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pankajrajdeo
/
Bioformer-16L-UMLS-1.00

Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
Generated from Trainer
dataset_size:187491593
loss:CustomTripletLoss
text-embeddings-inference
Inference Endpoints
Model card Files Community
pankajrajdeo commited on
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Add new SentenceTransformer model

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Files changed (11) hide show
  1. 1_Pooling/config.json +10 -0
  2. README.md +2240 -0
  3. config.json +25 -0
  4. config_sentence_transformers.json +10 -0
  5. model.safetensors +3 -0
  6. modules.json +14 -0
  7. sentence_bert_config.json +4 -0
  8. special_tokens_map.json +37 -0
  9. tokenizer.json +0 -0
  10. tokenizer_config.json +64 -0
  11. vocab.txt +0 -0
1_Pooling/config.json ADDED
@@ -0,0 +1,10 @@
 
 
 
 
 
 
 
 
 
 
 
1
+ {
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+ "word_embedding_dimension": 384,
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+ "pooling_mode_cls_token": false,
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+ "pooling_mode_mean_tokens": true,
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+ "pooling_mode_max_tokens": false,
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+ "pooling_mode_mean_sqrt_len_tokens": false,
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+ "pooling_mode_weightedmean_tokens": false,
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+ "pooling_mode_lasttoken": false,
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+ "include_prompt": true
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+ }
README.md ADDED
@@ -0,0 +1,2240 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ library_name: sentence-transformers
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+ pipeline_tag: sentence-similarity
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+ tags:
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+ - sentence-transformers
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+ - sentence-similarity
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+ - feature-extraction
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+ - generated_from_trainer
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+ - dataset_size:187491593
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+ - loss:CustomTripletLoss
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+ widget:
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+ - source_sentence: 1.2 ML temsirolimus 25 MG/ML Injection
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+ sentences:
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+ - Temsirolimus 25 MG/1 ML Intravenous Solution
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+ - C3537356
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+ - C1949367
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+ - 0.5 ML influenza A virus vaccine, A-Victoria-361-2011 (H3N2)-like virus 0.03 MG/ML
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+ / influenza A-California-7-2009-(H1N1)v-like virus vaccine 0.03 MG/ML / influenza
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+ B virus vaccine B/Brisbane/60/2008 antigen 0.03 MG/ML / influenza B virus vaccine,
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+ B-Massachusetts-2-2012-like virus 0.03 MG/ML Prefilled Syringe [Fluzone Quadrivalent
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+ 2013-2014 Formula]
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+ - source_sentence: spastic ataxia type 2
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+ sentences:
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+ - ZPLD2P gene
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+ - C5240110
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+ - Kinesin Family Member 1C wt Allele
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+ - C5443974
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+ - source_sentence: アルコール性発作
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+ sentences:
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+ - C0586323
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+ - C4295585
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+ - epilepsy; alcohol
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+ - HELLP syndrome second trimester
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+ - source_sentence: Tergitol
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+ sentences:
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+ - C0439129
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+ - F 82526
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+ - C1563639
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+ - CD 3 color developer, sulfate, hydrate (2:3:1)
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+ - source_sentence: Albendazol
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+ sentences:
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+ - N-(p-(((2,4-diamino-5-methyl-6-quinazolinyl)methyl)amino)benzoyl)-L-glutamic acid
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+ - C0699923
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+ - C0130494
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+ - SKF-92058
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+ ---
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+
48
+ # SentenceTransformer
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+
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+ This is a [sentence-transformers](https://www.SBERT.net) model trained. 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.
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+
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+ ## Model Details
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+
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+ ### Model Description
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+ - **Model Type:** Sentence Transformer
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+ <!-- - **Base model:** [Unknown](https://huggingface.co/unknown) -->
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+ - **Maximum Sequence Length:** 1024 tokens
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+ - **Output Dimensionality:** 384 tokens
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+ - **Similarity Function:** Cosine Similarity
60
+ <!-- - **Training Dataset:** Unknown -->
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+ <!-- - **Language:** Unknown -->
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+ <!-- - **License:** Unknown -->
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+
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+ ### Model Sources
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+
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+ - **Documentation:** [Sentence Transformers Documentation](https://sbert.net)
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+ - **Repository:** [Sentence Transformers on GitHub](https://github.com/UKPLab/sentence-transformers)
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+ - **Hugging Face:** [Sentence Transformers on Hugging Face](https://huggingface.co/models?library=sentence-transformers)
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+
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+ ### Full Model Architecture
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+
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+ ```
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+ SentenceTransformer(
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+ (0): Transformer({'max_seq_length': 1024, 'do_lower_case': False}) with Transformer model: BertModel
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+ (1): Pooling({'word_embedding_dimension': 384, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
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+ )
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+ ```
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+
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+ ## Usage
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+
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+ ### Direct Usage (Sentence Transformers)
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+
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+ First install the Sentence Transformers library:
