diff --git "a/README.md" "b/README.md" new file mode 100644--- /dev/null +++ "b/README.md" @@ -0,0 +1,1525 @@ +--- +base_model: SQAI/bge-embedding-model +datasets: [] +language: +- en +library_name: sentence-transformers +license: apache-2.0 +metrics: +- cosine_accuracy@1 +- cosine_accuracy@3 +- cosine_accuracy@5 +- cosine_accuracy@10 +- cosine_precision@1 +- cosine_precision@3 +- cosine_precision@5 +- cosine_precision@10 +- cosine_recall@1 +- cosine_recall@3 +- cosine_recall@5 +- cosine_recall@10 +- cosine_ndcg@10 +- cosine_mrr@10 +- cosine_map@100 +pipeline_tag: sentence-similarity +tags: +- sentence-transformers +- sentence-similarity +- feature-extraction +- generated_from_trainer +- dataset_size:1865 +- loss:MatryoshkaLoss +- loss:MultipleNegativesRankingLoss +widget: +- source_sentence: threshold.highLuxThreshold + sentences: + - '"Can you provide the timestamp of the last update to the threshold settings, + and detail any faults in the lux module related to light level sensing and control + for the streetlight on this specific street name? I also want to know the longitude + of the streetlight. And also, can you tell me what type of dimming schedule is + applied to the streetlight, the type of port used for its dimming controls, and + the total energy it has consumed, recorded in kilowatt-hours. Lastly, could you + also provide the timestamp of the recorded streetlighting error, and confirm the + status of the relay responsible for turning this streetlight on and off, as I + am suspecting it might be sticking?"' + - '"Can you provide me with the unique streetlight identifier, upper lux level for + managing light intensity, a brief description, and the delta or height of the + grid area occupied by a group of streetlights? Also, can you note the AC voltage + supply for these streetlights, any issues with communication related to their + lux sensors, and the count of how many times each streetlight has been switched + on? Please ensure that the data is constrained to just those that can be determined + with the unique streetlight identifier I provided."' + - '"What was the last recorded data or action timestamp of the streetlight located + at the specific longitude, and in which time zone is it situated? Could you also + provide information on its default dimming level and the maximum power usage threshold + above which indicates potential faults? Are there any identified faults in the + lux module impacting light level sensing and control? Additionally, what are the + minimum longitude and delta or height for the grid area occupied by this group + of streetlights and could you specify the network time received from the central + control for synchronization purposes?"' +- source_sentence: asset.geoZone + sentences: + - '"Could you check the status of the streetlight with the unique identifier, located + on the named street, specifically looking at any records of complete loss of power + which could indicate supply issues or damage? Also, could you provide details + on the instances where the voltage under load is lower than expected, as well + as instances of lower than expected power consumption, which could signal potential + electrical or hardware issues? I''m also interested in understanding if there + are any faults in our link control mechanism managing multiple streetlights. Additionally, + could you tell me the current drawn by this specific streetlight when it was lower + than expected and the current dimming level of the streetlight in operation? Lastly, + could you specify the maximum safe voltage under load conditions for this light + and verify whether its broadcast subscription used for receiving control signals + is doing fine?"' + - '"Can you provide me with the details regarding a specific streetlight on Main + Street, particularly the minimum current level below which it''s considered abnormal, + its power factor indicating efficient power usage, total operational hours logged, + any incidences where power consumption was higher than expected possibly due to + potential faults, its geoZone, X-coordinate in the grid layout, minimum operational + voltage under load conditions, minimum load current that indicates suboptimal + performance, and the timestamp of the last update made to the threshold settings?"' + - '"What is the width and height of the grid area occupied by the group of streetlights, + type of port used for dimming controls, power consumption levels, and what is + the safety of the current exceeded on the streetlight? Besides, could you explain + the high power factor indicating potential overloads or capacitive imbalances?"' +- source_sentence: errors.deviceId + sentences: + - '"Can you show me a report of all the streetlights with a unique identifier, which + have an internal temperature indicating abnormal operating conditions such as + voltage supplied being below the safe level, and operating temperature below expected + limit possibly due to environmental conditions? Can this report also include instances + of faults in link control mechanism managing multiple streetlights and cases of + open circuit in the relay preventing normal operation?"' + - '"Could you provide information about the streetlight on ''specific street name'', + specifically concerning its current drawn which appears to be lower than expected, + potential issues in the link control mechanism that manages multiple streetlights, + whether its operating temperature exceeds safe limits thus risking damage, and + if its power output is lower than expected? Also, could you let me know at what + interval this streetlight sends data reports and inform about any other issues + detected, particularly when the current is below the expected range?"' + - '"What is the minimum power usage level below which it is considered abnormal + for our ''Main Street Lamps'' group of streetlights, which are described as a + series of LED lamps installed along the main town stretch, and what could be the + reasons if the power consumption is lower than expected, possibly due to hardware + issues? Also, could you give me the description on what means when intermittent + flashing of the streetlight occurs, indicating instability and tell me about the + strength of the wireless signal received by the streetlight''s communication module. + Could you confirm what control mode switch identifier we should use for changing + streetlight settings and the highest power factor that is considered optimal for + streetlight efficiency? Additionally, we discovered issues with group management + of streetlights via our central control system, and we would like to know the + time taken for the streetlight to activate or light up from the command."' +- source_sentence: threshold.lowLoadVoltage + sentences: + - '"Could you please show me the latest data recorded or action performed by the + streetlight, specifically highlighting the control mode switch identifier used + for changing its settings, the type of DALI dimming protocol it uses, and the + type of port used for its dimming controls? Furthermore, has there been any intermittent + flashing indicating instability? Also, could you provide data on its minimum operational + voltage under load conditions, and let me know if its power consumption is lower + than expected due to potential hardware issues?" + + ' + - '"Can the operator managing the streetlight provide the timestamp of the latest + data recorded or action performed by the streetlight, details on the minimum operational + voltage under load conditions, the current issues with the driver that powers + and controls the streetlight, why the power output is lower than expected for + the streetlight, and what is the maximum latitude of the geographic area covered + by this group of streetlights?"' + - '"Can you provide a report that shows all the streetlights in a grid layout with + Y-coordinate information, indicating whether their control mode setting is on + automated or manual, their minimum current level, and instances of communication + issues between the streetlight''s driver and the control system, as well as instances + when the operating temperature fell below expected limits, possibly due to environmental + conditions?"' +- source_sentence: errors.controllerFault.lowLoadCurrent + sentences: + - '"Can you provide me with the current status of the streetlight on ''street name'', + specifically in relation to its voltage under load, whether it''s lower than expected + and how that might be indicating potential electrical issues? Could you also give + me insight into the current drawn by the streetlight, whether or not the relay + is currently on or off, and if there are any faults in the lux module that may + affect light level sensing and control? Moreover, could you tell me the type of + dimming schedule applied, the ambient light level detected in lux, the total energy + consumed so far recorded in kilowatt-hours, and the lower voltage threshold for + this streetlight''s efficient operation?"' + - '"Can you provide a detailed report for the streetlight on [Name of the street + for the streetlight in error]? The report should include the timestamp of the + last recorded error, synchronization time received from the central control, the + dimming schedule type we''re currently using, and both minimum operational and + maximum safe voltage under load conditions. Also, indicate the time of the last + action was recorded and if there are any reported faults in the metering components + affecting data reporting. Can you also specify the port type used for dimming + controls and whether the power consumption has been unusually low due to potential + hardware issues?"' + - '"Can you show me the current status of the relay in the streetlights located + at the X-coordinate grid, highlighting any faults in the lux module that might + be affecting light level sensing and control? Also, could you provide information + on the current dimming level of these streetlights in operation, the type of dimming + schedule applied, and whether the voltage is within the upper limit considered + safe and efficient for their operation?"' +model-index: +- name: BGE base Financial Matryoshka + results: + - task: + type: information-retrieval + name: Information Retrieval + dataset: + name: dim 768 + type: dim_768 + metrics: + - type: cosine_accuracy@1 + value: 0.0 + name: Cosine Accuracy@1 + - type: cosine_accuracy@3 + value: 0.0 + name: Cosine Accuracy@3 + - type: cosine_accuracy@5 + value: 0.0 + name: Cosine Accuracy@5 + - type: cosine_accuracy@10 + value: 0.014423076923076924 + name: Cosine Accuracy@10 + - type: cosine_precision@1 + value: 0.0 + name: Cosine Precision@1 + - type: cosine_precision@3 + value: 0.0 + name: Cosine Precision@3 + - type: cosine_precision@5 + value: 0.0 + name: Cosine Precision@5 + - type: cosine_precision@10 + value: 0.0014423076923076926 + name: Cosine Precision@10 + - type: cosine_recall@1 + value: 0.0 + name: Cosine Recall@1 + - type: cosine_recall@3 + value: 0.0 + name: Cosine Recall@3 + - type: cosine_recall@5 + value: 0.0 + name: Cosine Recall@5 + - type: cosine_recall@10 + value: 0.014423076923076924 + name: Cosine Recall@10 + - type: cosine_ndcg@10 + value: 0.004284253930989665 + name: Cosine Ndcg@10 + - type: cosine_mrr@10 + value: 0.001549145299145299 + name: Cosine Mrr@10 + - type: cosine_map@100 + value: 0.005857063109582476 + name: Cosine Map@100 + - task: + type: information-retrieval + name: Information Retrieval + dataset: + name: dim 512 + type: dim_512 + metrics: + - type: cosine_accuracy@1 + value: 0.0 + name: Cosine Accuracy@1 + - type: cosine_accuracy@3 + value: 0.0 + name: Cosine Accuracy@3 + - type: cosine_accuracy@5 + value: 0.0 + name: Cosine Accuracy@5 + - type: cosine_accuracy@10 + value: 0.014423076923076924 + name: Cosine Accuracy@10 + - type: cosine_precision@1 + value: 0.0 + name: Cosine Precision@1 + - type: cosine_precision@3 + value: 0.0 + name: Cosine Precision@3 + - type: cosine_precision@5 + value: 0.0 + name: Cosine Precision@5 + - type: cosine_precision@10 + value: 0.0014423076923076926 + name: Cosine Precision@10 + - type: cosine_recall@1 + value: 0.0 + name: Cosine Recall@1 + - type: cosine_recall@3 + value: 0.0 + name: Cosine Recall@3 + - type: cosine_recall@5 + value: 0.0 + name: Cosine Recall@5 + - type: cosine_recall@10 + value: 0.014423076923076924 + name: Cosine Recall@10 + - type: cosine_ndcg@10 + value: 0.004284253930989665 + name: Cosine Ndcg@10 + - type: cosine_mrr@10 + value: 0.001549145299145299 + name: Cosine Mrr@10 + - type: cosine_map@100 + value: 0.005857063109582476 + name: Cosine Map@100 + - task: + type: information-retrieval + name: Information Retrieval + dataset: + name: dim 256 + type: dim_256 + metrics: + - type: cosine_accuracy@1 + value: 0.0 + name: Cosine Accuracy@1 + - type: cosine_accuracy@3 + value: 0.0 + name: Cosine Accuracy@3 + - type: cosine_accuracy@5 + value: 0.0 + name: Cosine Accuracy@5 + - type: cosine_accuracy@10 + value: 0.014423076923076924 + name: Cosine Accuracy@10 + - type: cosine_precision@1 + value: 0.0 + name: Cosine Precision@1 + - type: cosine_precision@3 + value: 0.0 + name: Cosine Precision@3 + - type: cosine_precision@5 + value: 0.0 + name: Cosine Precision@5 + - type: cosine_precision@10 + value: 0.0014423076923076926 + name: Cosine Precision@10 + - type: cosine_recall@1 + value: 0.0 + name: Cosine Recall@1 + - type: cosine_recall@3 + value: 0.0 + name: Cosine Recall@3 + - type: cosine_recall@5 + value: 0.0 + name: Cosine Recall@5 + - type: cosine_recall@10 + value: 0.014423076923076924 + name: Cosine Recall@10 + - type: cosine_ndcg@10 + value: 0.0043536523979211435 + name: Cosine Ndcg@10 + - type: cosine_mrr@10 + value: 0.0016159188034188035 + name: Cosine Mrr@10 + - type: cosine_map@100 + value: 0.005708010488423065 + name: Cosine Map@100 + - task: + type: information-retrieval + name: Information Retrieval + dataset: + name: dim 128 + type: dim_128 + metrics: + - type: cosine_accuracy@1 + value: 0.0 + name: Cosine Accuracy@1 + - type: cosine_accuracy@3 + value: 0.0 + name: Cosine Accuracy@3 + - type: cosine_accuracy@5 + value: 0.0 + name: Cosine Accuracy@5 + - type: cosine_accuracy@10 + value: 0.009615384615384616 + name: Cosine Accuracy@10 + - type: cosine_precision@1 + value: 0.0 + name: Cosine Precision@1 + - type: cosine_precision@3 + value: 0.0 + name: Cosine Precision@3 + - type: cosine_precision@5 + value: 0.0 + name: Cosine Precision@5 + - type: cosine_precision@10 + value: 0.0009615384615384616 + name: Cosine Precision@10 + - type: cosine_recall@1 + value: 0.0 + name: Cosine Recall@1 + - type: cosine_recall@3 + value: 0.0 + name: Cosine Recall@3 + - type: cosine_recall@5 + value: 0.0 + name: Cosine Recall@5 + - type: cosine_recall@10 + value: 0.009615384615384616 + name: Cosine Recall@10 + - type: cosine_ndcg@10 + value: 0.0030498236971024735 + name: Cosine Ndcg@10 + - type: cosine_mrr@10 + value: 0.001221001221001221 + name: Cosine Mrr@10 + - type: cosine_map@100 + value: 0.005185692544152747 + name: Cosine Map@100 + - task: + type: information-retrieval + name: Information Retrieval + dataset: + name: dim 64 + type: dim_64 + metrics: + - type: cosine_accuracy@1 + value: 0.0 + name: Cosine Accuracy@1 + - type: cosine_accuracy@3 + value: 0.0 + name: Cosine Accuracy@3 + - type: cosine_accuracy@5 + value: 0.0 + name: Cosine Accuracy@5 + - type: cosine_accuracy@10 + value: 0.019230769230769232 + name: Cosine Accuracy@10 + - type: cosine_precision@1 + value: 0.0 + name: Cosine Precision@1 + - type: cosine_precision@3 + value: 0.0 + name: Cosine Precision@3 + - type: cosine_precision@5 + value: 0.0 + name: Cosine Precision@5 + - type: cosine_precision@10 + value: 0.0019230769230769232 + name: Cosine Precision@10 + - type: cosine_recall@1 + value: 0.0 + name: Cosine Recall@1 + - type: cosine_recall@3 + value: 0.0 + name: Cosine Recall@3 + - type: cosine_recall@5 + value: 0.0 + name: Cosine Recall@5 + - type: cosine_recall@10 + value: 0.019230769230769232 + name: Cosine Recall@10 + - type: cosine_ndcg@10 + value: 0.005956216500485246 + name: Cosine Ndcg@10 + - type: cosine_mrr@10 + value: 0.0023027319902319903 + name: Cosine Mrr@10 + - type: cosine_map@100 + value: 0.0051874402718147935 + name: Cosine Map@100 +--- + +# BGE base Financial Matryoshka + +This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [SQAI/bge-embedding-model](https://huggingface.co/SQAI/bge-embedding-model). 