273 | 190 | 0.0057 | - | - |662| 1.7364 | 191 | 0.0133 | - | - |663| 1.7455 | 192 | 0.0099 | - | - |664| 1.7545 | 193 | 0.1022 | - | - |665| 1.7636 | 194 | 0.0223 | - | - |666| 1.7727 | 195 | 0.0037 | - | - |667| 1.7818 | 196 | 0.0073 | - | - |668| 1.7909 | 197 | 0.0212 | - | - |669| 1.8 | 198 | 0.0231 | - | - |670| 1.8091 | 199 | 0.0016 | - | - |671| 1.8182 | 200 | 0.0017 | - | - |672| 1.8273 | 201 | 0.0035 | - | - |673| 1.8364 | 202 | 0.0165 | - | - |674| 1.8455 | 203 | 0.0131 | - | - |675| 1.8545 | 204 | 0.0032 | - | - |676| 1.8636 | 205 | 0.0075 | - | - |677| 1.8727 | 206 | 0.0438 | - | - |678| 1.8818 | 207 | 0.0022 | - | - |679| 1.8909 | 208 | 0.0501 | - | - |680| 1.9 | 209 | 0.0121 | - | - |681| 1.9091 | 210 | 0.0036 | - | - |682| 1.9182 | 211 | 0.0041 | - | - |683| 1.9273 | 212 | 0.0048 | - | - |684| 1.9364 | 213 | 0.0159 | - | - |685| 1.9455 | 214 | 0.0036 | - | - |686| 1.9545 | 215 | 0.0035 | - | - |687| 1.9636 | 216 | 0.004 | - | - |688| 1.9727 | 217 | 0.0039 | - | - |689| 1.9818 | 218 | 0.0177 | - | - |690| 1.9909 | 219 | 0.0042 | - | - |691| 2.0 | 220 | 0.0044 | 0.0230 | 0.7225 |692| 2.0091 | 221 | 0.0339 | - | - |693| 2.0182 | 222 | 0.0032 | - | - |694| 2.0273 | 223 | 0.0133 | - | - |695| 2.0364 | 224 | 0.0031 | - | - |696| 2.0455 | 225 | 0.0025 | - | - |697| 2.0545 | 226 | 0.0039 | - | - |698| 2.0636 | 227 | 0.0011 | - | - |699| 2.0727 | 228 | 0.0021 | - | - |700| 2.0818 | 229 | 0.0591 | - | - |701| 2.0909 | 230 | 0.0011 | - | - |702| 2.1 | 231 | 0.0008 | - | - |703| 2.1091 | 232 | 0.0014 | - | - |704| 2.1182 | 233 | 0.0057 | - | - |705| 2.1273 | 234 | 0.0044 | - | - |706| 2.1364 | 235 | 0.001 | - | - |707| 2.1455 | 236 | 0.0009 | - | - |708| 2.1545 | 237 | 0.0028 | - | - |709| 2.1636 | 238 | 0.0076 | - | - |710| 2.1727 | 239 | 0.0018 | - | - |711| 2.1818 | 240 | 0.0022 | - | - |712| 2.1909 | 241 | 0.0029 | - | - |713| 2.2 | 242 | 0.0004 | - | - |714| 2.2091 | 243 | 0.0025 | - | - |715| 2.2182 | 244 | 0.0013 | - | - |716| 2.2273 | 245 | 0.0487 | - | - |717| 2.2364 | 246 | 0.0016 | - | - |718| 2.2455 | 247 | 0.0023 | - | - |719| 2.2545 | 248 | 0.0038 | - | - |720| 2.2636 | 249 | 0.003 | - | - |721| 2.2727 | 250 | 0.0017 | - | - |722| 2.2818 | 251 | 0.0056 | - | - |723| 2.2909 | 252 | 0.0036 | - | - |724| 2.3 | 253 | 0.0016 | - | - |725| 2.3091 | 254 | 0.0021 | - | - |726| 2.3182 | 255 | 0.0019 | - | - |727| 2.3273 | 256 | 0.001 | - | - |728| 2.3364 | 257 | 0.0017 | - | - |729| 2.3455 | 258 | 0.0027 | - | - |730| 2.3545 | 259 | 