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+
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+ ```bash
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+ pip install -U sentence-transformers
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+ ```
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+
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+ Then you can load this model and run inference.
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+ ```python
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+ from sentence_transformers import SentenceTransformer
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+
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+ # Download from the 🤗 Hub
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+ model = SentenceTransformer("pankajrajdeo/3749828_bioformer_16L")
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+ # Run inference
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+ sentences = [
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+ 'Albendazol',
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+ 'SKF-92058',
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+ 'C0130494',
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+ ]
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+ embeddings = model.encode(sentences)
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+ print(embeddings.shape)
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+ # [3, 384]
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+
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+ # Get the similarity scores for the embeddings
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+ similarities = model.similarity(embeddings, embeddings)
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+ print(similarities.shape)
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+ # [3, 3]
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+ ```
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+
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+ <!--
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+ ### Direct Usage (Transformers)
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+
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+ <details><summary>Click to see the direct usage in Transformers</summary>
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+
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+ </details>
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+ -->
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+
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+ <!--
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+ ### Downstream Usage (Sentence Transformers)
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+
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+ You can finetune this model on your own dataset.
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+
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+ <details><summary>Click to expand</summary>
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+
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+ </details>
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+ -->
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+
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+ <!--
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+ ### Out-of-Scope Use
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+
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+ *List how the model may foreseeably be misused and address what users ought not to do with the model.*
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+ -->
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+
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+ <!--
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+ ## Bias, Risks and Limitations
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+
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+ *What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.*
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+ -->
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+
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+ <!--
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+ ### Recommendations
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+
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+ *What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*
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+ -->
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+
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+ ## Training Details
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+
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+ ### Training Dataset
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+
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+ #### Unnamed Dataset
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+
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+
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+ * Size: 187,491,593 training samples
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+ * Columns: <code>anchor</code>, <code>positive</code>, <code>negative_id</code>, <code>positive_id</code>, and <code>negative</code>
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+ * Approximate statistics based on the first 1000 samples:
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+ | | anchor | positive | negative_id | positive_id | negative |
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+ |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:--------------------------------------------------------------------------------|:--------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|
159
+ | type | string | string | string | string | string |
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+ | details | <ul><li>min: 3 tokens</li><li>mean: 13.27 tokens</li><li>max: 247 tokens</li></ul> | <ul><li>min: 3 tokens</li><li>mean: 12.25 tokens</li><li>max: 157 tokens</li></ul> | <ul><li>min: 5 tokens</li><li>mean: 6.27 tokens</li><li>max: 7 tokens</li></ul> | <ul><li>min: 5 tokens</li><li>mean: 6.49 tokens</li><li>max: 7 tokens</li></ul> | <ul><li>min: 3 tokens</li><li>mean: 13.53 tokens</li><li>max: 118 tokens</li></ul> |
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+ * Samples:
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+ | anchor | positive | negative_id | positive_id | negative |
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+ |:----------------------------------------------|:------------------------------------------------------------------------------------------------|:----------------------|:----------------------|:------------------------------------------------------------------------------------------------|
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+ | <code>Zaburzenie metabolizmu minerałów</code> | <code>Distúrbio não especificado do metabolismo de minerais</code> | <code>C2887914</code> | <code>C0154260</code> | <code>Acute alcoholic hepatic failure</code> |
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+ | <code>testy funkčnosti placenty</code> | <code>Metoder som brukes til å vurdere morkakefunksjon.</code> | <code>C2350391</code> | <code>C0032049</code> | <code>Hjärtmuskelscintigrafi</code> |
166
+ | <code>Tsefapiriin:Susc:Pt:Is:OrdQn</code> | <code>cefapirina:susceptibilidad:punto en el tiempo:cepa clínica:ordinal o cuantitativo:</code> | <code>C0942365</code> | <code>C0801894</code> | <code>2 proyecciones:hallazgo:punto en el tiempo:tobillo.izquierdo:Narrativo:radiografía</code> |
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+ * Loss: <code>__main__.CustomTripletLoss</code> with these parameters:
168
+ ```json
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+ {
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+ "distance_metric": "TripletDistanceMetric.EUCLIDEAN",
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+ "triplet_margin": 5
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+ }
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+ ```
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+
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+ ### Training Hyperparameters
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+ #### Non-Default Hyperparameters
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+
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+ - `per_device_train_batch_size`: 50