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:** [SQAI/bge-embedding-model](https://huggingface.co/SQAI/bge-embedding-model) +- **Maximum Sequence Length:** 512 tokens +- **Output Dimensionality:** 384 tokens +- **Similarity Function:** Cosine Similarity + +- **Language:** en +- **License:** apache-2.0 + +### Model Sources + +- **Documentation:** [Sentence Transformers Documentation](https://sbert.net) +- **Repository:** [Sentence Transformers on GitHub](https://github.com/UKPLab/sentence-transformers) +- **Hugging Face:** [Sentence Transformers on Hugging Face](https://huggingface.co/models?library=sentence-transformers) + +### Full Model Architecture + +``` +SentenceTransformer( + (0): Transformer({'max_seq_length': 512, 'do_lower_case': True}) with Transformer model: BertModel + (1): Pooling({'word_embedding_dimension': 384, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True}) + (2): Normalize() +) +``` + +## Usage + +### Direct Usage (Sentence Transformers) + +First install the Sentence Transformers library: + +```bash +pip install -U sentence-transformers +``` + +Then you can load this model and run inference. +```python +from sentence_transformers import SentenceTransformer + +# Download from the 🤗 Hub +model = SentenceTransformer("SQAI/bge-embedding-model2") +# Run inference +sentences = [ + 'errors.controllerFault.lowLoadCurrent', + '"Can you provide me with the current status of the streetlight on \'street name\', specifically in relation to its voltage under load, whether it\'s lower than expected and how that might be indicating potential electrical issues? Could you also give me insight into the current drawn by the streetlight, whether or not the relay is currently on or off, and if there are any faults in the lux module that may affect light level sensing and control? Moreover, could you tell me the type of dimming schedule applied, the ambient light level detected in lux, the total energy consumed so far recorded in kilowatt-hours, and the lower voltage threshold for this streetlight\'s efficient operation?"', + '"Can you show me the current status of the relay in the streetlights located at the X-coordinate grid, highlighting any faults in the lux module that might be affecting light level sensing and control? Also, could you provide information on the current dimming level of these streetlights in operation, the type of dimming schedule applied, and whether the voltage is within the upper limit considered safe and efficient for their operation?"', +] +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] +``` + + + + + + + +## Evaluation + +### Metrics + +#### Information Retrieval +* Dataset: `dim_768` +* Evaluated with [InformationRetrievalEvaluator](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.InformationRetrievalEvaluator) + +| Metric | Value | +|:--------------------|:-----------| +| cosine_accuracy@1 | 0.0 | +| cosine_accuracy@3 | 0.0 | +| cosine_accuracy@5 | 0.0 | +| cosine_accuracy@10 | 0.0144 | +| cosine_precision@1 | 0.0 | +| cosine_precision@3 | 0.0 | +| cosine_precision@5 | 0.0 | +| cosine_precision@10 | 0.0014 | +| cosine_recall@1 | 0.0 | +| cosine_recall@3 | 0.0 | +| cosine_recall@5 | 0.0 | +| cosine_recall@10 | 0.0144 | +| cosine_ndcg@10 | 0.0043 | +| cosine_mrr@10 | 0.0015 | +| **cosine_map@100** | **0.0059** | + +#### Information Retrieval +* Dataset: `dim_512` +* Evaluated with [InformationRetrievalEvaluator](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.InformationRetrievalEvaluator) + +| Metric | Value | +|:--------------------|:-----------| +| cosine_accuracy@1 | 0.0 | +| cosine_accuracy@3 | 0.0 | +| cosine_accuracy@5 | 0.0 | +| cosine_accuracy@10 | 0.0144 | +| cosine_precision@1 | 0.0 | +| cosine_precision@3 | 0.0 | +| cosine_precision@5 | 0.0 | +| cosine_precision@10 | 0.0014 | +| cosine_recall@1 | 0.0 | +| cosine_recall@3 | 0.0 | +| cosine_recall@5 | 0.0 | +| cosine_recall@10 | 0.0144 | +| cosine_ndcg@10 | 0.0043 | +| cosine_mrr@10 | 0.0015 | +| **cosine_map@100** | **0.0059** | + +#### Information Retrieval +* Dataset: `dim_256` +* Evaluated with [InformationRetrievalEvaluator](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.InformationRetrievalEvaluator) + +| Metric | Value | +|:--------------------|:-----------| +| cosine_accuracy@1 | 0.0 | +| cosine_accuracy@3 | 0.0 | +| cosine_accuracy@5 | 0.0 | +| cosine_accuracy@10 | 0.0144 | +| cosine_precision@1 | 0.0 | +| cosine_precision@3 | 0.0 | +| cosine_precision@5 | 0.0 | +| cosine_precision@10 | 0.0014 | +| cosine_recall@1 | 0.0 | +| cosine_recall@3 | 0.0 | +| cosine_recall@5 | 0.0 | +| cosine_recall@10 | 0.0144 | +| cosine_ndcg@10 | 0.0044 | +| cosine_mrr@10 | 0.0016 | +| **cosine_map@100** | **0.0057** | + +#### Information Retrieval +* Dataset: `dim_128` +* Evaluated with [InformationRetrievalEvaluator](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.InformationRetrievalEvaluator) + +| Metric | Value | +|:--------------------|:-----------| +| cosine_accuracy@1 | 0.0 | +| cosine_accuracy@3 | 0.0 | +| cosine_accuracy@5 | 0.0 | +| cosine_accuracy@10 | 0.0096 | +| cosine_precision@1 | 0.0 | +| cosine_precision@3 | 0.0 | +| cosine_precision@5 | 0.0 | +| cosine_precision@10 | 0.001 | +| cosine_recall@1 | 0.0 | +| cosine_recall@3 | 0.0 | +| cosine_recall@5 | 0.0 | +| cosine_recall@10 | 0.0096 | +| cosine_ndcg@10 | 0.003 | +| cosine_mrr@10 | 0.0012 | +| **cosine_map@100** | **0.0052** | + +#### Information Retrieval +* Dataset: `dim_64` +* Evaluated with [InformationRetrievalEvaluator](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.InformationRetrievalEvaluator) + +| Metric | Value | +|:--------------------|:-----------| +| cosine_accuracy@1 | 0.0 | +| cosine_accuracy@3 | 0.0 | +| cosine_accuracy@5 | 0.0 | +| cosine_accuracy@10 | 0.0192 | +| cosine_precision@1 | 0.0 | +| cosine_precision@3 | 0.0 | +| cosine_precision@5 | 0.0 | +| cosine_precision@10 | 0.0019 | +| cosine_recall@1 | 0.0 | +| cosine_recall@3 | 0.0 | +| cosine_recall@5 | 0.0 | +| cosine_recall@10 | 0.0192 | +| cosine_ndcg@10 | 0.006 | +| cosine_mrr@10 | 0.0023 | +| **cosine_map@100** | **0.0052** | + + + + + +## Training Details + +### Training Dataset + +#### Unnamed Dataset + + +* Size: 1,865 training samples +* Columns: positive and anchor +* Approximate statistics based on the first 1000 samples: + | | positive | anchor | + |:--------|:---------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| + | type | string | string | + | details | | | +* Samples: + | positive | anchor | + |:----------------------------------------------|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| + | threshold.lowLoadVoltage | "What is the maximum current level above which it is considered unsafe for a specific streetlight in my area, what is the minimum longitude of the geographic area this streetlight covers, is this streetlight's control mode automated or manually controlled, also, can you provide the delta or width of the grid area occupied by this group of streetlights, what is the level of AC voltage supply to this streetlight, what's the lower voltage threshold below which this streetlight may not operate efficiently, how many times has this streetlight been switched on, what is the minimum operational voltage under load conditions, and finally, what is the latitude of this streetlight?" | + | asset.id | "Could you please tell me the scheduled dimming settings for the string stored streetlights, troubleshoot why these streetlights remain on during daylight hours, and confirm if this could be due to sensor faults? Also, I'd like to know the identifier for the parent group to which this group of streetlights belongs, and the IMEI number of the streetlight device." | + | errors.controllerFault.highPower | "Can you provide an analysis of the efficiency of power usage by examining the power factor of the streetlights, especially in areas of the grid with high Y-coordinates, highlight instances where power consumption is significantly