0.0039 | - | - |731| 2.3636 | 260 | 0.0011 | - | - |732| 2.3727 | 261 | 0.0248 | - | - |733| 2.3818 | 262 | 0.0219 | - | - |734| 2.3909 | 263 | 0.0015 | - | - |735| 2.4 | 264 | 0.0009 | - | - |736| 2.4091 | 265 | 0.0013 | - | - |737| 2.4182 | 266 | 0.0049 | - | - |738| 2.4273 | 267 | 0.0073 | - | - |739| 2.4364 | 268 | 0.007 | - | - |740| 2.4455 | 269 | 0.0024 | - | - |741| 2.4545 | 270 | 0.0008 | - | - |742| 2.4636 | 271 | 0.001 | - | - |743| 2.4727 | 272 | 0.0016 | - | - |744| 2.4818 | 273 | 0.0007 | - | - |745| 2.4909 | 274 | 0.0091 | - | - |746| 2.5 | 275 | 0.0127 | - | - |747| 2.5091 | 276 | 0.0013 | - | - |748| 2.5182 | 277 | 0.001 | - | - |749| 2.5273 | 278 | 0.0006 | - | - |750| 2.5364 | 279 | 0.005 | - | - |751| 2.5455 | 280 | 0.0154 | - | - |752| 2.5545 | 281 | 0.0015 | - | - |753| 2.5636 | 282 | 0.0229 | - | - |754| 2.5727 | 283 | 0.0026 | - | - |755| 2.5818 | 284 | 0.0008 | - | - |756| 2.5909 | 285 | 0.0024 | - | - |757| 2.6 | 286 | 0.0012 | - | - |758| 2.6091 | 287 | 0.0748 | - | - |759| 2.6182 | 288 | 0.0086 | - | - |760| 2.6273 | 289 | 0.0013 | - | - |761| 2.6364 | 290 | 0.0089 | - | - |762| 2.6455 | 291 | 0.0011 | - | - |763| 2.6545 | 292 | 0.0096 | - | - |764| 2.6636 | 293 | 0.1416 | - | - |765| 2.6727 | 294 | 0.0005 | - | - |766| 2.6818 | 295 | 0.0021 | - | - |767| 2.6909 | 296 | 0.0014 | - | - |768| 2.7 | 297 | 0.0097 | - | - |769| 2.7091 | 298 | 0.0014 | - | - |770| 2.7182 | 299 | 0.0009 | - | - |771| 2.7273 | 300 | 0.0016 | - | - |772| 2.7364 | 301 | 0.0166 | - | - |773| 2.7455 | 302 | 0.0028 | - | - |774| 2.7545 | 303 | 0.0014 | - | - |775| 2.7636 | 304 | 0.0018 | - | - |776| 2.7727 | 305 | 0.0059 | - | - |777| 2.7818 | 306 | 0.0012 | - | - |778| 2.7909 | 307 | 0.0008 | - | - |779| 2.8 | 308 | 0.0007 | - | - |780| 2.8091 | 309 | 0.0038 | - | - |781| 2.8182 | 310 | 0.0012 | - | - |782| 2.8273 | 311 | 0.0091 | - | - |783| 2.8364 | 312 | 0.0111 | - | - |784| 2.8455 | 313 | 0.0016 | - | - |785| 2.8545 | 314 | 0.0089 | - | - |786| 2.8636 | 315 | 0.0071 | - | - |787| 2.8727 | 316 | 0.0012 | - | - |788| 2.8818 | 317 | 0.0251 | - | - |789| 2.8909 | 318 | 0.0017 | - | - |790| 2.9 | 319 | 0.0006 | - | - |791| 2.9091 | 320 | 0.0014 | - | - |792| 2.9182 | 321 | 0.0011 | - | - |793| 2.9273 | 322 | 0.0084 | - | - |794| 2.9364 | 323 | 0.0055 | - | - |795| 2.9455 | 324 | 0.0011 | - | - |796| 2.9545 | 325 | 0.0017 | - | - |797| 2.9636 | 326 | 0.0008 | - | - |798| 2.9727 | 327 | 0.0082 | - | - |799| 2.9818 | 328 | 0.0006 | - | - |800| 