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+ - `learning_rate`: 2e-05
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+ - `num_train_epochs`: 5
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+ - `warmup_ratio`: 0.1
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+ - `fp16`: True
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+
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+ #### All Hyperparameters
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+ <details><summary>Click to expand</summary>
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+
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+ - `overwrite_output_dir`: False
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+ - `do_predict`: False
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+ - `eval_strategy`: no
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+ - `prediction_loss_only`: True
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+ - `per_device_train_batch_size`: 50
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+ - `per_device_eval_batch_size`: 8
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+ - `per_gpu_train_batch_size`: None
194
+ - `per_gpu_eval_batch_size`: None
195
+ - `gradient_accumulation_steps`: 1
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+ - `eval_accumulation_steps`: None
197
+ - `torch_empty_cache_steps`: None
198
+ - `learning_rate`: 2e-05
199
+ - `weight_decay`: 0.0
200
+ - `adam_beta1`: 0.9
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+ - `adam_beta2`: 0.999
202
+ - `adam_epsilon`: 1e-08
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+ - `max_grad_norm`: 1.0
204
+ - `num_train_epochs`: 5
205
+ - `max_steps`: -1
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+ - `lr_scheduler_type`: linear
207
+ - `lr_scheduler_kwargs`: {}
208
+ - `warmup_ratio`: 0.1
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+ - `warmup_steps`: 0
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+ - `log_level`: passive
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+ - `log_level_replica`: warning
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+ - `log_on_each_node`: True
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+ - `logging_nan_inf_filter`: True
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+ - `save_safetensors`: True
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+ - `save_on_each_node`: False
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+ - `save_only_model`: False
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+ - `restore_callback_states_from_checkpoint`: False
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+ - `no_cuda`: False
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+ - `use_cpu`: False
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+ - `use_mps_device`: False
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+ - `seed`: 42
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+ - `data_seed`: None
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+ - `jit_mode_eval`: False
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+ - `use_ipex`: False
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+ - `bf16`: False
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+ - `fp16`: True
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+ - `fp16_opt_level`: O1
228
+ - `half_precision_backend`: auto
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+ - `bf16_full_eval`: False
230
+ - `fp16_full_eval`: False
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+ - `tf32`: None
232
+ - `local_rank`: 0
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+ - `ddp_backend`: None
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+ - `tpu_num_cores`: None
235
+ - `tpu_metrics_debug`: False
236
+ - `debug`: []
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+ - `dataloader_drop_last`: False
238
+ - `dataloader_num_workers`: 0
239
+ - `dataloader_prefetch_factor`: None
240
+ - `past_index`: -1
241
+ - `disable_tqdm`: False
242
+ - `remove_unused_columns`: True
243
+ - `label_names`: None
244
+ - `load_best_model_at_end`: False
245
+ - `ignore_data_skip`: False
246
+ - `fsdp`: []
247
+ - `fsdp_min_num_params`: 0
248
+ - `fsdp_config`: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}
249
+ - `fsdp_transformer_layer_cls_to_wrap`: None
250
+ - `accelerator_config`: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None}
251
+ - `deepspeed`: None
252
+ - `label_smoothing_factor`: 0.0
253
+ - `optim`: adamw_torch
254
+ - `optim_args`: None
255
+ - `adafactor`: False
256
+ - `group_by_length`: False
257
+ - `length_column_name`: length
258
+ - `ddp_find_unused_parameters`: None
259
+ - `ddp_bucket_cap_mb`: None
260
+ - `ddp_broadcast_buffers`: False
261
+ - `dataloader_pin_memory`: True
262
+ - `dataloader_persistent_workers`: False
263
+ - `skip_memory_metrics`: True
264
+ - `use_legacy_prediction_loop`: False
265
+ - `push_to_hub`: False
266
+ - `resume_from_checkpoint`: None
267
+ - `hub_model_id`: None
268
+ - `hub_strategy`: every_save
269
+ - `hub_private_repo`: False
270
+ - `hub_always_push`: False
271
+ - `gradient_checkpointing`: False
272
+ - `gradient_checkpointing_kwargs`: None
273
+ - `include_inputs_for_metrics`: False
274
+ - `include_for_metrics`: []
275
+ - `eval_do_concat_batches`: True
276
+ - `fp16_backend`: auto
277
+ - `push_to_hub_model_id`: None
278
+ - `push_to_hub_organization`: None
279
+ - `mp_parameters`:
280
+ - `auto_find_batch_size`: False
281
+ - `full_determinism`: False
282
+ - `torchdynamo`: None
283
+ - `ray_scope`: last
284
+ - `ddp_timeout`: 1800
285
+ - `torch_compile`: False
286
+ - `torch_compile_backend`: None
287
+ - `torch_compile_mode`: None
288
+ - `dispatch_batches`: None
289
+ - `split_batches`: None
290
+ - `include_tokens_per_second`: False
291
+ - `include_num_input_tokens_seen`: False
292
+ - `neftune_noise_alpha`: None
293
+ - `optim_target_modules`: None
294
+ - `batch_eval_metrics`: False
295
+ - `eval_on_start`: False
296
+ - `use_liger_kernel`: False
297
+ - `eval_use_gather_object`: False
298
+ - `batch_sampler`: batch_sampler
299
+ - `multi_dataset_batch_sampler`: proportional
300
+
301
+ </details>
302
+
303
+ ### Training Logs
304
+ <details><summary>Click to expand</summary>
305
+
306
+ | Epoch | Step | Training Loss |
307
+ |:------:|:-------:|:-------------:|
308
+ | 0.5000 | 1875000 | 0.1053 |
309
+ | 0.5003 | 1876000 | 0.0899 |
310
+ | 0.5006 | 1877000 | 0.0978 |
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+ | 0.5008 | 1878000 | 0.0928 |
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+ | 0.5011 | 1879000 | 0.0887 |
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+ | 0.5014 | 1880000 | 0.0921 |
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+ | 0.5016 | 1881000 | 0.0908 |
315
+ | 0.5019 | 1882000 | 0.0925 |
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+ | 0.5022 | 1883000 | 0.0886 |
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+ | 0.5024 | 1884000 | 0.0924 |
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+ | 0.5027 | 1885000 | 0.0932 |
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+ | 0.5030 | 1886000 | 0.0938 |
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+ | 0.5032 | 1887000 | 0.0976 |
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+ | 0.5035 | 1888000 | 0.087 |
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+ | 0.5038 | 1889000 | 0.0882 |
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+ | 0.5040 | 1890000 | 0.0955 |
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+ | 0.5043 | 1891000 | 0.0927 |
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+ | 0.5046 | 1892000 | 0.0922 |
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+ | 0.5048 | 1893000 | 0.086 |
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+ | 0.5051 | 1894000 | 0.0899 |
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+ | 0.5054 | 1895000 | 0.0941 |
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+ | 0.5056 | 1896000 | 0.0924 |
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+ | 0.5059 | 1897000 | 0.0941 |
331
+ | 0.5062 | 1898000 | 0.0904 |
332
+ | 0.5064 | 1899000 | 0.09 |
333
+ | 0.5067 | 1900000 | 0.0928 |
334
+ | 0.5070 | 1901000 | 0.088 |
335
+ | 0.5072 | 1902000 | 0.0924 |
336
+ | 0.5075 | 1903000 | 0.0927 |
337
+ | 0.5078 | 1904000 | 0.0912 |
338
+ | 0.5080 | 1905000 | 0.0971 |
339
+ | 0.5083 | 1906000 | 0.0973 |
340
+ | 0.5086 | 1907000 | 0.0932 |