higher than expected which may indicate faults, identify situations where voltage under load is above safe levels, and assess if there are any problems with our central control system's ability to manage streetlight groups?" | +* Loss: [MatryoshkaLoss](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#matryoshkaloss) with these parameters: + ```json + { + "loss": "MultipleNegativesRankingLoss", + "matryoshka_dims": [ + 384, + 256, + 128, + 64 + ], + "matryoshka_weights": [ + 1, + 1, + 1, + 1 + ], + "n_dims_per_step": -1 + } + ``` + +### Evaluation Dataset + +#### Unnamed Dataset + + +* Size: 208 evaluation samples +* Columns: positive and anchor +* Approximate statistics based on the first 1000 samples: + | | positive | anchor | + |:--------|:---------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| + | type | string | string | + | details | | | +* Samples: + | positive | anchor | + |:---------------------------------------------------|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| + | log.controlModeSwitch | "Can you provide the control mode switch identifier used for changing the default dimming level set for a specific group of streetlights, identified by their unique identifier, considering the time taken for the streetlight to activate or light up from the command, and possibly troubleshoot why the power consumption is lower than expected which could be due to hardware issues, quite possibly due to the relay responsible for turning the streetlight on and off sticking?" | + | errors.controllerFault.luxModuleFault | "Can you provide the timestamp of the last update to the threshold settings, and detail any faults in the lux module related to light level sensing and control for the streetlight on this specific street name? I also want to know the longitude of the streetlight. And also, can you tell me what type of dimming schedule is applied to the streetlight, the type of port used for its dimming controls, and the total energy it has consumed, recorded in kilowatt-hours. Lastly, could you also provide the timestamp of the recorded streetlighting error, and confirm the status of the relay responsible for turning this streetlight on and off, as I am suspecting it might be sticking?" | + | threshold.lowLoadCurrent | "What is the maximum safe voltage under load conditions for the city's streetlights, and do we possess the necessary rights to link these streetlights for synchronized control? Could you provide me with the timestamp of the latest data or action performed by our streetlights, and tell me the lower lux level threshold at which we would need to consider additional lighting? How often does each streetlight send a data report in normal operation, and what is the minimum load current level where we might start seeing suboptimal functioning? Have we been experiencing any problems with managing groups of streetlights via the central control system? Also, has there been any instances where the current under load was excessively high, indicating possible overloads, or situations where the operation temperature was belo normal limits due to environmental conditions? Lastly, have there been any noted communication issues between the streetlight's driver and the control system?" | +* Loss: [MatryoshkaLoss](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#matryoshkaloss) with these parameters: + ```json + { + "loss": "MultipleNegativesRankingLoss", + "matryoshka_dims": [ + 384, + 256, + 128, + 64 + ], + "matryoshka_weights": [ + 1, + 1, + 1, + 1 + ], + "n_dims_per_step": -1 + } + ``` + +### Training Hyperparameters +#### Non-Default Hyperparameters + +- `eval_strategy`: epoch +- `per_device_train_batch_size`: 32 +- `per_device_eval_batch_size`: 16 +- `gradient_accumulation_steps`: 16 +- `learning_rate`: 2e-06 +- `weight_decay`: 0.03 +- `num_train_epochs`: 200 +- `lr_scheduler_type`: cosine +- `warmup_ratio`: 0.2 +- `bf16`: True +- `tf32`: True +- `load_best_model_at_end`: True +- `optim`: adamw_torch_fused +- `batch_sampler`: no_duplicates + +#### All Hyperparameters +
Click to expand + +- `overwrite_output_dir`: False +- `do_predict`: False +- `eval_strategy`: epoch +- `prediction_loss_only`: True +- `per_device_train_batch_size`: 32 +- `per_device_eval_batch_size`: 16 +- `per_gpu_train_batch_size`: None +- `per_gpu_eval_batch_size`: None +- `gradient_accumulation_steps`: 16 +- `eval_accumulation_steps`: None +- `learning_rate`: 2e-06 +- `weight_decay`: 0.03 +- `adam_beta1`: 0.9 +- `adam_beta2`: 0.999 +- `adam_epsilon`: 1e-08 +- `max_grad_norm`: 1.0 +- `num_train_epochs`: 200 +- `max_steps`: -1 +- `lr_scheduler_type`: cosine +- `lr_scheduler_kwargs`: {} +- `warmup_ratio`: 0.2 +- `warmup_steps`: 0 +- `log_level`: passive +- `log_level_replica`: warning +- `log_on_each_node`: True +- `logging_nan_inf_filter`: True +- `save_safetensors`: True +- `save_on_each_node`: False +- `save_only_model`: False +- `restore_callback_states_from_checkpoint`: False +- `no_cuda`: False +- `use_cpu`: False +- `use_mps_device`: False +- `seed`: 42 +- `data_seed`: None +- `jit_mode_eval`: False +- `use_ipex`: False +- `bf16`: True +- `fp16`: False +- `fp16_opt_level`: O1 +- `half_precision_backend`: auto +- `bf16_full_eval`: False +- `fp16_full_eval`: False +- `tf32`: True +- `local_rank`: 0 +- `ddp_backend`: None +- `tpu_num_cores`: None +- `tpu_metrics_debug`: False +- `debug`: [] +- `dataloader_drop_last`: False +- `dataloader_num_workers`: 0 +- `dataloader_prefetch_factor`: None +- `past_index`: -1 +- `disable_tqdm`: False +- `remove_unused_columns`: True +- `label_names`: None +- `load_best_model_at_end`: True +- `ignore_data_skip`: False +- `fsdp`: [] +- `fsdp_min_num_params`: 0 +- `fsdp_config`: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False} +- `fsdp_transformer_layer_cls_to_wrap`: None +- `accelerator_config`: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None} +- `deepspeed`: None +- `label_smoothing_factor`: 0.0 +- `optim`: adamw_torch_fused +- `optim_args`: None +- `adafactor`: False +- `group_by_length`: False +- `length_column_name`: length +- `ddp_find_unused_parameters`: None +- `ddp_bucket_cap_mb`: None +- `ddp_broadcast_buffers`: False +- `dataloader_pin_memory`: True +- `dataloader_persistent_workers`: False +- `skip_memory_metrics`: True +- `use_legacy_prediction_loop`: False +- `push_to_hub`: False +- `resume_from_checkpoint`: None +- `hub_model_id`: None +- `hub_strategy`: every_save +- `hub_private_repo`: 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 +- `batch_sampler`: no_duplicates +- `multi_dataset_batch_sampler`: proportional + +
+ +### Training Logs +
Click to expand + +| Epoch | Step | Training Loss | loss | dim_128_cosine_map@100 | dim_256_cosine_map@100 | dim_512_cosine_map@100 | dim_64_cosine_map@100 | dim_768_cosine_map@100 | +|:----------:|:------:|:-------------:|:----------:|:----------------------:|:----------------------:|:----------------------:|:---------------------:|:----------------------:| +| 0.2712 | 1 | 13.2713 | - | - | - | - | - | - | +| 0.5424 | 2 | 13.2895 | - | - | - | - | - | - | +| 0.8136 | 3 | 9.9139 | - | - | - | - | - | - | +| 1.0847 | 4 | 5.6117 | - | - | - | - | - | - | +| 1.3559 | 5 | 4.7571 | - | - | - | - | - | - | +| 1.6271 | 6 | 5.5215 | - | - | - | - | - | - | +| 1.8983 | 7 | 5.7945 | - | - | - | - | - | - | +| 2.1695 | 8 | 5.7064 | - | - | - | - | - | - | +| 2.4407 | 9 | 5.6794 | - | - | - | - | - | - | +| 2.7119 | 10 | 5.7384 | - | - | - | - | - | - | +| 2.9831 | 11 | 5.6081 | - | - | - | - | - | - | +| 3.2542 | 12 | 5.5278 | - | - | - | - | - | - | +| 3.5254 | 13 | 5.149 | - | - | - | - | - | - | +| 3.7966 | 14 | 5.5904 | 5.6043 | 0.0081 | 0.0072 | 0.0079 | 0.0055 | 0.0079 | +| 1.0169 | 15 | 3.9458 | - | - | - | - | - | - | +| 1.2881 | 16 | 13.3653 | - | - | - | - | - | - | +| 1.5593 | 17 | 13.4413 | - | - | - | - | - | - | +| 1.8305 | 18 | 9.4188 | - | - | - | - | - | - | +| 2.1017 | 19 | 5.717 | - | - | - | - | - | - | +| 2.3729 | 20 | 5.2455 | - | - | - | - | - | - | +| 2.6441 | 21 | 5.2117 | - | - | - | - | - | - | +| 2.9153 | 22 | 5.5217 | - | - | - | - | - | - | +| 3.1864 | 23 | 5.6725 | - | - | - | - | - | - | +| 3.4576 | 24 | 5.786 | - | - | - | - | - | - | +| 3.7288 | 25 | 5.6507 | - | - | - | - | - | - | +| 4.0 | 26 | 5.7215 | - | - | - | - | - | - | +| 4.2712 | 27 | 5.3999 | - | - | - | - | - | - | +| 4.5424 | 28 | 5.4275 | - | - | - | - | - | - | +| 4.8136 | 29 | 5.7143 | 5.5718 | 0.0082 | 0.0071 | 0.0077 | 0.0052 | 0.0077 | +| 2.0339 | 30 | 4.478 | - | - | - | - | - | - | +| 2.3051 | 31 | 13.1821 | - | - | - | - | - | - | +| 2.5763 | 32 | 13.2473 | - | - | - | - | - | - | +| 2.8475 | 33 | 8.8654 | - | - | - | - | - | - | +| 3.1186 | 34 | 5.3181 | - | - | - | - | - | - | +| 3.3898 | 35 | 5.2091 | - | - | - | - | - | - | +| 3.6610 | 36 | 5.6027 | - | - | - | - | - | - | +| 3.9322 | 37 | 5.6839 | - | - | - | - | - | - | +| 4.2034 | 38 | 5.5955 | - | - | - | - | - | - | +| 4.4746 | 39 | 5.5786 | - | - | - | - | - | - | +| 4.7458 | 40 | 5.4509 | - | - | - | - | - | - | +| 5.0169 | 41 | 5.3361 | - | - | - | - | - | - | +| 5.2881 | 42 | 5.1608 | - | - | - | - | - | - | +| 5.5593 | 43 | 5.4896 | - | - | - | - | - | - | +| 5.8305 | 44 | 5.6466 | 5.5241 | 0.0062 | 0.0070 | 0.0076 | 0.0095 | 0.0076 | +| 3.0508 | 45 | 4.5617 | - | - | - | - | - | - | +| 3.3220 | 46 | 13.0665 | - | - | - | - | - | - | +| 3.5932 | 47 | 13.1848 | - | - | - | - | - | - | +| 3.8644 | 48 | 8.4053 | - | - | - | - | - | - | +| 4.1356 | 49 | 5.2706 | - | - | - | - | - | - | +| 4.4068 | 50 | 5.4269 | - | - | - | - | - | - | +| 4.6780 | 51 | 5.3645 | - | - | - | - | - | - | +| 4.9492 | 52 | 5.3587 | - | - | - | - | - | - | +| 5.2203 | 53 | 5.1047 | - | - | - | - | - | - | +| 5.4915 | 54 | 5.743 | - | - | - | - | - | - | +| 5.7627 | 55 | 5.3754 | - | - | - | - | - | - | +| 6.0339 | 56 | 5.3021 | - | - | - | - | - | - | +| 6.3051 | 57 | 5.6983 | - | - | - | - | - | - | +| 6.5763 | 58 | 5.302 | - | - | - | - | - | - | +| 6.8475 | 59 | 5.4545 | 5.4638 | 0.0060 | 0.0070 | 0.0077 | 0.0094 | 0.0077 | +| 4.0678 | 60 | 5.2213 | - | - | - | - | - | - | +| 4.3390 | 61 | 12.9854 | - | - | - | - | - | - | +| 4.6102 | 62 | 13.207 | - | - | - | - | - | - | +| 4.8814 | 63 | 7.7493 | - | - | - | - | - | - | +| 5.1525 | 64 | 5.3787 | - | - | - | - | - | - | +| 5.4237 | 65 | 4.9406 | - | - | - | - | - | - | +| 5.6949 | 66 | 5.3963 | - | - | - | - | - | - | +| 5.9661 | 67 | 5.3429 | - | - | - | - | - | - | +| 6.2373 | 68 | 5.292 | - | - | - | - | - | - | +| 6.5085 | 69 | 5.6738 | - | - | - | - | - | - | +| 6.7797 | 70 | 5.5927 | - | - | - | - | - | - | +| 7.0508 | 71 | 5.5245 | - | - | - | - | - | - | +| 7.3220 | 72 | 4.8334 | - | - | - | - | - | - | +| 7.5932 | 73 | 5.2015 | - | - | - | - | - | - | +| 7.8644 | 74 | 5.5393 | 5.3954 | 0.0060 | 0.0071 | 0.0078 | 0.0094 | 0.0078 | +| 5.0847 | 75 | 5.6168 | - | - | - | - | - | - | +| 5.3559 | 76 | 12.8678 | - | - | - | - | - | - | +| 5.6271 | 77 | 13.2377 | - | - | - | - | - | - | +| 5.8983 | 78 | 7.1882 | - | - | - | - | - | - | +| 6.1695 | 79 | 5.1293 | - | - | - | - | - | - | +| 6.4407 | 80 | 4.9413 | - | - | - | - | - | - | +| 6.7119 | 81 | 5.1763 | - | - | - | - | - | - | +| 6.9831 | 82 | 4.9512 | - | - | - | - | - | - | +| 7.2542 | 83 | 5.2744 | - | - | - | - | - | - | +| 7.5254 | 84 | 5.0573 | - | - | - | - | - | - | +| 7.7966 | 85 | 5.1938 | - | - | - | - | - | - | +| 8.0678 | 86 | 5.1514 | - | - | - | - | - | - | +| 8.3390 | 87 | 4.9808 | - | - | - | - | - | - | +| 8.6102 | 88 | 4.9983 | - | - | - | - | - | - | +| **8.8814** | **89** | **5.3211** | **5.3268** | **0.0062** | **0.0067** | **0.0075** | **0.0095** | **0.0075** | +| 6.1017 | 90 | 6.1513 | - | - | - | - | - | - | +| 6.3729 | 91 | 12.7972 | - | - | - | - | - | - | +| 6.6441 | 92 | 13.0051 | - | - | - | - | - | - | +| 6.9153 | 93 | 6.551 | - | - | - | - | - | - | +| 7.1864 | 94 | 4.6644 | - | - | - | - | - | - | +| 7.4576 | 95 | 4.8619 | - | - | - | - | - | - | +| 7.7288 | 96 | 5.0812 | - | - | - | - | - | - | +| 8.0 | 97 | 4.758 | - | - | - | - | - | - | +| 8.2712 | 98 | 5.1362 | - | - | - | - | - | - | +| 8.5424 | 99 | 5.5405 | - | - | - | - | - | - | +| 8.8136 | 100 | 5.228 | - | - | - | - | - | - | +| 9.0847 | 101 | 5.1084 | - | - | - | - | - | - | +| 9.3559 | 102 | 5.1574 | - | - | - | - | - | - | +| 9.6271 | 103 | 5.3326 | - | - | - | - | - | - | +| 9.8983 | 104 | 5.34 | 5.2658 | 0.0060 | 0.0066 | 0.0076 | 0.0052 | 0.0076 | +| 7.1186 | 105 | 6.5789 | - | - | - | - | - | - | +| 7.3898 | 106 | 12.7557 | - | - | - | - | - | - | +| 7.6610 | 107 | 13.0203 | - | - | - | - | - | - | +| 7.9322 | 108 | 5.7148 | - | - | - | - | - | - | +| 8.2034 | 109 | 4.7945 | - | - | - | - | - | - | +| 8.4746 | 110 | 4.5926 | - | - | - | - | - | - | +| 8.7458 | 111 | 4.6727 | - | - | - | - | - | - | +| 9.0169 | 112 | 5.0886 | - | - | - | - | - | - | +| 9.2881 | 113 | 5.0562 | - | - | - | - | - | - | +| 9.5593 | 114 | 5.2167 | - | - | - | - | - | - | +| 9.8305 | 115 | 5.048 | - | - | - | - | - | - | +| 10.1017 | 116 | 4.7765 | - | - | - | - | - | - | +| 10.3729 | 117 | 4.9875 | - | - | - | - | - | - | +| 10.6441 | 118 | 4.9501 | - | - | - | - | - | - | +| 10.9153 | 119 | 4.756 | 5.2124 | 0.0057 | 0.0065 | 0.0075 | 0.0054 | 0.0075 | +| 8.1356 | 120 | 6.9381 | - | - | - | - | - | - | +| 8.4068 | 121 | 12.7916 | - | - | - | - | - | - | +| 8.6780 | 122 | 12.8517 | - | - | - | - | - | - | +| 8.9492 | 123 | 5.51 | - | - | - | - | - | - | +| 9.2203 | 124 | 4.686 | - | - | - | - | - | - | +| 9.4915 | 125 | 4.6611 | - | - | - | - | - | - | +| 9.7627 | 126 | 5.2767 | - | - | - | - | - | - | +| 10.0339 | 127 | 4.6103 | - | - | - | - | - | - | +| 10.3051 | 128 | 4.957 | - | - | - | - | - | - | +| 10.5763 | 129 | 5.0236 | - | - | - | - | - | - | +| 10.8475 | 130 | 5.0894 | - | - | - | - | - | - | +| 11.1186 | 131 | 4.7025 | - | - | - | - | - | - | +| 11.3898 | 132 | 5.0765 | - | - | - | - | - | - | +| 11.6610 | 133 | 4.6601 | - | - | - | - | - | - | +| 11.9322 | 134 | 4.9064 | 5.1731 | 0.0056 | 0.0060 | 0.0070 | 0.0054 | 0.0070 | +| 9.1525 | 135 | 7.5884 | - | - | - | - | - | - | +| 9.4237 | 136 | 12.679 | - | - | - | - | - | - | +| 9.6949 | 137 | 12.417 | - | - | - | - | - | - | +| 9.9661 | 138 | 5.1632 | - | - | - | - | - | - | +| 10.2373 | 139 | 4.9486 | - | - | - | - | - | - | +| 10.5085 | 140 | 4.6341 | - | - | - | - | - | - | +| 10.7797 | 141 | 4.9664 | - | - | - | - | - | - | +| 11.0508 | 142 | 4.9567 | - | - | - | - | - | - | +| 11.3220 | 143 | 4.7532 | - | - | - | - | - | - | +| 11.5932 | 144 | 5.2556 | - | - | - | - | - | - | +| 11.8644 | 145 | 4.9652 | - | - | - | - | - | - | +| 12.1356 | 146 | 4.8118 | - | - | - | - | - | - | +| 12.4068 | 147 | 4.704 | - | - | - | - | - | - | +| 12.6780 | 148 | 4.8922 | - | - | - | - | - | - | +| 12.9492 | 149 | 4.6571 | 5.1441 | 0.0061 | 0.0055 | 0.0064 | 0.0053 | 0.0064 | +| 10.1695 | 150 | 8.1284 | - | - | - | - | - | - | +| 10.4407 | 151 | 12.5703 | - | - | - | - | - | - | +| 10.7119 | 152 | 11.8696 | - | - | - | - | - | - | +| 10.9831 | 153 | 4.8543 | - | - | - | - | - | - | +| 11.2542 | 154 | 4.8099 | - | - | - | - | - | - | +| 11.5254 | 155 | 4.7009 | - | - | - | - | - | - | +| 11.7966 | 156 | 4.7986 | - | - | - | - | - | - | +| 12.0678 | 157 | 4.7973 | - | - | - | - | - | - | +| 12.3390 | 158 | 4.5529 | - | - | - | - | - | - | +| 12.6102 | 159 | 5.0275 | - | - | - | - | - | - | +| 12.8814 | 160 | 4.6675 | - | - | - | - | - | - | +| 13.1525 | 161 | 4.6538 | - | - | - | - | - | - | +| 13.4237 | 162 | 4.8355 | - | - | - | - | - | - | +| 13.6949 | 163 | 4.6304 | - | - | - | - | - | - | +| 13.9661 | 164 | 4.7047 | 5.1242 | 0.0064 | 0.0054 | 0.0064 | 0.0095 | 0.0064 | +| 11.1864 | 165 | 8.6549 | - | - | - | - | - | - | +| 11.4576 | 166 | 12.4788 | - | - | - | - | - | - | +| 11.7288 | 167 | 11.6425 | - | - | - | - | - | - | +| 12.0 | 168 | 4.5654 | - | - | - | - | - | - | +| 12.2712 | 169 | 4.7016 | - | - | - | - | - | - | +| 12.5424 | 170 | 4.3306 | - | - | - | - | - | - | +| 12.8136 | 171 | 4.9692 | - | - | - | - | - | - | +| 13.0847 | 172 | 4.7557 | - | - | - | - | - | - | +| 13.3559 | 173 | 4.8665 | - | - | - | - | - | - | +| 13.6271 | 174 | 4.8338 | - | - | - | - | - | - | +| 13.8983 | 175 | 4.9221 | - | - | - | - | - | - | +| 14.1695 | 176 | 4.4968 | - | - | - | - | - | - | +| 14.4407 | 177 | 4.6104 | - | - | - | - | - | - | +| 14.7119 | 178 | 4.8449 | - | - | - | - | - | - | +| 14.9831 | 179 | 4.2392 | 5.1123 | 0.0059 | 0.0055 | 0.0065 | 0.0094 | 0.0065 | +| 12.2034 | 180 | 9.4893 | - | - | - | - | - | - | +| 12.4746 | 181 | 12.4241 | - | - | - | - | - | - | +| 12.7458 | 182 | 11.0389 | - | - | - | - | - | - | +| 13.0169 | 183 | 4.7595 | - | - | - | - | - | - | +| 13.2881 | 184 | 4.5408 | - | - | - | - | - | - | +| 13.5593 | 185 | 4.6108 | - | - | - | - | - | - | +| 13.8305 | 186 | 4.5832 | - | - | - | - | - | - | +| 14.1017 | 187 | 4.6741 | - | - | - | - | - | - | +| 14.3729 | 188 | 4.9353 | - | - | - | - | - | - | +| 14.6441 | 189 | 5.0511 | - | - | - | - | - | - | +| 14.9153 | 190 | 4.6575 | - | - | - | - | - | - | +| 15.1864 | 191 | 4.648 | - | - | - | - | - | - | +| 15.4576 | 192 | 4.6224 | - | - | - | - | - | - | +| 15.7288 | 193 | 4.9292 | - | - | - | - | - | - | +| 16.0 | 194 | 3.7805 | 5.1058 | 0.0063 | 0.0057 | 0.0062 | 0.0094 | 0.0062 | +| 13.2203 | 195 | 10.2695 | - | - | - | - | - | - | +| 13.4915 | 196 | 12.5043 | - | - | - | - | - | - | +| 13.7627 | 197 | 10.4795 | - | - | - | - | - | - | +| 14.0339 | 198 | 4.6901 | - | - | - | - | - | - | +| 14.3051 | 199 | 4.6538 | - | - | - | - | - | - | +| 14.5763 | 200 | 4.4736 | - | - | - | - | - | - | +| 14.8475 | 201 | 4.4383 | - | - | - | - | - | - | +| 15.1186 | 202 | 5.0382 | - | - | - | - | - | - | +| 15.3898 | 203 | 4.5636 | - | - | - | - | - | - | +| 15.6610 | 204 | 4.8089 | - | - | - | - | - | - | +| 15.9322 | 205 | 4.4746 | - | - | - | - | - | - | +| 16.2034 | 206 | 4.5876 | - | - | - | - | - | - | +| 16.4746 | 207 | 4.4972 | - | - | - | - | - | - | +| 16.7458 | 208 | 4.8569 | - | - | - | - | - | - | +| 17.0169 | 209 | 3.5883 | 5.1031 | 0.0059 | 0.0057 | 0.0061 | 0.0095 | 0.0061 | +| 14.2373 | 210 | 10.8988 | - | - | - | - | - | - | +| 14.5085 | 211 | 12.4944 | - | - | - | - | - | - | +| 14.7797 | 212 | 10.1041 | - | - | - | - | - | - | +| 15.0508 | 213 | 4.8811 | - | - | - | - | - | - | +| 15.3220 | 214 | 4.6292 | - | - | - | - | - | - | +| 15.5932 | 215 | 4.4828 | - | - | - | - | - | - | +| 15.8644 | 216 | 4.7588 | - | - | - | - | - | - | +| 16.1356 | 217 | 4.26 | - | - | - | - | - | - | +| 16.4068 | 218 | 4.9124 | - | - | - | - | - | - | +| 16.6780 | 219 | 4.8098 | - | - | - | - | - | - | +| 16.9492 | 220 | 4.4439 | - | - | - | - | - | - | +| 17.2203 | 221 | 4.4824 | - | - | - | - | - | - | +| 17.4915 | 222 | 4.7771 | - | - | - | - | - | - | +| 17.7627 | 223 | 4.5966 | - | - | - | - | - | - | +| 18.0339 | 224 | 3.1409 | 5.1009 | 0.0055 | 0.0057 | 0.0062 | 0.0052 | 0.0062 | +| 15.2542 | 225 | 11.657 | - | - | - | - | - | - | +| 15.5254 | 226 | 12.5032 | - | - | - | - | - | - | +| 15.7966 | 227 | 9.4495 | - | - | - | - | - | - | +| 16.0678 | 228 | 4.7099 | - | - | - | - | - | - | +| 16.3390 | 229 | 4.6049 | - | - | - | - | - | - | +| 16.6102 | 230 | 4.6311 | - | - | - | - | - | - | +| 16.8814 | 231 | 4.7562 | - | - | - | - | - | - | +| 17.1525 | 232 | 4.7195 | - | - | - | - | - | - | +| 17.4237 | 233 | 4.8557 | - | - | - | - | - | - | +| 17.6949 | 234 | 4.8423 | - | - | - | - | - | - | +| 17.9661 | 235 | 4.5764 | - | - | - | - | - | - | +| 18.2373 | 236 | 4.5081 | - | - | - | - | - | - | +| 18.5085 | 237 | 4.7974 | - | - | - | - | - | - | +| 18.7797 | 238 | 4.871 | - | - | - | - | - | - | +| 19.0508 | 239 | 2.8558 | 5.1020 | 0.0054 | 0.0057 | 0.0061 | 0.0054 | 0.0061 | +| 16.2712 | 240 | 12.4297 | - | - | - | - | - | - | +| 16.5424 | 241 | 12.5186 | - | - | - | - | - | - | +| 16.8136 | 242 | 8.8827 | - | - | - | - | - | - | +| 17.0847 | 243 | 4.8406 | - | - | - | - | - | - | +| 17.3559 | 244 | 4.4367 | - | - | - | - | - | - | +| 17.6271 | 245 | 4.5996 | - | - | - | - | - | - | +| 17.8983 | 246 | 4.6692 | - | - | - | - | - | - | +| 18.1695 | 247 | 4.6498 | - | - | - | - | - | - | +| 18.4407 | 248 | 4.7211 | - | - | - | - | - | - | +| 18.7119 | 249 | 4.7675 | - | - | - | - | - | - | +| 18.9831 | 250 | 4.4405 | - | - | - | - | - | - | +| 19.2542 | 251 | 4.6778 | - | - | - | - | - | - | +| 19.5254 | 252 | 4.6674 | - | - | - | - | - | - | +| 19.7966 | 253 | 4.735 | 5.1036 | 0.0054 | 0.0056 | 0.0060 | 0.0054 | 0.0060 | +| 17.0169 | 254 | 3.6188 | - | - | - | - | - | - | +| 17.2881 | 255 | 12.4112 | - | - | - | - | - | - | +| 17.5593 | 256 | 12.5261 | - | - | - | - | - | - | +| 17.8305 | 257 | 8.3408 | - | - | - | - | - | - | +| 18.1017 | 258 | 4.6496 | - | - | - | - | - | - | +| 18.3729 | 259 | 4.7177 | - | - | - | - | - | - | +| 18.6441 | 260 | 4.7956 | - | - | - | - | - | - | +| 18.9153 | 261 | 4.7228 | - | - | - | - | - | - | +| 19.1864 | 262 | 4.6083 | - | - | - | - | - | - | +| 19.4576 | 263 | 4.7985 | - | - | - | - | - | - | +| 19.7288 | 264 | 4.6675 | - | - | - | - | - | - | +| 20.0 | 265 | 4.6353 | - | - | - | - | - | - | +| 20.2712 | 266 | 4.5717 | - | - | - | - | - | - | +| 20.5424 | 267 | 4.4358 | - | - | - | - | - | - | +| 20.8136 | 268 | 4.8288 | 5.1030 | 0.0056 | 0.0057 | 0.0062 | 0.0053 | 0.0062 | +| 18.0339 | 269 | 3.7877 | - | - | - | - | - | - | +| 18.3051 | 270 | 12.4042 | - | - | - | - | - | - | +| 18.5763 | 271 | 12.4793 | - | - | - | - | - | - | +| 18.8475 | 272 | 7.9475 | - | - | - | - | - | - | +| 19.1186 | 273 | 4.5502 | - | - | - | - | - | - | +| 19.3898 | 274 | 4.5565 | - | - | - | - | - | - | +| 19.6610 | 275 | 4.4172 | - | - | - | - | - | - | +| 19.9322 | 276 | 4.5319 | - | - | - | - | - | - | +| 20.2034 | 277 | 4.5635 | - | - | - | - | - | - | +| 20.4746 | 278 | 4.5233 | - | - | - | - | - | - | +| 20.7458 | 279 | 4.6766 | - | - | - | - | - | - | +| 21.0169 | 280 | 4.5863 | - | - | - | - | - | - | +| 21.2881 | 281 | 4.5784 | - | - | - | - | - | - | +| 21.5593 | 282 | 4.7198 | - | - | - | - | - | - | +| 21.8305 | 283 | 4.7383 | 5.1065 | 0.0054 | 0.0056 | 0.0061 | 0.0050 | 0.0061 | +| 19.0508 | 284 | 4.4257 | - | - | - | - | - | - | +| 19.3220 | 285 | 12.3475 | - | - | - | - | - | - | +| 19.5932 | 286 | 12.5168 | - | - | - | - | - | - | +| 19.8644 | 287 | 7.3671 | - | - | - | - | - | - | +| 20.1356 | 288 | 4.3771 | - | - | - | - | - | - | +| 20.4068 | 289 | 4.542 | - | - | - | - | - | - | +| 20.6780 | 290 | 4.3629 | - | - | - | - | - | - | +| 20.9492 | 291 | 4.5474 | - | - | - | - | - | - | +| 21.2203 | 292 | 4.7436 | - | - | - | - | - | - | +| 21.4915 | 293 | 4.5915 | - | - | - | - | - | - | +| 21.7627 | 294 | 4.5522 | - | - | - | - | - | - | +| 22.0339 | 295 | 4.6591 | - | - | - | - | - | - | +| 22.3051 | 296 | 4.6179 | - | - | - | - | - | - | +| 22.5763 | 297 | 4.6086 | - | - | - | - | - | - | +| 22.8475 | 298 | 4.8808 | 5.1083 | 0.0054 | 0.0057 | 0.0062 | 0.0055 | 0.0062 | +| 20.0678 | 299 | 4.7358 | - | - | - | - | - | - | +| 20.3390 | 300 | 12.3209 | - | - | - | - | - | - | +| 20.6102 | 301 | 12.6406 | - | - | - | - | - | - | +| 20.8814 | 302 | 6.7971 | - | - | - | - | - | - | +| 21.1525 | 303 | 4.3723 | - | - | - | - | - | - | +| 21.4237 | 304 | 4.61 | - | - | - | - | - | - | +| 21.6949 | 305 | 4.4624 | - | - | - | - | - | - | +| 21.9661 | 306 | 4.6145 | - | - | - | - | - | - | +| 22.2373 | 307 | 4.5794 | - | - | - | - | - | - | +| 22.5085 | 308 | 4.6625 | - | - | - | - | - | - | +| 22.7797 | 309 | 4.5499 | - | - | - | - | - | - | +| 23.0508 | 310 | 4.5657 | - | - | - | - | - | - | +| 23.3220 | 311 | 4.5896 | - | - | - | - | - | - | +| 23.5932 | 312 | 4.5692 | - | - | - | - | - | - | +| 23.8644 | 313 | 4.93 | 5.1119 | 0.0055 | 0.0057 | 0.0061 | 0.0056 | 0.0061 | +| 21.0847 | 314 | 5.3829 | - | - | - | - | - | - | +| 21.3559 | 315 | 12.3422 | - | - | - | - | - | - | +| 21.6271 | 316 | 12.601 | - | - | - | - | - | - | +| 21.8983 | 317 | 6.5062 | - | - | - | - | - | - | +| 22.1695 | 318 | 4.4681 | - | - | - | - | - | - | +| 22.4407 | 319 | 4.4244 | - | - | - | - | - | - | +| 22.7119 | 320 | 4.4514 | - | - | - | - | - | - | +| 22.9831 | 321 | 4.5469 | - | - | - | - | - | - | +| 23.2542 | 322 | 4.6924 | - | - | - | - | - | - | +| 23.5254 | 323 | 4.682 | - | - | - | - | - | - | +| 23.7966 | 324 | 4.6403 | - | - | - | - | - | - | +| 24.0678 | 325 | 4.6272 | - | - | - | - | - | - | +| 24.3390 | 326 | 4.3605 | - | - | - | - | - | - | +| 24.6102 | 327 | 4.5992 | - | - | - | - | - | - | +| 24.8814 | 328 | 4.6776 | 