2.9909 | 329 | 0.0008 | - | - |801| 3.0 | 330 | 0.0022 | 0.0275 | 0.6950 |802| 3.0091 | 331 | 0.0007 | - | - |803| 3.0182 | 332 | 0.0012 | - | - |804| 3.0273 | 333 | 0.0007 | - | - |805| 3.0364 | 334 | 0.0038 | - | - |806| 3.0455 | 335 | 0.0006 | - | - |807| 3.0545 | 336 | 0.0012 | - | - |808| 3.0636 | 337 | 0.0873 | - | - |809| 3.0727 | 338 | 0.0022 | - | - |810| 3.0818 | 339 | 0.0004 | - | - |811| 3.0909 | 340 | 0.001 | - | - |812| 3.1 | 341 | 0.0002 | - | - |813| 3.1091 | 342 | 0.0069 | - | - |814| 3.1182 | 343 | 0.0009 | - | - |815| 3.1273 | 344 | 0.0101 | - | - |816| 3.1364 | 345 | 0.0022 | - | - |817| 3.1455 | 346 | 0.009 | - | - |818| 3.1545 | 347 | 0.0018 | - | - |819| 3.1636 | 348 | 0.0018 | - | - |820| 3.1727 | 349 | 0.0045 | - | - |821| 3.1818 | 350 | 0.029 | - | - |822| 3.1909 | 351 | 0.0036 | - | - |823| 3.2 | 352 | 0.0015 | - | - |824| 3.2091 | 353 | 0.0021 | - | - |825| 3.2182 | 354 | 0.0103 | - | - |826| 3.2273 | 355 | 0.0005 | - | - |827| 3.2364 | 356 | 0.0133 | - | - |828| 3.2455 | 357 | 0.0015 | - | - |829| 3.2545 | 358 | 0.001 | - | - |830| 3.2636 | 359 | 0.0024 | - | - |831| 3.2727 | 360 | 0.0052 | - | - |832| 3.2818 | 361 | 0.0032 | - | - |833| 3.2909 | 362 | 0.0024 | - | - |834| 3.3 | 363 | 0.0008 | - | - |835| 3.3091 | 364 | 0.0035 | - | - |836| 3.3182 | 365 | 0.0012 | - | - |837| 3.3273 | 366 | 0.0049 | - | - |838| 3.3364 | 367 | 0.0452 | - | - |839| 3.3455 | 368 | 0.0017 | - | - |840| 3.3545 | 369 | 0.0112 | - | - |841| 3.3636 | 370 | 0.0011 | - | - |842| 3.3727 | 371 | 0.0016 | - | - |843| 3.3818 | 372 | 0.0015 | - | - |844| 3.3909 | 373 | 0.004 | - | - |845| 3.4 | 374 | 0.0074 | - | - |846| 3.4091 | 375 | 0.0005 | - | - |847| 3.4182 | 376 | 0.0007 | - | - |848| 3.4273 | 377 | 0.0014 | - | - |849| 3.4364 | 378 | 0.0097 | - | - |850| 3.4455 | 379 | 0.0026 | - | - |851| 3.4545 | 380 | 0.0022 | - | - |852| 3.4636 | 381 | 0.001 | - | - |853| 3.4727 | 382 | 0.0004 | - | - |854| 3.4818 | 383 | 0.004 | - | - |855| 3.4909 | 384 | 0.0017 | - | - |856| 3.5 | 385 | 0.0014 | - | - |857| 3.5091 | 386 | 0.001 | - | - |858| 3.5182 | 387 | 0.0047 | - | - |859| 3.5273 | 388 | 0.0061 | - | - |860| 3.5364 | 389 | 0.0017 | - | - |861| 3.5455 | 390 | 0.0024 | - | - |862| 3.5545 | 391 | 0.0021 | - | - |863| 3.5636 | 392 | 0.0007 | - | - |864| 3.5727 | 393 | 0.0009 | - | - |865| 3.5818 | 394 | 0.0006 | - | - |866| 3.5909 | 395 | 0.0038 | - | - |867| 3.6 | 396 | 0.0006 | - | - |868| 3.6091 | 397 | 0.0011 | - | - |869| 3.6182 | 398 | 0.001 | - | - |870| 3.6273 | 399 | 0.0014 | - | - |871| 3.6364 | 400 | 0.0007 | - | - |872| 3.6455 | 401 | 0.0052 | - | - |873| 3.6545 | 402 | 0.0008 | - | - |874| 3.6636 | 403 | 0.0009 | - | - |875| 3.6727 | 404 | 0.0017 | - | - |876| 3.6818 | 405 | 0.0028 | - | - |877| 3.6909 | 406 | 0.0044 | - | - |878| 3.7 | 407 | 0.0009 | - | - |879| 3.7091 | 408 | 0.0134 | - | - |880| 3.7182 | 409 | 0.001 | - | - |881| 3.7273 | 410 | 0.0044 | - | - |882| 3.7364 | 411 | 0.0138 | - | - |883| 3.7455 | 412 | 0.0032 | - | - |884| 3.7545 | 413 | 0.0004 | - | - |885| 3.7636 | 414 | 0.0065 | - | - |886| 3.7727 | 415 | 0.0007 | - | - |887| 3.7818 | 416 | 0.0008 | - | - |888| 3.7909 | 417 | 0.0007 | - | - |889| 3.8 | 418 | 0.0018 | - | - |890| 3.8091 | 419 | 0.001 | - | - |891| 3.8182 | 420 | 0.0305 | - | - |892| 3.8273 | 421 | 0.001 | - | - |893| 3.8364 | 422 | 0.0011 | - | - |894| 3.8455 | 423 | 0.0004 | - | - |895| 3.8545 | 424 | 0.003 | - | - |896| 3.8636 | 425 | 0.002 | - | - |897| 3.8727 | 426 | 0.0018 | - | - |898| 3.8818 | 427 | 0.0968 | - | - |899| 3.8909 | 428 | 0.002 | - | - |900| 3.9 | 429 | 0.002 | - | - |901| 3.9091 | 430 | 0.0156 | - | - |902| 3.9182 | 431 | 0.0059 | - | - |903| 3.9273 | 432 | 0.001 | - | - |904| 3.9364 | 433 | 0.0153 | - | - |905| 3.9455 | 434 | 0.0013 | - | - |906| 3.9545 | 435 | 0.0003 | - | - |907| 3.9636 | 436 | 0.001 | - | - |908| 3.9727 | 437 | 0.0005 | - | - |909| 3.9818 | 438 | 0.0012 | - | - |910| 3.9909 | 439 | 0.0109 | - | - |911| 4.0 | 440 | 0.1597 | 0.0211 | 0.7235 |912| 4.0091 | 441 | 0.0027 | - | - |913| 4.0182 | 442 | 0.0007 | - | - |914| 4.0273 | 443 | 0.0089 | - | - |915| 4.0364 | 444 | 0.0007 | - | - |916| 4.0455 | 445 | 0.005 | - | - |917| 4.0545 | 446 | 0.0019 | - | - |918| 4.0636 | 447 | 0.0007 | - | - |919| 4.0727 | 448 | 0.0008 | - | - |920| 4.0818 | 449 | 0.002 | - | - |921| 4.0909 | 450 | 0.043 | - | - |922| 4.1 | 451 | 0.0273 | - | - |923| 4.1091 | 452 | 0.0009 | - | - |924| 4.1182 | 453 | 0.0011 | - | - |925| 4.1273 | 454 | 0.0007 | - | - |926| 4.1364 | 455 | 0.0062 | - | - |927| 4.1455 | 456 | 0.0004 | - | - |928| 4.1545 | 457 | 0.0008 | - | - |929| 4.1636 | 458 | 0.0128 | - | - |930| 4.1727 | 459 | 0.0012 | - | - |931| 4.1818 | 460 | 0.0013 | - | - |932| 4.1909 | 461 | 0.0009 | - | - |933| 4.2 | 462 | 0.0011 | - | - |934| 4.2091 | 463 | 0.0336 | - | - |935| 4.2182 | 464 | 0.0018 | - | - |936| 4.2273 | 465 | 0.0009 | - | - |937| 4.2364 | 466 | 0.0049 | - | - |938| 4.2455 | 467 | 0.0012 | - | - |939| 4.2545 | 468 | 0.001 | - | - |940| 4.2636 | 469 | 0.0024 | - | - |941| 4.2727 | 470 | 0.0063 | - | - |942| 4.2818 | 471 | 0.0008 | - | - |943| 4.2909 | 472 | 0.0793 | - | - |944| 4.3 | 473 | 0.0016 | - | - |945| 4.3091 | 474 | 0.0016 | - | - |946| 4.3182 | 475 | 0.0043 | - | - |947| 4.3273 | 476 | 0.036 | - | - |948| 4.3364 | 477 | 0.002 | - | - |949| 4.3455 | 478 | 0.0019 | - | - |950| 4.3545 | 479 | 0.0012 | - | - |951| 4.3636 | 480 | 0.0059 | - | - |952| 4.3727 | 481 | 0.0017 | - | - |953| 4.3818 | 482 | 0.0004 | - | - |954| 4.3909 | 483 | 0.0014 | - | - |955| 4.4 | 484 | 0.0143 | - | - |956| 4.4091 | 485 | 0.0014 | - | - |957| 4.4182 | 486 | 0.0009 | - | - |958| 4.4273 | 487 | 0.0027 | - | - |959| 4.4364 | 488 | 0.0017 | - | - |960| 4.4455 | 489 | 0.0007 | - | - |961| 4.4545 | 490 | 0.0008 | - | - |962| 4.4636 | 491 | 0.0008 | - | - |963| 4.4727 | 492 | 0.0014 | - | - |964| 4.4818 | 493 | 0.0011 | - | - |965| 4.4909 | 494 | 0.0013 | - | - |966| 4.5 | 495 | 0.0016 | - | - |967| 4.5091 | 496 | 0.001 | - | - |968| 4.5182 | 497 | 0.0008 | - | - |969| 4.5273 | 498 | 0.001 | - | - |970| 4.5364 | 499 | 0.0019 | - | - |971| 4.5455 | 500 | 0.0008 | - | - |972 973</details>974 975### Framework Versions976- Python: 3.12.9977- Sentence Transformers: 4.1.0978- Transformers: 4.52.3979- PyTorch: 2.6.0+cu124980- Accelerate: 1.7.0981- Datasets: 3.6.0982- Tokenizers: 0.21.1983 984## Citation985 986### BibTeX987 988#### Sentence Transformers989```bibtex990@inproceedings{reimers-2019-sentence-bert,991 title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",992 author = "Reimers, Nils and Gurevych, Iryna",993 booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",994 month = "11",995 year = "2019",996 publisher = "Association for Computational Linguistics",997 url = "https://arxiv.org/abs/1908.10084",998}999```1000 1001#### MultipleNegativesRankingLoss1002```bibtex1003@misc{henderson2017efficient,1004 title={Efficient Natural Language Response Suggestion for Smart Reply},1005 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},1006 year={2017},1007 eprint={1705.00652},1008 archivePrefix={arXiv},1009 primaryClass={cs.CL}1010}1011```1012 1013<!--1014## Glossary1015 1016*Clearly define terms in order to be accessible across audiences.*1017-->1018 1019<!--1020## Model Card Authors1021 1022*Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.*1023-->1024 1025<!--1026## Model Card Contact1027 1028*Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.*1029-->