341
+ | 0.5088 | 1908000 | 0.092 |
342
+ | 0.5091 | 1909000 | 0.0894 |
343
+ | 0.5094 | 1910000 | 0.0866 |
344
+ | 0.5096 | 1911000 | 0.0951 |
345
+ | 0.5099 | 1912000 | 0.0924 |
346
+ | 0.5102 | 1913000 | 0.0913 |
347
+ | 0.5104 | 1914000 | 0.0921 |
348
+ | 0.5107 | 1915000 | 0.0915 |
349
+ | 0.5110 | 1916000 | 0.0897 |
350
+ | 0.5112 | 1917000 | 0.0932 |
351
+ | 0.5115 | 1918000 | 0.0871 |
352
+ | 0.5118 | 1919000 | 0.0872 |
353
+ | 0.5120 | 1920000 | 0.0962 |
354
+ | 0.5123 | 1921000 | 0.0902 |
355
+ | 0.5126 | 1922000 | 0.0939 |
356
+ | 0.5128 | 1923000 | 0.0873 |
357
+ | 0.5131 | 1924000 | 0.0841 |
358
+ | 0.5134 | 1925000 | 0.0863 |
359
+ | 0.5136 | 1926000 | 0.0941 |
360
+ | 0.5139 | 1927000 | 0.0905 |
361
+ | 0.5142 | 1928000 | 0.0876 |
362
+ | 0.5144 | 1929000 | 0.0866 |
363
+ | 0.5147 | 1930000 | 0.0921 |
364
+ | 0.5150 | 1931000 | 0.0973 |
365
+ | 0.5152 | 1932000 | 0.0937 |
366
+ | 0.5155 | 1933000 | 0.0899 |
367
+ | 0.5158 | 1934000 | 0.0965 |
368
+ | 0.5160 | 1935000 | 0.0942 |
369
+ | 0.5163 | 1936000 | 0.0927 |
370
+ | 0.5166 | 1937000 | 0.0897 |
371
+ | 0.5168 | 1938000 | 0.094 |
372
+ | 0.5171 | 1939000 | 0.0874 |
373
+ | 0.5174 | 1940000 | 0.0954 |
374
+ | 0.5176 | 1941000 | 0.0904 |
375
+ | 0.5179 | 1942000 | 0.0913 |
376
+ | 0.5182 | 1943000 | 0.0891 |
377
+ | 0.5184 | 1944000 | 0.0941 |
378
+ | 0.5187 | 1945000 | 0.0908 |
379
+ | 0.5190 | 1946000 | 0.0903 |
380
+ | 0.5192 | 1947000 | 0.0957 |
381
+ | 0.5195 | 1948000 | 0.0875 |
382
+ | 0.5198 | 1949000 | 0.0895 |
383
+ | 0.5200 | 1950000 | 0.0883 |
384
+ | 0.5203 | 1951000 | 0.0942 |
385
+ | 0.5206 | 1952000 | 0.091 |
386
+ | 0.5208 | 1953000 | 0.0874 |
387
+ | 0.5211 | 1954000 | 0.0921 |
388
+ | 0.5214 | 1955000 | 0.0967 |
389
+ | 0.5216 | 1956000 | 0.0962 |
390
+ | 0.5219 | 1957000 | 0.0942 |
391
+ | 0.5222 | 1958000 | 0.0818 |
392
+ | 0.5224 | 1959000 | 0.0861 |
393
+ | 0.5227 | 1960000 | 0.0849 |
394
+ | 0.5230 | 1961000 | 0.0894 |
395
+ | 0.5232 | 1962000 | 0.101 |
396
+ | 0.5235 | 1963000 | 0.0832 |
397
+ | 0.5238 | 1964000 | 0.0901 |
398
+ | 0.5240 | 1965000 | 0.0949 |
399
+ | 0.5243 | 1966000 | 0.0942 |
400
+ | 0.5246 | 1967000 | 0.0897 |
401
+ | 0.5248 | 1968000 | 0.0894 |
402
+ | 0.5251 | 1969000 | 0.0846 |
403
+ | 0.5254 | 1970000 | 0.087 |
404
+ | 0.5256 | 1971000 | 0.086 |
405
+ | 0.5259 | 1972000 | 0.086 |
406
+ | 0.5262 | 1973000 | 0.0913 |
407
+ | 0.5264 | 1974000 | 0.0916 |
408
+ | 0.5267 | 1975000 | 0.0867 |
409
+ | 0.5270 | 1976000 | 0.085 |
410
+ | 0.5272 | 1977000 | 0.0863 |
411
+ | 0.5275 | 1978000 | 0.0927 |
412
+ | 0.5278 | 1979000 | 0.0866 |
413
+ | 0.5280 | 1980000 | 0.0865 |
414
+ | 0.5283 | 1981000 | 0.0898 |
415
+ | 0.5286 | 1982000 | 0.0917 |
416
+ | 0.5288 | 1983000 | 0.0864 |
417
+ | 0.5291 | 1984000 | 0.0937 |
418
+ | 0.5294 | 1985000 | 0.0916 |
419
+ | 0.5296 | 1986000 | 0.0913 |
420
+ | 0.5299 | 1987000 | 0.0927 |
421
+ | 0.5302 | 1988000 | 0.0947 |
422
+ | 0.5304 | 1989000 | 0.0939 |
423
+ | 0.5307 | 1990000 | 0.0864 |
424
+ | 0.5310 | 1991000 | 0.0816 |
425
+ | 0.5312 | 1992000 | 0.0931 |
426
+ | 0.5315 | 1993000 | 0.0906 |
427
+ | 0.5318 | 1994000 | 0.0907 |
428
+ | 0.5320 | 1995000 | 0.0895 |
429
+ | 0.5323 | 1996000 | 0.0913 |
430
+ | 0.5326 | 1997000 | 0.0915 |
431
+ | 0.5328 | 1998000 | 0.0909 |
432
+ | 0.5331 | 1999000 | 0.0917 |
433
+ | 0.5334 | 2000000 | 0.0828 |
434
+ | 0.5336 | 2001000 | 0.0865 |
435
+ | 0.5339 | 2002000 | 0.0864 |
436
+ | 0.5342 | 2003000 | 0.0887 |
437
+ | 0.5344 | 2004000 | 0.0871 |
438
+ | 0.5347 | 2005000 | 0.0903 |
439
+ | 0.5350 | 2006000 | 0.092 |
440
+ | 0.5352 | 2007000 | 0.083 |
441
+ | 0.5355 | 2008000 | 0.0934 |
442
+ | 0.5358 | 2009000 | 0.0885 |
443
+ | 0.5360 | 2010000 | 0.0841 |
444
+ | 0.5363 | 2011000 | 0.0919 |
445
+ | 0.5366 | 2012000 | 0.0909 |
446
+ | 0.5368 | 2013000 | 0.0899 |
447
+ | 0.5371 | 2014000 | 0.0905 |
448
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449
+ | 0.5376 | 2016000 | 0.0936 |
450
+ | 0.5379 | 2017000 | 0.0926 |
451
+ | 0.5382 | 2018000 | 0.0884 |
452
+ | 0.5384 | 2019000 | 0.0909 |
453
+ | 0.5387 | 2020000 | 0.0858 |
454
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455
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456
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457
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458
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459
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460
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461
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462
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463
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464
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465
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466
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467
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468
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469
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470
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471
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472
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473
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474
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475
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476
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477
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478
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479
+ | 0.5456 | 2046000 | 0.0863 |
480
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481
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482
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483
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484
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485
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486
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487
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488
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489
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490
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491
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492
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493
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494
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495
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496
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497
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498
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499
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500
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501
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502
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503
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504
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505
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506
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507
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508
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509
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510
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511
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512
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513
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514
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515
+ | 0.5552 | 2082000 | 0.0897 |
516
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517
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518
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519
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520
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521
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522
+ | 0.5571 | 2089000 | 0.0845 |
523
+ | 0.5574 | 2090000 | 0.0854 |
524
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525
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526
+ | 0.5582 | 2093000 | 0.0881 |
527
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528
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529
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530
+ | 0.5592 | 2097000 | 0.0835 |
531
+ | 0.5595 | 2098000 | 0.0911 |
532
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533
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534
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535