5.1126 | 0.0053 | 0.0057 | 0.0061 | 0.0056 | 0.0061 | +| 22.1017 | 329 | 5.8504 | - | - | - | - | - | - | +| 22.3729 | 330 | 12.335 | - | - | - | - | - | - | +| 22.6441 | 331 | 12.5779 | - | - | - | - | - | - | +| 22.9153 | 332 | 5.7261 | - | - | - | - | - | - | +| 23.1864 | 333 | 4.5411 | - | - | - | - | - | - | +| 23.4576 | 334 | 4.4783 | - | - | - | - | - | - | +| 23.7288 | 335 | 4.5589 | - | - | - | - | - | - | +| 24.0 | 336 | 4.6305 | - | - | - | - | - | - | +| 24.2712 | 337 | 4.674 | - | - | - | - | - | - | +| 24.5424 | 338 | 4.7455 | - | - | - | - | - | - | +| 24.8136 | 339 | 4.6011 | - | - | - | - | - | - | +| 25.0847 | 340 | 4.5899 | - | - | - | - | - | - | +| 25.3559 | 341 | 4.3981 | - | - | - | - | - | - | +| 25.6271 | 342 | 4.7031 | - | - | - | - | - | - | +| 25.8983 | 343 | 4.68 | 5.1182 | 0.0054 | 0.0057 | 0.0059 | 0.0056 | 0.0059 | +| 23.1186 | 344 | 6.3521 | - | - | - | - | - | - | +| 23.3898 | 345 | 12.2283 | - | - | - | - | - | - | +| 23.6610 | 346 | 12.533 | - | - | - | - | - | - | +| 23.9322 | 347 | 5.2654 | - | - | - | - | - | - | +| 24.2034 | 348 | 4.3667 | - | - | - | - | - | - | +| 24.4746 | 349 | 4.4718 | - | - | - | - | - | - | +| 24.7458 | 350 | 4.6212 | - | - | - | - | - | - | +| 25.0169 | 351 | 4.447 | - | - | - | - | - | - | +| 25.2881 | 352 | 4.6247 | - | - | - | - | - | - | +| 25.5593 | 353 | 5.0093 | - | - | - | - | - | - | +| 25.8305 | 354 | 4.6316 | - | - | - | - | - | - | +| 26.1017 | 355 | 4.6655 | - | - | - | - | - | - | +| 26.3729 | 356 | 4.5964 | - | - | - | - | - | - | +| 26.6441 | 357 | 4.682 | - | - | - | - | - | - | +| 26.9153 | 358 | 4.6375 | 5.1205 | 0.0051 | 0.0056 | 0.0059 | 0.0055 | 0.0059 | +| 24.1356 | 359 | 6.727 | - | - | - | - | - | - | +| 24.4068 | 360 | 12.3706 | - | - | - | - | - | - | +| 24.6780 | 361 | 12.4755 | - | - | - | - | - | - | +| 24.9492 | 362 | 4.623 | - | - | - | - | - | - | +| 25.2203 | 363 | 4.2947 | - | - | - | - | - | - | +| 25.4915 | 364 | 4.3993 | - | - | - | - | - | - | +| 25.7627 | 365 | 4.4148 | - | - | - | - | - | - | +| 26.0339 | 366 | 4.2376 | - | - | - | - | - | - | +| 26.3051 | 367 | 4.6334 | - | - | - | - | - | - | +| 26.5763 | 368 | 4.7007 | - | - | - | - | - | - | +| 26.8475 | 369 | 4.3542 | - | - | - | - | - | - | +| 27.1186 | 370 | 4.7036 | - | - | - | - | - | - | +| 27.3898 | 371 | 4.2382 | - | - | - | - | - | - | +| 27.6610 | 372 | 4.5011 | - | - | - | - | - | - | +| 27.9322 | 373 | 4.6292 | 5.1241 | 0.0051 | 0.0056 | 0.0059 | 0.0056 | 0.0059 | +| 25.1525 | 374 | 7.3562 | - | - | - | - | - | - | +| 25.4237 | 375 | 12.2926 | - | - | - | - | - | - | +| 25.6949 | 376 | 12.1694 | - | - | - | - | - | - | +| 25.9661 | 377 | 4.7183 | - | - | - | - | - | - | +| 26.2373 | 378 | 4.4099 | - | - | - | - | - | - | +| 26.5085 | 379 | 4.3366 | - | - | - | - | - | - | +| 26.7797 | 380 | 4.4848 | - | - | - | - | - | - | +| 27.0508 | 381 | 4.6947 | - | - | - | - | - | - | +| 27.3220 | 382 | 4.5683 | - | - | - | - | - | - | +| 27.5932 | 383 | 4.7691 | - | - | - | - | - | - | +| 27.8644 | 384 | 4.3879 | - | - | - | - | - | - | +| 28.1356 | 385 | 4.3461 | - | - | - | - | - | - | +| 28.4068 | 386 | 4.4756 | - | - | - | - | - | - | +| 28.6780 | 387 | 4.5355 | - | - | - | - | - | - | +| 28.9492 | 388 | 4.4837 | 5.1278 | 0.0052 | 0.0056 | 0.0059 | 0.0054 | 0.0059 | +| 26.1695 | 389 | 7.9407 | - | - | - | - | - | - | +| 26.4407 | 390 | 12.3054 | - | - | - | - | - | - | +| 26.7119 | 391 | 11.6158 | - | - | - | - | - | - | +| 26.9831 | 392 | 4.5724 | - | - | - | - | - | - | +| 27.2542 | 393 | 4.467 | - | - | - | - | - | - | +| 27.5254 | 394 | 4.4395 | - | - | - | - | - | - | +| 27.7966 | 395 | 4.4111 | - | - | - | - | - | - | +| 28.0678 | 396 | 4.5565 | - | - | - | - | - | - | +| 28.3390 | 397 | 4.6063 | - | - | - | - | - | - | +| 28.6102 | 398 | 4.5312 | - | - | - | - | - | - | +| 28.8814 | 399 | 4.5436 | - | - | - | - | - | - | +| 29.1525 | 400 | 4.5366 | - | - | - | - | - | - | +| 29.4237 | 401 | 4.4488 | - | - | - | - | - | - | +| 29.6949 | 402 | 4.5641 | - | - | - | - | - | - | +| 29.9661 | 403 | 4.2491 | 5.1303 | 0.0053 | 0.0057 | 0.0060 | 0.0055 | 0.0060 | +| 27.1864 | 404 | 8.574 | - | - | - | - | - | - | +| 27.4576 | 405 | 12.2836 | - | - | - | - | - | - | +| 27.7288 | 406 | 11.1935 | - | - | - | - | - | - | +| 28.0 | 407 | 4.5464 | - | - | - | - | - | - | +| 28.2712 | 408 | 4.3132 | - | - | - | - | - | - | +| 28.5424 | 409 | 4.3553 | - | - | - | - | - | - | +| 28.8136 | 410 | 4.4679 | - | - | - | - | - | - | +| 29.0847 | 411 | 4.7705 | - | - | - | - | - | - | +| 29.3559 | 412 | 4.5667 | - | - | - | - | - | - | +| 29.6271 | 413 | 4.6547 | - | - | - | - | - | - | +| 29.8983 | 414 | 4.6709 | - | - | - | - | - | - | +| 30.1695 | 415 | 4.784 | - | - | - | - | - | - | +| 30.4407 | 416 | 4.4368 | - | - | - | - | - | - | +| 30.7119 | 417 | 4.6159 | - | - | - | - | - | - | +| 30.9831 | 418 | 4.0117 | 5.1322 | 0.0050 | 0.0057 | 0.0059 | 0.0054 | 0.0059 | +| 28.2034 | 419 | 9.2905 | - | - | - | - | - | - | +| 28.4746 | 420 | 12.2439 | - | - | - | - | - | - | +| 28.7458 | 421 | 10.722 | - | - | - | - | - | - | +| 29.0169 | 422 | 4.6608 | - | - | - | - | - | - | +| 29.2881 | 423 | 4.5196 | - | - | - | - | - | - | +| 29.5593 | 424 | 4.4313 | - | - | - | - | - | - | +| 29.8305 | 425 | 4.513 | - | - | - | - | - | - | +| 30.1017 | 426 | 4.5812 | - | - | - | - | - | - | +| 30.3729 | 427 | 4.5275 | - | - | - | - | - | - | +| 30.6441 | 428 | 4.8022 | - | - | - | - | - | - | +| 30.9153 | 429 | 4.5171 | - | - | - | - | - | - | +| 31.1864 | 430 | 4.5968 | - | - | - | - | - | - | +| 31.4576 | 431 | 4.2145 | - | - | - | - | - | - | +| 31.7288 | 432 | 4.7041 | - | - | - | - | - | - | +| 32.0 | 433 | 3.6187 | 5.1356 | 0.0051 | 0.0057 | 0.0059 | 0.0055 | 0.0059 | +| 29.2203 | 434 | 10.0897 | - | - | - | - | - | - | +| 29.4915 | 435 | 12.2909 | - | - | - | - | - | - | +| 29.7627 | 436 | 10.1362 | - | - | - | - | - | - | +| 30.0339 | 437 | 4.5172 | - | - | - | - | - | - | +| 30.3051 | 438 | 4.3273 | - | - | - | - | - | - | +| 30.5763 | 439 | 4.5272 | - | - | - | - | - | - | +| 30.8475 | 440 | 4.376 | - | - | - | - | - | - | +| 31.1186 | 441 | 4.5803 | - | - | - | - | - | - | +| 31.3898 | 442 | 4.5654 | - | - | - | - | - | - | +| 31.6610 | 443 | 4.5024 | - | - | - | - | - | - | +| 31.9322 | 444 | 4.5889 | - | - | - | - | - | - | +| 32.2034 | 445 | 4.6489 | - | - | - | - | - | - | +| 32.4746 | 446 | 4.4505 | - | - | - | - | - | - | +| 32.7458 | 447 | 4.7026 | - | - | - | - | - | - | +| 33.0169 | 448 | 3.4719 | 5.1368 | 0.0050 | 0.0056 | 0.0059 | 0.0052 | 0.0059 | +| 30.2373 | 449 | 10.7633 | - | - | - | - | - | - | +| 30.5085 | 450 | 12.3203 | - | - | - | - | - | - | +| 30.7797 | 451 | 9.7535 | - | - | - | - | - | - | +| 31.0508 | 452 | 4.7462 | - | - | - | - | - | - | +| 31.3220 | 453 | 4.4271 | - | - | - | - | - | - | +| 31.5932 | 454 | 4.4347 | - | - | - | - | - | - | +| 31.8644 | 455 | 4.6443 | - | - | - | - | - | - | +| 32.1356 | 456 | 4.6344 | - | - | - | - | - | - | +| 32.4068 | 457 | 4.6518 | - | - | - | - | - | - | +| 32.6780 | 458 | 4.6437 | - | - | - | - | - | - | +| 32.9492 | 459 | 4.6168 | - | - | - | - | - | - | +| 33.2203 | 460 | 4.4948 | - | - | - | - | - | - | +| 33.4915 | 461 | 4.5268 | - | - | - | - | - | - | +| 33.7627 | 462 | 4.4844 | - | - | - | - | - | - | +| 34.0339 | 463 | 3.276 | 5.1384 | 0.0051 | 0.0057 | 0.0060 | 0.0053 | 0.0060 | +| 31.2542 | 464 | 11.5311 | - | - | - | - | - | - | +| 31.5254 | 465 | 12.3812 | - | - | - | - | - | - | +| 31.7966 | 466 | 9.1499 | - | - | - | - | - | - | +| 32.0678 | 467 | 4.7032 | - | - | - | - | - | - | +| 32.3390 | 468 | 4.2429 | - | - | - | - | - | - | +| 32.6102 | 469 | 4.549 | - | - | - | - | - | - | +| 32.8814 | 470 | 4.7083 | - | - | - | - | - | - | +| 33.1525 | 471 | 4.5348 | - | - | - | - | - | - | +| 33.4237 | 472 | 4.472 | - | - | - | - | - | - | +| 33.6949 | 473 | 4.5818 | - | - | - | - | - | - | +| 33.9661 | 474 | 4.5534 | - | - | - | - | - | - | +| 34.2373 | 475 | 4.5743 | - | - | - | - | - | - | +| 34.5085 | 476 | 4.54 | - | - | - | - | - | - | +| 34.7797 | 477 | 4.681 | - | - | - | - | - | - | +| 35.0508 | 478 | 2.9902 | 5.1397 | 0.0052 | 0.0057 | 0.0059 | 0.0053 | 0.0059 | +| 32.2712 | 479 | 12.3174 | - | - | - | - | - | - | +| 32.5424 | 480 | 12.2996 | - | - | - | - | - | - | +| 32.8136 | 481 | 8.7153 | - | - | - | - | - | - | +| 33.0847 | 482 | 4.5692 | - | - | - | - | - | - | +| 33.3559 | 483 | 4.3255 | - | - | - | - | - | - | +| 33.6271 | 484 | 4.4515 | - | - | - | - | - | - | +| 33.8983 | 485 | 4.6708 | - | - | - | - | - | - | +| 34.1695 | 486 | 4.2648 | - | - | - | - | - | - | +| 34.4407 | 487 | 4.6268 | - | - | - | - | - | - | +| 34.7119 | 488 | 4.703 | - | - | - | - | - | - | +| 34.9831 | 489 | 4.6269 | - | - | - | - | - | - | +| 35.2542 | 490 | 4.6464 | - | - | - | - | - | - | +| 35.5254 | 491 | 4.4952 | - | - | - | - | - | - | +| 35.7966 | 492 | 4.6097 | 5.1406 | 0.0052 | 0.0058 | 0.0058 | 0.0054 | 0.0058 | +| 33.0169 | 493 | 3.2718 | - | - | - | - | - | - | +| 33.2881 | 494 | 12.3329 | - | - | - | - | - | - | +| 33.5593 | 495 | 12.3503 | - | - | - | - | - | - | +| 33.8305 | 496 | 8.1544 | - | - | - | - | - | - | +| 34.1017 | 497 | 4.4684 | - | - | - | - | - | - | +| 34.3729 | 498 | 4.4062 | - | - | - | - | - | - | +| 34.6441 | 499 | 4.2644 | - | - | - | - | - | - | +| 34.9153 | 500 | 4.5294 | - | - | - | - | - | - | +| 35.1864 | 501 | 4.673 | - | - | - | - | - | - | +| 35.4576 | 502 | 4.4884 | - | - | - | - | - | - | +| 35.7288 | 503 | 4.5989 | - | - | - | - | - | - | +| 36.0 | 504 | 4.6182 | - | - | - | - | - | - | +| 36.2712 | 505 | 4.6487 | - | - | - | - | - | - | +| 36.5424 | 506 | 4.6436 | - | - | - | - | - | - | +| 36.8136 | 507 | 4.6059 | 5.1417 | 0.0051 | 0.0057 | 0.0059 | 0.0052 | 0.0059 | +| 34.0339 | 508 | 3.7589 | - | - | - | - | - | - | +| 34.3051 | 509 | 12.2815 | - | - | - | - | - | - | +| 34.5763 | 510 | 12.5481 | - | - | - | - | - | - | +| 34.8475 | 511 | 7.6339 | - | - | - | - | - | - | +| 35.1186 | 512 | 4.5528 | - | - | - | - | - | - | +| 35.3898 | 513 | 4.3266 | - | - | - | - | - | - | +| 35.6610 | 514 | 4.3093 | - | - | - | - | - | - | +| 35.9322 | 515 | 4.7401 | - | - | - | - | - | - | +| 36.2034 | 516 | 4.523 | - | - | - | - | - | - | +| 36.4746 | 517 | 4.5255 | - | - | - | - | - | - | +| 36.7458 | 518 | 4.5058 | - | - | - | - | - | - | +| 37.0169 | 519 | 4.5614 | - | - | - | - | - | - | +| 37.2881 | 520 | 4.5323 | - | - | - | - | - | - | +| 37.5593 | 521 | 4.5739 | - | - | - | - | - | - | +| 37.8305 | 522 | 4.6501 | 5.1427 | 0.0052 | 0.0058 | 0.0059 | 0.0053 | 0.0059 | +| 35.0508 | 523 | 4.2083 | - | - | - | - | - | - | +| 35.3220 | 524 | 12.2888 | - | - | - | - | - | - | +| 35.5932 | 525 | 12.4709 | - | - | - | - | - | - | +| 35.8644 | 526 | 7.3926 | - | - | - | - | - | - | +| 36.1356 | 527 | 4.4719 | - | - | - | - | - | - | +| 36.4068 | 528 | 4.5033 | - | - | - | - | - | - | +| 36.6780 | 529 | 4.388 | - | - | - | - | - | - | +| 36.9492 | 530 | 4.5606 | - | - | - | - | - | - | +| 37.2203 | 531 | 4.6936 | - | - | - | - | - | - | +| 37.4915 | 532 | 4.6008 | - | - | - | - | - | - | +| 37.7627 | 533 | 4.6973 | - | - | - | - | - | - | +| 38.0339 | 534 | 4.4194 | - | - | - | - | - | - | +| 38.3051 | 535 | 4.5616 | - | - | - | - | - | - | +| 38.5763 | 536 | 4.6307 | - | - | - | - | - | - | +| 38.8475 | 537 | 4.8322 | 5.1442 | 0.0051 | 0.0057 | 0.0059 | 0.0053 | 0.0059 | +| 36.0678 | 538 | 4.8388 | - | - | - | - | - | - | +| 36.3390 | 539 | 12.2334 | - | - | - | - | - | - | +| 36.6102 | 540 | 12.4205 | - | - | - | - | - | - | +| 36.8814 | 541 | 6.9051 | - | - | - | - | - | - | +| 37.1525 | 542 | 4.6011 | - | - | - | - | - | - | +| 37.4237 | 543 | 4.4701 | - | - | - | - | - | - | +| 37.6949 | 544 | 4.421 | - | - | - | - | - | - | +| 37.9661 | 545 | 4.6877 | - | - | - | - | - | - | +| 38.2373 | 546 | 4.6348 | - | - | - | - | - | - | +| 38.5085 | 547 | 4.5822 | - | - | - | - | - | - | +| 38.7797 | 548 | 4.5697 | - | - | - | - | - | - | +| 39.0508 | 549 | 4.3118 | - | - | - | - | - | - | +| 39.3220 | 550 | 4.5131 | - | - | - | - | - | - | +| 39.5932 | 551 | 4.4879 | - | - | - | - | - | - | +| 39.8644 | 552 | 4.5945 | 5.1429 | 0.0052 | 0.0056 | 0.0059 | 0.0054 | 0.0059 | +| 37.0847 | 553 | 5.4083 | - | - | - | - | - | - | +| 37.3559 | 554 | 12.2092 | - | - | - | - | - | - | +| 37.6271 | 555 | 12.5043 | - | - | - | - | - | - | +| 37.8983 | 556 | 6.1239 | - | - | - | - | - | - | +| 38.1695 | 557 | 4.2932 | - | - | - | - | - | - | +| 38.4407 | 558 | 4.3845 | - | - | - | - | - | - | +| 38.7119 | 559 | 4.5619 | - | - | - | - | - | - | +| 38.9831 | 560 | 4.6936 | - | - | - | - | - | - | +| 39.2542 | 561 | 4.6636 | - | - | - | - | - | - | +| 39.5254 | 562 | 4.7964 | - | - | - | - | - | - | +| 39.7966 | 563 | 4.613 | - | - | - | - | - | - | +| 40.0678 | 564 | 4.5856 | - | - | - | - | - | - | +| 40.3390 | 565 | 4.4605 | - | - | - | - | - | - | +| 40.6102 | 566 | 4.5461 | - | - | - | - | - | - | +| 40.8814 | 567 | 4.7145 | 5.1454 | 0.0052 | 0.0056 | 0.0059 | 0.0052 | 0.0059 | +| 38.1017 | 568 | 5.8311 | - | - | - | - | - | - | +| 38.3729 | 569 | 12.2142 | - | - | - | - | - | - | +| 38.6441 | 570 | 12.4489 | - | - | - | - | - | - | +| 38.9153 | 571 | 5.7328 | - | - | - | - | - | - | +| 39.1864 | 572 | 4.4402 | - | - | - | - | - | - | +| 39.4576 | 573 | 4.1806 | - | - | - | - | - | - | +| 39.7288 | 574 | 4.6327 | - | - | - | - | - | - | +| 40.0 | 575 | 4.2768 | - | - | - | - | - | - | +| 40.2712 | 576 | 4.4669 | - | - | - | - | - | - | +| 40.5424 | 577 | 4.8094 | - | - | - | - | - | - | +| 40.8136 | 578 | 4.5773 | - | - | - | - | - | - | +| 41.0847 | 579 | 4.439 | - | - | - | - | - | - | +| 41.3559 | 580 | 4.5718 | - | - | - | - | - | - | +| 41.6271 | 581 | 4.5955 | - | - | - | - | - | - | +| 41.8983 | 582 | 4.5043 | 5.1443 | 0.0051 | 0.0056 | 0.0059 | 0.0054 | 0.0059 | +| 39.1186 | 583 | 6.359 | - | - | - | - | - | - | +| 39.3898 | 584 | 12.212 | - | - | - | - | - | - | +| 39.6610 | 585 | 12.538 | - | - | - | - | - | - | +| 39.9322 | 586 | 5.0971 | - | - | - | - | - | - | +| 40.2034 | 587 | 4.4783 | - | - | - | - | - | - | +| 40.4746 | 588 | 4.394 | - | - | - | - | - | - | +| 40.7458 | 589 | 4.4847 | - | - | - | - | - | - | +| 41.0169 | 590 | 4.4116 | - | - | - | - | - | - | +| 41.2881 | 591 | 4.3979 | - | - | - | - | - | - | +| 41.5593 | 592 | 4.6652 | - | - | - | - | - | - | +| 41.8305 | 593 | 4.3939 | - | - | - | - | - | - | +| 42.1017 | 594 | 4.5555 | - | - | - | - | - | - | +| 42.3729 | 595 | 4.4966 | - | - | - | - | - | - | +| 42.6441 | 596 | 4.6267 | - | - | - | - | - | - | +| 42.9153 | 597 | 4.5834 | 5.1446 | 0.0051 | 0.0057 | 0.0058 | 0.0052 | 0.0058 | +| 40.1356 | 598 | 6.7009 | - | - | - | - | - | - | +| 40.4068 | 599 | 12.2755 | - | - | - | - | - | - | +| 40.6780 | 600 | 12.4465 | 5.1447 | 0.0052 | 0.0057 | 0.0059 | 0.0052 | 0.0059 | + +* The bold row denotes the saved checkpoint. +
+ +### Framework Versions +- Python: 3.10.12 +- Sentence Transformers: 3.0.1 +- Transformers: 4.41.2 +- PyTorch: 2.1.2+cu121 +- Accelerate: 0.31.0 +- Datasets: 2.19.1 +- Tokenizers: 0.19.1 + +## Citation + +### BibTeX + +#### Sentence Transformers +```bibtex +@inproceedings{reimers-2019-sentence-bert, + title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks", + author = "Reimers, Nils and Gurevych, Iryna", + booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing", + month = "11", + year = "2019", + publisher = "Association for Computational Linguistics", + url = "https://arxiv.org/abs/1908.10084", +} +``` + +#### MatryoshkaLoss +```bibtex +@misc{kusupati2024matryoshka, + title={Matryoshka Representation Learning}, + author={Aditya Kusupati and Gantavya Bhatt and Aniket Rege and Matthew Wallingford and Aditya Sinha and Vivek Ramanujan and William Howard-Snyder and Kaifeng Chen and Sham Kakade and Prateek Jain and Ali Farhadi}, + year={2024}, + eprint={2205.13147}, + archivePrefix={arXiv}, + primaryClass={cs.LG} +} +``` + +#### MultipleNegativesRankingLoss +```bibtex +@misc{henderson2017efficient, + title={Efficient Natural Language Response Suggestion for Smart Reply}, + author={Matthew Henderson and Rami Al-Rfou and Brian Strope and Yun-hsuan Sung and Laszlo Lukacs and Ruiqi Guo and Sanjiv Kumar and Balint Miklos and Ray Kurzweil}, + year={2017}, + eprint={1705.00652}, + archivePrefix={arXiv}, + primaryClass={cs.CL} +} +``` + + + + + + \ No newline at end of file