+ | 0.5606 | 2102000 | 0.0855 |
536
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537
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538
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539
+ | 0.5616 | 2106000 | 0.0925 |
540
+ | 0.5619 | 2107000 | 0.0874 |
541
+ | 0.5622 | 2108000 | 0.0901 |
542
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543
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544
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545
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546
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547
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548
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549
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550
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551
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552
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553
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554
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555
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556
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557
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558
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559
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560
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561
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562
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563
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564
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565
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566
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567
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568
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569
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570
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571
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572
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573
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574
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575
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576
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577
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578
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579
+ | 0.5723 | 2146000 | 0.0841 |
580
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581
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582
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583
+ | 0.5734 | 2150000 | 0.0852 |
584
+ | 0.5736 | 2151000 | 0.0858 |
585
+ | 0.5739 | 2152000 | 0.0878 |
586
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587
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588
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589
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590
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591
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592
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593
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594
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595
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596
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597
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598
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599
+ | 0.5776 | 2166000 | 0.0894 |
600
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601
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602
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603
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604
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605
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606
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607
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608
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609
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610
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611
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612
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613
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614
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615
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616
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617
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618
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619
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620
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621
+ | 0.5835 | 2188000 | 0.0829 |
622
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623
+ | 0.5840 | 2190000 | 0.0861 |
624
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625
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626
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627
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628
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629
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630
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631
+ | 0.5862 | 2198000 | 0.0854 |
632
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633
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634
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635
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636
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637
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638
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639
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640
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641
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642
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643
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644
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645
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646
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647
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648
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649
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650
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651
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652
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653
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654
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655
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656
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657
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658
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659
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660
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661
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662
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663
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664
+ | 0.5950 | 2231000 | 0.0788 |
665
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666
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667
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668
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669
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670
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671
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672
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673
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674
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675
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676
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677
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678
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679
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680
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681
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682
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683
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684
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685
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686
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687
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688
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689
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690
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691
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692
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693
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694
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695
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696
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697
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698
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699
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700
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701
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702
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703
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704
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705
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706
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707
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708
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709
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710
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711
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712
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713
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714
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715
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716
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717
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718
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719
+ | 0.6096 | 2286000 | 0.087 |
720
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721
+ | 0.6102 | 2288000 | 0.0821 |
722
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723
+ | 0.6107 | 2290000 | 0.0838 |
724
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725
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726
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727
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728
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729
+ | 0.6123 | 2296000 | 0.0833 |
730
+ | 0.6126 | 2297000 | 0.0859 |
731
+ | 0.6128 | 2298000 | 0.0824 |
732
+ | 0.6131 | 2299000 | 0.0825 |
733
+ | 0.6134 | 2300000 | 0.0909 |
734
+ | 0.6136 | 2301000 | 0.0856 |
735
+ | 0.6139 | 2302000 | 0.0827 |
736
+ | 0.6142 | 2303000 | 0.0842 |
737
+ | 0.6144 | 2304000 | 0.0798 |
738
+ | 0.6147 | 2305000 | 0.0797 |
739
+ | 0.6150 | 2306000 | 0.0812 |
740
+ | 0.6152 | 2307000 | 0.0812 |
741
+ | 0.6155 | 2308000 | 0.0897 |
742
+ | 0.6158 | 2309000 | 0.0833 |
743
+ | 0.6160 | 2310000 | 0.0835 |
744
+ | 0.6163 | 2311000 | 0.0848 |
745
+ | 0.6166 | 2312000 | 0.0858 |
746
+ | 0.6168 | 2313000 | 0.0738 |
747
+ | 0.6171 | 2314000 | 0.08 |
748
+ | 0.6174 | 2315000 | 0.0784 |
749
+ | 0.6176 | 2316000 | 0.0797 |
750
+ | 0.6179 | 2317000 | 0.0791 |
751
+ | 0.6182 | 2318000 | 0.0873 |
752
+ | 0.6184 | 2319000 | 0.0825 |
753
+ | 0.6187 | 2320000 | 0.0883 |
754
+ | 0.6190 | 2321000 | 0.084 |
755
+ | 0.6192 | 2322000 | 0.0801 |
756
+ | 0.6195 | 2323000 | 0.0856 |
757
+ | 0.6198 | 2324000 | 0.0764 |
758
+ | 0.6200 | 2325000 | 0.088 |
759
+ | 0.6203 | 2326000 | 0.0814 |
760
+ | 0.6206 | 2327000 | 0.0857 |
761
+ | 0.6208 | 2328000 | 0.0873 |
762
+ | 0.6211 | 2329000 | 0.0846 |
763
+ | 0.6214 | 2330000 | 0.0871 |
764
+ | 0.6216 | 2331000 | 0.0798 |
765
+ | 0.6219 | 2332000 | 0.0908 |
766
+ | 0.6222 | 2333000 | 0.0799 |
767
+ | 0.6224 | 2334000 | 0.0801 |
768
+ | 0.6227 | 2335000 | 0.0813 |
769
+ | 0.6230 | 2336000 | 0.0868 |
770
+ | 0.6232 | 2337000 | 0.0794 |
771
+ | 0.6235 | 2338000 | 0.0869 |
772
+ | 0.6238 | 2339000 | 0.0799 |
773
+ | 0.6240 | 2340000 | 0.0793 |
774
+ | 0.6243 | 2341000 | 0.0801 |
775
+ | 0.6246 | 2342000 | 0.0836 |
776
+ | 0.6248 | 2343000 | 0.0836 |
777
+ | 0.6251 | 2344000 | 0.0855 |
778
+ | 0.6254 | 2345000 | 0.0792 |
779
+ | 0.6256 | 2346000 | 0.0805 |
780
+ | 0.6259 | 2347000 | 0.0807 |
781
+ | 0.6262 | 2348000 | 0.0815 |
782
+ | 0.6264 | 2349000 | 0.0864 |
783
+ | 0.6267 | 2350000 | 0.0745 |
784
+ | 0.6270 | 2351000 | 0.0813 |
785
+ | 0.6272 | 2352000 | 0.0882 |
786
+ | 0.6275 | 2353000 | 0.0789 |
787
+ | 0.6278 | 2354000 | 0.0756 |
788
+ | 0.6280 | 2355000 | 0.0863 |
789
+ | 0.6283 | 2356000 | 0.0833 |
790
+ | 0.6286 | 2357000 | 0.0739 |
791
+ | 0.6288 | 2358000 | 0.081 |
792
+ | 0.6291 | 2359000 | 0.0776 |
793
+ | 0.6294 | 2360000 | 0.0805 |
794
+ | 0.6296 | 2361000 | 0.0806 |
795
+ | 0.6299 | 2362000 | 0.0882 |
796
+ | 0.6302 | 2363000 | 0.0823 |
797
+ | 0.6304 | 2364000 | 0.09 |
798
+ | 0.6307 | 2365000 | 0.0763 |
799
+ | 0.6310 | 2366000 | 0.0796 |
800
+ | 0.6312 | 2367000 | 0.0835 |
801
+ | 0.6315 | 2368000 | 0.0803 |
802
+ | 0.6318 | 2369000 | 0.084 |
803
+ | 0.6320 | 2370000 | 0.084 |
804
+ | 0.6323 | 2371000 | 0.076 |
805
+ | 0.6326 | 2372000 | 0.0749 |
806
+ | 0.6328 | 2373000 | 0.0795 |
807
+ | 0.6331 | 2374000 | 0.0813 |
808
+ | 0.6334 | 2375000 | 0.0825 |
809
+ | 0.6336 | 2376000 | 0.0829 |
810
+ | 0.6339 | 2377000 | 0.0818 |
811
+ | 0.6342 | 2378000 | 0.0797 |
812
+ | 0.6344 | 2379000 | 0.0846 |
813
+ | 0.6347 | 2380000 | 0.0832 |
814
+ | 0.6350 | 2381000 | 0.082 |
815
+ | 0.6352 | 2382000 | 0.0842 |
816
+ | 0.6355 | 2383000 | 0.0849 |
817
+ | 0.6358 | 2384000 | 0.08 |
818
+ | 0.6360 | 2385000 | 0.0805 |
819
+ | 0.6363 | 2386000 | 0.0787 |
820
+ | 0.6366 | 2387000 | 0.088 |
821
+ | 0.6368 | 2388000 | 0.0883 |
822
+ | 0.6371 | 2389000 | 0.0807 |
823
+ | 0.6374 | 2390000 | 0.0786 |
824
+ | 0.6376 | 2391000 | 0.0836 |
825
+ | 0.6379 | 2392000 | 0.0795 |
826
+ | 0.6382 | 2393000 | 0.0801 |
827
+ | 0.6384 | 2394000 | 0.085 |
828
+ | 0.6387 | 2395000 | 0.0815 |
829
+ | 0.6390 | 2396000 | 0.0845 |
830
+ | 0.6392 | 2397000 | 0.0798 |
831
+ | 0.6395 | 2398000 | 0.0836 |
832
+ | 0.6398 | 2399000 | 0.0803 |
833
+ | 0.6400 | 2400000 | 0.0817 |
834
+ | 0.6403 | 2401000 | 0.0894 |
835
+ | 0.6406 | 2402000 | 0.0809 |
836
+ | 0.6408 | 2403000 | 0.0761 |
837
+ | 0.6411 | 2404000 | 0.0809 |
838
+ | 0.6414 | 2405000 | 0.0777 |
839
+ | 0.6416 | 2406000 | 0.0794 |
840
+ | 0.6419 | 2407000 | 0.0787 |
841
+ | 0.6422 | 2408000 | 0.081 |
842
+ | 0.6424 | 2409000 | 0.0847 |
843
+ | 0.6427 | 2410000 | 0.0823 |
844
+ | 0.6430 | 2411000 | 0.0751 |
845
+ | 0.6432 | 2412000 | 0.0859 |
846
+ | 0.6435 | 2413000 | 0.0805 |
847
+ | 0.6438 | 2414000 | 0.082 |
848
+ | 0.6440 | 2415000 | 0.0861 |
849
+ | 0.6443 | 2416000 | 0.0842 |
850
+ | 0.6446 | 2417000 | 0.0876 |
851
+ | 0.6448 | 2418000 | 0.074 |
852
+ | 0.6451 | 2419000 | 0.0818 |
853
+ | 0.6454 | 2420000 | 0.0836 |
854
+ | 0.6456 | 2421000 | 0.082 |
855
+ | 0.6459 | 2422000 | 0.0749 |
856
+ | 0.6462 | 2423000 | 0.0865 |
857
+ | 0.6464 | 2424000 | 0.0809 |
858
+ | 0.6467 | 2425000 | 0.0854 |
859
+ | 0.6470 | 2426000 | 0.0829 |
860
+ | 0.6472 | 2427000 | 0.08 |
861
+ | 0.6475 | 2428000 | 0.0873 |
862
+ | 0.6478 | 2429000 | 0.0757 |
863
+ | 0.6480 | 2430000 | 0.0788 |
864
+ | 0.6483 | 2431000 | 0.082 |
865
+ | 0.6486 | 2432000 | 0.0834 |
866
+ | 0.6488 | 2433000 | 0.0795 |
867
+ | 0.6491 | 2434000 | 0.0859 |
868
+ | 0.6494 | 2435000 | 0.0839 |
869
+ | 0.6496 | 2436000 | 0.0874 |
870
+ | 0.6499 | 2437000 | 0.0812 |
871
+ | 0.6502 | 2438000 | 0.0824 |
872
+ | 0.6504 | 2439000 | 0.0794 |
873
+ | 0.6507 | 2440000 | 0.0795 |
874
+ | 0.6510 | 2441000 | 0.0826 |
875
+ | 0.6512 | 2442000 | 0.0813 |
876
+ | 0.6515 | 2443000 | 0.0788 |
877
+ | 0.6518 | 2444000 | 0.0848 |
878
+ | 0.6520 | 2445000 | 0.0826 |
879
+ | 0.6523 | 2446000 | 0.0762 |
880
+ | 0.6526 | 2447000 | 0.0802 |
881
+ | 0.6528 | 2448000 | 0.0871 |
882
+ | 0.6531 | 2449000 | 0.0803 |
883
+ | 0.6534 | 2450000 | 0.0797 |
884
+ | 0.6536 | 2451000 | 0.0842 |
885
+ | 0.6539 | 2452000 | 0.0819 |
886
+ | 0.6542 | 2453000 | 0.0848 |
887
+ | 0.6544 | 2454000 | 0.08 |
888
+ | 0.6547 | 2455000 | 0.0815 |
889
+ | 0.6550 | 2456000 | 0.0806 |
890
+ | 0.6552 | 2457000 | 0.0811 |
891
+ | 0.6555 | 2458000 | 0.0798 |
892
+ | 0.6558 | 2459000 | 0.0789 |
893
+ | 0.6560 | 2460000 | 0.0793 |
894
+ | 0.6563 | 2461000 | 0.0821 |
895
+ | 0.6566 | 2462000 | 0.0835 |
896
+ | 0.6568 | 2463000 | 0.0833 |
897
+ | 0.6571 | 2464000 | 0.0821 |
898
+ | 0.6574 | 2465000 | 0.088 |
899
+ | 0.6576 | 2466000 | 0.0822 |
900
+ | 0.6579 | 2467000 | 0.0749 |
901
+ | 0.6582 | 2468000 | 0.0787 |
902
+ | 0.6584 | 2469000 | 0.0793 |
903
+ | 0.6587 | 2470000 | 0.0793 |
904
+ | 0.6590 | 2471000 | 0.0807 |
905
+ | 0.6592 | 2472000 | 0.0767 |
906
+ | 0.6595 | 2473000 | 0.0823 |
907
+ | 0.6598 | 2474000 | 0.0867 |
908
+ | 0.6600 | 2475000 | 0.0834 |
909
+ | 0.6603 | 2476000 | 0.0821 |
910
+ | 0.6606 | 2477000 | 0.0787 |
911
+ | 0.6608 | 2478000 | 0.077 |
912
+ | 0.6611 | 2479000 | 0.0771 |
913
+ | 0.6614 | 2480000 | 0.0822 |
914
+ | 0.6616 | 2481000 | 0.0824 |
915
+ | 0.6619 | 2482000 | 0.0786 |
916
+ | 0.6622 | 2483000 | 0.0795 |
917
+ | 0.6624 | 2484000 | 0.0718 |
918
+ | 0.6627 | 2485000 | 0.0807 |
919
+ | 0.6630 | 2486000 | 0.0791 |
920
+ | 0.6632 | 2487000 | 0.0801 |
921
+ | 0.6635 | 2488000 | 0.0843 |
922
+ | 0.6638 | 2489000 | 0.0843 |
923
+ | 0.6640 | 2490000 | 0.0771 |
924
+ | 0.6643 | 2491000 | 0.083 |
925
+ | 0.6646 | 2492000 | 0.0824 |
926
+ | 0.6648 | 2493000 | 0.0841 |
927
+ | 0.6651 | 2494000 | 0.0823 |
928
+ | 0.6654 | 2495000 | 0.0795 |
929
+ | 0.6656 | 2496000 | 0.0825 |
930
+ | 0.6659 | 2497000 | 0.0803 |
931
+ | 0.6662 | 2498000 | 0.0843 |
932
+ | 0.6664 | 2499000 | 0.0787 |
933
+ | 0.6667 | 2500000 | 0.0817 |
934
+ | 0.6670 | 2501000 | 0.0816 |
935
+ | 0.6672 | 2502000 | 0.0793 |
936
+ | 0.6675 | 2503000 | 0.0823 |
937
+ | 0.6678 | 2504000 | 0.0764 |
938
+ | 0.6680 | 2505000 | 0.0782 |
939
+ | 0.6683 | 2506000 | 0.0807 |
940
+ | 0.6686 | 2507000 | 0.0824 |
941
+ | 0.6688 | 2508000 | 0.0768 |
942
+ | 0.6691 | 2509000 | 0.0859 |
943
+ | 0.6694 | 2510000 | 0.0791 |
944
+ | 0.6696 | 2511000 | 0.0789 |
945
+ | 0.6699 | 2512000 | 0.0848 |
946
+ | 0.6702 | 2513000 | 0.0749 |
947
+ | 0.6704 | 2514000 | 0.0776 |
948
+ | 0.6707 | 2515000 | 0.0735 |
949
+ | 0.6710 | 2516000 | 0.0778 |
950
+ | 0.6712 | 2517000 | 0.0801 |
951
+ | 0.6715 | 2518000 | 0.0798 |
952
+ | 0.6718 | 2519000 | 0.0784 |
953
+ | 0.6720 | 2520000 | 0.0781 |
954
+ | 0.6723 | 2521000 | 0.0818 |
955
+ | 0.6726 | 2522000 | 0.0762 |
956
+ | 0.6728 | 2523000 | 0.0806 |
957
+ | 0.6731 | 2524000 | 0.0773 |
958
+ | 0.6734 | 2525000 | 0.0772 |
959
+ | 0.6736 | 2526000 | 0.0782 |
960
+ | 0.6739 | 2527000 | 0.0767 |
961
+ | 0.6742 | 2528000 | 0.0828 |
962
+ | 0.6744 | 2529000 | 0.0829 |
963
+ | 0.6747 | 2530000 | 0.0792 |
964
+ | 0.6750 | 2531000 | 0.0797 |
965
+ | 0.6752 | 2532000 | 0.0823 |
966
+ | 0.6755 | 2533000 | 0.0772 |
967
+ | 0.6758 | 2534000 | 0.0765 |
968
+ | 0.6760 | 2535000 | 0.075 |
969
+ | 0.6763 | 2536000 | 0.0786 |
970
+ | 0.6766 | 2537000 | 0.0785 |
971
+ | 0.6768 | 2538000 | 0.0877 |
972
+ | 0.6771 | 2539000 | 0.0747 |
973
+ | 0.6774 | 2540000 | 0.0755 |
974
+ | 0.6776 | 2541000 | 0.082 |
975
+ | 0.6779 | 2542000 | 0.0759 |
976
+ | 0.6782 | 2543000 | 0.0831 |
977
+ | 0.6784 | 2544000 | 0.0811 |
978
+ | 0.6787 | 2545000 | 0.0795 |
979
+ | 0.6790 | 2546000 | 0.0852 |
980
+ | 0.6792 | 2547000 | 0.0832 |
981
+ | 0.6795 | 2548000 | 0.0793 |
982
+ | 0.6798 | 2549000 | 0.0832 |
983
+ | 0.6800 | 2550000 | 0.0799 |
984
+ | 0.6803 | 2551000 | 0.0733 |
985
+ | 0.6806 | 2552000 | 0.0809 |
986
+ | 0.6808 | 2553000 | 0.0772 |
987
+ | 0.6811 | 2554000 | 0.0801 |
988
+ | 0.6814 | 2555000 | 0.0794 |
989
+ | 0.6816 | 2556000 | 0.0792 |
990
+ | 0.6819 | 2557000 | 0.0847 |
991
+ | 0.6822 | 2558000 | 0.0748 |
992
+ | 0.6824 | 2559000 | 0.0813 |
993
+ | 0.6827 | 2560000 | 0.0741 |
994
+ | 0.6830 | 2561000 | 0.0851 |
995
+ | 0.6832 | 2562000 | 0.0763 |
996
+ | 0.6835 | 2563000 | 0.0841 |
997
+ | 0.6838 | 2564000 | 0.0762 |
998
+ | 0.6840 | 2565000 | 0.0752 |
999
+ | 0.6843 | 2566000 | 0.0857 |
1000
+ | 0.6846 | 2567000 | 0.0824 |
1001
+ | 0.6848 | 2568000 | 0.0762 |
1002
+ | 0.6851 | 2569000 | 0.0754 |
1003
+ | 0.6854 | 2570000 | 0.0795 |
1004
+ | 0.6856 | 2571000 | 0.0829 |
1005
+ | 0.6859 | 2572000 | 0.0839 |
1006
+ | 0.6862 | 2573000 | 0.0779 |
1007
+ | 0.6864 | 2574000 | 0.08 |
1008
+ | 0.6867 | 2575000 | 0.0722 |
1009
+ | 0.6870 | 2576000 | 0.0796 |
1010
+ | 0.6872 | 2577000 | 0.0831 |
1011
+ | 0.6875 | 2578000 | 0.0795 |
1012
+ | 0.6878 | 2579000 | 0.0827 |
1013
+ | 0.6880 | 2580000 | 0.0821 |
1014
+ | 0.6883 | 2581000 | 0.074 |
1015
+ | 0.6886 | 2582000 | 0.0811 |
1016
+ | 0.6888 | 2583000 | 0.0758 |
1017
+ | 0.6891 | 2584000 | 0.0742 |
1018
+ | 0.6894 | 2585000 | 0.0744 |
1019
+ | 0.6896 | 2586000 | 0.081 |
1020
+ | 0.6899 | 2587000 | 0.0738 |
1021
+ | 0.6902 | 2588000 | 0.0844 |
1022
+ | 0.6904 | 2589000 | 0.0773 |
1023
+ | 0.6907 | 2590000 | 0.0756 |
1024
+ | 0.6910 | 2591000 | 0.0805 |
1025
+ | 0.6912 | 2592000 | 0.0812 |
1026
+ | 0.6915 | 2593000 | 0.0757 |
1027
+ | 0.6918 | 2594000 | 0.0802 |
1028
+ | 0.6920 | 2595000 | 0.0813 |
1029
+ | 0.6923 | 2596000 | 0.0769 |
1030
+ | 0.6926 | 2597000 | 0.0752 |
1031
+ | 0.6928 | 2598000 | 0.0843 |
1032
+ | 0.6931 | 2599000 | 0.0755 |
1033
+ | 0.6934 | 2600000 | 0.0837 |
1034
+ | 0.6936 | 2601000 | 0.0823 |
1035
+ | 0.6939 | 2602000 | 0.0728 |
1036
+ | 0.6942 | 2603000 | 0.0811 |
1037
+ | 0.6944 | 2604000 | 0.0802 |
1038
+ | 0.6947 | 2605000 | 0.0758 |
1039
+ | 0.6950 | 2606000 | 0.0797 |
1040
+ | 0.6952 | 2607000 | 0.0841 |
1041
+ | 0.6955 | 2608000 | 0.0788 |
1042
+ | 0.6958 | 2609000 | 0.0811 |
1043
+ | 0.6960 | 2610000 | 0.0788 |
1044
+ | 0.6963 | 2611000 | 0.0786 |
1045
+ | 0.6966 | 2612000 | 0.0722 |
1046
+ | 0.6968 | 2613000 | 0.0853 |
1047
+ | 0.6971 | 2614000 | 0.0755 |
1048
+ | 0.6974 | 2615000 | 0.0818 |
1049
+ | 0.6976 | 2616000 | 0.0792 |
1050
+ | 0.6979 | 2617000 | 0.0854 |
1051
+ | 0.6982 | 2618000 | 0.0735 |
1052
+ | 0.6984 | 2619000 | 0.0786 |
1053
+ | 0.6987 | 2620000 | 0.0805 |
1054
+ | 0.6990 | 2621000 | 0.0756 |
1055
+ | 0.6992 | 2622000 | 0.0792 |
1056
+ | 0.6995 | 2623000 | 0.0761 |
1057
+ | 0.6998 | 2624000 | 0.0762 |
1058
+ | 0.7000 | 2625000 | 0.0778 |
1059
+ | 0.7003 | 2626000 | 0.0826 |
1060
+ | 0.7006 | 2627000 | 0.0789 |
1061
+ | 0.7008 | 2628000 | 0.0786 |
1062
+ | 0.7011 | 2629000 | 0.0792 |
1063
+ | 0.7014 | 2630000 | 0.0816 |
1064
+ | 0.7016 | 2631000 | 0.0751 |
1065
+ | 0.7019 | 2632000 | 0.0729 |
1066
+ | 0.7022 | 2633000 | 0.0776 |
1067
+ | 0.7024 | 2634000 | 0.0823 |
1068
+ | 0.7027 | 2635000 | 0.0808 |
1069
+ | 0.7030 | 2636000 | 0.079 |
1070
+ | 0.7032 | 2637000 | 0.0792 |
1071
+ | 0.7035 | 2638000 | 0.0761 |
1072
+ | 0.7038 | 2639000 | 0.0795 |
1073
+ | 0.7040 | 2640000 | 0.0806 |
1074
+ | 0.7043 | 2641000 | 0.0793 |
1075
+ | 0.7046 | 2642000 | 0.086 |
1076
+ | 0.7048 | 2643000 | 0.0765 |
1077
+ | 0.7051 | 2644000 | 0.0745 |
1078
+ | 0.7054 | 2645000 | 0.0771 |
1079
+ | 0.7056 | 2646000 | 0.0808 |
1080
+ | 0.7059 | 2647000 | 0.0805 |
1081
+ | 0.7062 | 2648000 | 0.0759 |
1082
+ | 0.7064 | 2649000 | 0.0709 |
1083
+ | 0.7067 | 2650000 | 0.0787 |
1084
+ | 0.7070 | 2651000 | 0.08 |
1085
+ | 0.7072 | 2652000 | 0.0826 |
1086
+ | 0.7075 | 2653000 | 0.085 |
1087
+ | 0.7078 | 2654000 | 0.08 |
1088
+ | 0.7080 | 2655000 | 0.0762 |
1089
+ | 0.7083 | 2656000 | 0.0769 |
1090
+ | 0.7086 | 2657000 | 0.0783 |
1091
+ | 0.7088 | 2658000 | 0.0837 |
1092
+ | 0.7091 | 2659000 | 0.0803 |
1093
+ | 0.7094 | 2660000 | 0.0809 |
1094
+ | 0.7096 | 2661000 | 0.0764 |
1095
+ | 0.7099 | 2662000 | 0.0791 |
1096
+ | 0.7102 | 2663000 | 0.0829 |
1097
+ | 0.7104 | 2664000 | 0.0767 |
1098
+ | 0.7107 | 2665000 | 0.0799 |
1099
+ | 0.7110 | 2666000 | 0.0789 |
1100
+ | 0.7112 | 2667000 | 0.0781 |
1101
+ | 0.7115 | 2668000 | 0.0813 |
1102
+ | 0.7118 | 2669000 | 0.0793 |
1103
+ | 0.7120 | 2670000 | 0.0793 |
1104
+ | 0.7123 | 2671000 | 0.0815 |
1105
+ | 0.7126 | 2672000 | 0.0816 |
1106
+ | 0.7128 | 2673000 | 0.0774 |
1107
+ | 0.7131 | 2674000 | 0.0785 |
1108
+ | 0.7134 | 2675000 | 0.0711 |
1109
+ | 0.7136 | 2676000 | 0.0799 |
1110
+ | 0.7139 | 2677000 | 0.0758 |
1111
+ | 0.7142 | 2678000 | 0.08 |
1112
+ | 0.7144 | 2679000 | 0.081 |
1113
+ | 0.7147 | 2680000 | 0.0797 |
1114
+ | 0.7150 | 2681000 | 0.0798 |
1115
+ | 0.7152 | 2682000 | 0.0775 |
1116
+ | 0.7155 | 2683000 | 0.0766 |
1117
+ | 0.7158 | 2684000 | 0.0803 |
1118
+ | 0.7160 | 2685000 | 0.0743 |
1119
+ | 0.7163 | 2686000 | 0.0764 |
1120
+ | 0.7166 | 2687000 | 0.0773 |
1121
+ | 0.7168 | 2688000 | 0.0773 |
1122
+ | 0.7171 | 2689000 | 0.0769 |
1123
+ | 0.7174 | 2690000 | 0.0753 |
1124
+ | 0.7176 | 2691000 | 0.072 |
1125
+ | 0.7179 | 2692000 | 0.0779 |
1126
+ | 0.7182 | 2693000 | 0.0778 |
1127
+ | 0.7184 | 2694000 | 0.0743 |
1128
+ | 0.7187 | 2695000 | 0.0764 |
1129
+ | 0.7190 | 2696000 | 0.0762 |
1130
+ | 0.7192 | 2697000 | 0.0791 |
1131
+ | 0.7195 | 2698000 | 0.0804 |
1132
+ | 0.7198 | 2699000 | 0.0769 |
1133
+ | 0.7200 | 2700000 | 0.0787 |
1134
+ | 0.7203 | 2701000 | 0.0804 |
1135
+ | 0.7206 | 2702000 | 0.0746 |
1136
+ | 0.7208 | 2703000 | 0.0813 |
1137
+ | 0.7211 | 2704000 | 0.0783 |
1138
+ | 0.7214 | 2705000 | 0.0783 |
1139
+ | 0.7216 | 2706000 | 0.0748 |
1140
+ | 0.7219 | 2707000 | 0.0813 |
1141
+ | 0.7222 | 2708000 | 0.0885 |
1142
+ | 0.7224 | 2709000 | 0.0749 |
1143
+ | 0.7227 | 2710000 | 0.0812 |
1144
+ | 0.7230 | 2711000 | 0.0749 |
1145
+ | 0.7232 | 2712000 | 0.0787 |
1146
+ | 0.7235 | 2713000 | 0.0823 |
1147
+ | 0.7238 | 2714000 | 0.0754 |
1148
+ | 0.7240 | 2715000 | 0.0773 |
1149
+ | 0.7243 | 2716000 | 0.0774 |
1150
+ | 0.7246 | 2717000 | 0.0785 |
1151
+ | 0.7248 | 2718000 | 0.0813 |
1152
+ | 0.7251 | 2719000 | 0.0855 |
1153
+ | 0.7254 | 2720000 | 0.0812 |
1154
+ | 0.7256 | 2721000 | 0.0751 |
1155
+ | 0.7259 | 2722000 | 0.0778 |
1156
+ | 0.7262 | 2723000 | 0.0756 |
1157
+ | 0.7264 | 2724000 | 0.0808 |
1158
+ | 0.7267 | 2725000 | 0.0768 |
1159
+ | 0.7270 | 2726000 | 0.0775 |
1160
+ | 0.7272 | 2727000 | 0.0789 |
1161
+ | 0.7275 | 2728000 | 0.077 |
1162
+ | 0.7278 | 2729000 | 0.0795 |
1163
+ | 0.7280 | 2730000 | 0.0805 |
1164
+ | 0.7283 | 2731000 | 0.069 |
1165
+ | 0.7286 | 2732000 | 0.0807 |
1166
+ | 0.7288 | 2733000 | 0.0806 |
1167
+ | 0.7291 | 2734000 | 0.0805 |
1168
+ | 0.7294 | 2735000 | 0.0746 |
1169
+ | 0.7296 | 2736000 | 0.0823 |
1170
+ | 0.7299 | 2737000 | 0.0752 |
1171
+ | 0.7302 | 2738000 | 0.0761 |
1172
+ | 0.7304 | 2739000 | 0.079 |
1173
+ | 0.7307 | 2740000 | 0.0772 |
1174
+ | 0.7310 | 2741000 | 0.0781 |
1175
+ | 0.7312 | 2742000 | 0.0774 |
1176
+ | 0.7315 | 2743000 | 0.0805 |
1177
+ | 0.7318 | 2744000 | 0.0784 |
1178
+ | 0.7320 | 2745000 | 0.0783 |
1179
+ | 0.7323 | 2746000 | 0.0761 |
1180
+ | 0.7326 | 2747000 | 0.0772 |
1181
+ | 0.7328 | 2748000 | 0.0755 |
1182
+ | 0.7331 | 2749000 | 0.0733 |
1183
+ | 0.7334 | 2750000 | 0.0744 |
1184
+ | 0.7336 | 2751000 | 0.0737 |
1185
+ | 0.7339 | 2752000 | 0.0747 |
1186
+ | 0.7342 | 2753000 | 0.0742 |
1187
+ | 0.7344 | 2754000 | 0.0789 |
1188
+ | 0.7347 | 2755000 | 0.0788 |
1189
+ | 0.7350 | 2756000 | 0.0789 |
1190
+ | 0.7352 | 2757000 | 0.0763 |
1191
+ | 0.7355 | 2758000 | 0.0751 |
1192
+ | 0.7358 | 2759000 | 0.0745 |
1193
+ | 0.7360 | 2760000 | 0.0814 |
1194
+ | 0.7363 | 2761000 | 0.0792 |
1195
+ | 0.7366 | 2762000 | 0.0748 |
1196
+ | 0.7368 | 2763000 | 0.0822 |
1197
+ | 0.7371 | 2764000 | 0.0754 |
1198
+ | 0.7374 | 2765000 | 0.0765 |
1199
+ | 0.7376 | 2766000 | 0.074 |
1200
+ | 0.7379 | 2767000 | 0.0691 |
1201
+ | 0.7382 | 2768000 | 0.0754 |
1202
+ | 0.7384 | 2769000 | 0.0703 |
1203
+ | 0.7387 | 2770000 | 0.0795 |
1204
+ | 0.7390 | 2771000 | 0.0792 |
1205
+ | 0.7392 | 2772000 | 0.0741 |
1206
+ | 0.7395 | 2773000 | 0.0712 |
1207
+ | 0.7398 | 2774000 | 0.0713 |
1208
+ | 0.7400 | 2775000 | 0.071 |
1209
+ | 0.7403 | 2776000 | 0.079 |
1210
+ | 0.7406 | 2777000 | 0.0737 |
1211
+ | 0.7408 | 2778000 | 0.0751 |
1212
+ | 0.7411 | 2779000 | 0.074 |
1213
+ | 0.7414 | 2780000 | 0.0737 |
1214
+ | 0.7416 | 2781000 | 0.0814 |
1215
+ | 0.7419 | 2782000 | 0.0779 |
1216
+ | 0.7422 | 2783000 | 0.0769 |
1217
+ | 0.7424 | 2784000 | 0.0798 |
1218
+ | 0.7427 | 2785000 | 0.077 |
1219
+ | 0.7430 | 2786000 | 0.0713 |
1220
+ | 0.7432 | 2787000 | 0.0719 |
1221
+ | 0.7435 | 2788000 | 0.0776 |
1222
+ | 0.7438 | 2789000 | 0.0818 |
1223
+ | 0.7440 | 2790000 | 0.0763 |
1224
+ | 0.7443 | 2791000 | 0.0759 |
1225
+ | 0.7446 | 2792000 | 0.0753 |
1226
+ | 0.7448 | 2793000 | 0.0736 |
1227
+ | 0.7451 | 2794000 | 0.0801 |
1228
+ | 0.7454 | 2795000 | 0.0722 |
1229
+ | 0.7456 | 2796000 | 0.081 |
1230
+ | 0.7459 | 2797000 | 0.0714 |
1231
+ | 0.7462 | 2798000 | 0.0762 |
1232
+ | 0.7464 | 2799000 | 0.0809 |
1233
+ | 0.7467 | 2800000 | 0.0816 |
1234
+ | 0.7470 | 2801000 | 0.0794 |
1235
+ | 0.7472 | 2802000 | 0.078 |
1236
+ | 0.7475 | 2803000 | 0.0758 |
1237
+ | 0.7478 | 2804000 | 0.0796 |
1238
+ | 0.7480 | 2805000 | 0.0763 |
1239
+ | 0.7483 | 2806000 | 0.0751 |
1240
+ | 0.7486 | 2807000 | 0.0741 |
1241
+ | 0.7488 | 2808000 | 0.0777 |
1242
+ | 0.7491 | 2809000 | 0.0795 |
1243
+ | 0.7494 | 2810000 | 0.0806 |
1244
+ | 0.7496 | 2811000 | 0.0768 |
1245
+ | 0.7499 | 2812000 | 0.0774 |
1246
+ | 0.7502 | 2813000 | 0.0725 |
1247
+ | 0.7504 | 2814000 | 0.0791 |
1248
+ | 0.7507 | 2815000 | 0.0747 |
1249
+ | 0.7510 | 2816000 | 0.078 |
1250
+ | 0.7512 | 2817000 | 0.0789 |
1251
+ | 0.7515 | 2818000 | 0.0725 |
1252
+ | 0.7518 | 2819000 | 0.0764 |
1253
+ | 0.7520 | 2820000 | 0.0809 |
1254
+ | 0.7523 | 2821000 | 0.0706 |
1255
+ | 0.7526 | 2822000 | 0.0705 |
1256
+ | 0.7528 | 2823000 | 0.0733 |
1257
+ | 0.7531 | 2824000 | 0.0756 |
1258
+ | 0.7534 | 2825000 | 0.0805 |
1259
+ | 0.7536 | 2826000 | 0.0745 |
1260
+ | 0.7539 | 2827000 | 0.08 |
1261
+ | 0.7542 | 2828000 | 0.0687 |
1262
+ | 0.7544 | 2829000 | 0.0788 |
1263
+ | 0.7547 | 2830000 | 0.0763 |
1264
+ | 0.7550 | 2831000 | 0.0713 |
1265
+ | 0.7552 | 2832000 | 0.0754 |
1266
+ | 0.7555 | 2833000 | 0.0775 |
1267
+ | 0.7558 | 2834000 | 0.0727 |
1268
+ | 0.7560 | 2835000 | 0.0775 |
1269
+ | 0.7563 | 2836000 | 0.0754 |
1270
+ | 0.7566 | 2837000 | 0.0782 |
1271
+ | 0.7568 | 2838000 | 0.0724 |
1272
+ | 0.7571 | 2839000 | 0.0769 |
1273
+ | 0.7574 | 2840000 | 0.0778 |
1274
+ | 0.7576 | 2841000 | 0.0783 |
1275
+ | 0.7579 | 2842000 | 0.0756 |
1276
+ | 0.7582 | 2843000 | 0.0759 |
1277
+ | 0.7584 | 2844000 | 0.0751 |
1278
+ | 0.7587 | 2845000 | 0.0807 |
1279
+ | 0.7590 | 2846000 | 0.0748 |
1280
+ | 0.7592 | 2847000 | 0.0744 |
1281
+ | 0.7595 | 2848000 | 0.079 |
1282
+ | 0.7598 | 2849000 | 0.0741 |
1283
+ | 0.7600 | 2850000 | 0.0743 |
1284
+ | 0.7603 | 2851000 | 0.0745 |
1285
+ | 0.7606 | 2852000 | 0.0756 |
1286
+ | 0.7608 | 2853000 | 0.0732 |
1287
+ | 0.7611 | 2854000 | 0.0746 |
1288
+ | 0.7614 | 2855000 | 0.0854 |
1289
+ | 0.7616 | 2856000 | 0.0656 |
1290
+ | 0.7619 | 2857000 | 0.0757 |
1291
+ | 0.7622 | 2858000 | 0.077 |
1292
+ | 0.7624 | 2859000 | 0.0745 |
1293
+ | 0.7627 | 2860000 | 0.0726 |
1294
+ | 0.7630 | 2861000 | 0.0765 |
1295
+ | 0.7632 | 2862000 | 0.0754 |
1296
+ | 0.7635 | 2863000 | 0.0792 |
1297
+ | 0.7638 | 2864000 | 0.0841 |
1298
+ | 0.7640 | 2865000 | 0.0773 |
1299
+ | 0.7643 | 2866000 | 0.0801 |
1300
+ | 0.7646 | 2867000 | 0.0693 |
1301
+ | 0.7648 | 2868000 | 0.0767 |
1302
+ | 0.7651 | 2869000 | 0.0768 |
1303
+ | 0.7654 | 2870000 | 0.069 |
1304
+ | 0.7656 | 2871000 | 0.073 |
1305
+ | 0.7659 | 2872000 | 0.0774 |
1306
+ | 0.7662 | 2873000 | 0.0731 |
1307
+ | 0.7664 | 2874000 | 0.0769 |
1308
+ | 0.7667 | 2875000 | 0.0766 |
1309
+ | 0.7670 | 2876000 | 0.0719 |
1310
+ | 0.7672 | 2877000 | 0.0725 |
1311
+ | 0.7675 | 2878000 | 0.079 |
1312
+ | 0.7678 | 2879000 | 0.0754 |
1313
+ | 0.7680 | 2880000 | 0.0671 |
1314
+ | 0.7683 | 2881000 | 0.0798 |
1315
+ | 0.7686 | 2882000 | 0.0712 |
1316
+ | 0.7688 | 2883000 | 0.0699 |
1317
+ | 0.7691 | 2884000 | 0.0765 |
1318
+ | 0.7694 | 2885000 | 0.0762 |
1319
+ | 0.7696 | 2886000 | 0.0746 |
1320
+ | 0.7699 | 2887000 | 0.0729 |
1321
+ | 0.7702 | 2888000 | 0.078 |
1322
+ | 0.7704 | 2889000 | 0.0712 |
1323
+ | 0.7707 | 2890000 | 0.073 |
1324
+ | 0.7710 | 2891000 | 0.078 |
1325
+ | 0.7712 | 2892000 | 0.0744 |
1326
+ | 0.7715 | 2893000 | 0.0692 |
1327
+ | 0.7718 | 2894000 | 0.0703 |
1328
+ | 0.7720 | 2895000 | 0.0767 |
1329
+ | 0.7723 | 2896000 | 0.0754 |
1330
+ | 0.7726 | 2897000 | 0.0751 |
1331
+ | 0.7728 | 2898000 | 0.0753 |
1332
+ | 0.7731 | 2899000 | 0.0823 |
1333
+ | 0.7734 | 2900000 | 0.0782 |
1334
+ | 0.7736 | 2901000 | 0.0793 |
1335
+ | 0.7739 | 2902000 | 0.0686 |
1336
+ | 0.7742 | 2903000 | 0.0727 |
1337
+ | 0.7744 | 2904000 | 0.0737 |
1338
+ | 0.7747 | 2905000 | 0.0717 |
1339
+ | 0.7750 | 2906000 | 0.0794 |
1340
+ | 0.7752 | 2907000 | 0.0722 |
1341
+ | 0.7755 | 2908000 | 0.0738 |
1342
+ | 0.7758 | 2909000 | 0.0778 |
1343
+ | 0.7760 | 2910000 | 0.0765 |
1344
+ | 0.7763 | 2911000 | 0.0772 |
1345
+ | 0.7766 | 2912000 | 0.0775 |
1346
+ | 0.7768 | 2913000 | 0.0733 |
1347
+ | 0.7771 | 2914000 | 0.0718 |
1348
+ | 0.7774 | 2915000 | 0.0743 |
1349
+ | 0.7776 | 2916000 | 0.0614 |
1350
+ | 0.7779 | 2917000 | 0.0736 |
1351
+ | 0.7782 | 2918000 | 0.0792 |
1352
+ | 0.7784 | 2919000 | 0.0716 |
1353
+ | 0.7787 | 2920000 | 0.0695 |
1354
+ | 0.7790 | 2921000 | 0.0735 |
1355
+ | 0.7792 | 2922000 | 0.074 |
1356
+ | 0.7795 | 2923000 | 0.0723 |
1357
+ | 0.7798 | 2924000 | 0.0662 |
1358
+ | 0.7800 | 2925000 | 0.0674 |
1359
+ | 0.7803 | 2926000 | 0.0771 |
1360
+ | 0.7806 | 2927000 | 0.0706 |
1361
+ | 0.7808 | 2928000 | 0.0756 |
1362
+ | 0.7811 | 2929000 | 0.0758 |
1363
+ | 0.7814 | 2930000 | 0.0828 |
1364
+ | 0.7816 | 2931000 | 0.075 |
1365
+ | 0.7819 | 2932000 | 0.079 |
1366
+ | 0.7822 | 2933000 | 0.0658 |
1367
+ | 0.7824 | 2934000 | 0.076 |
1368
+ | 0.7827 | 2935000 | 0.0776 |
1369
+ | 0.7830 | 2936000 | 0.0758 |
1370
+ | 0.7832 | 2937000 | 0.0748 |
1371
+ | 0.7835 | 2938000 | 0.0764 |
1372
+ | 0.7838 | 2939000 | 0.0745 |
1373
+ | 0.7840 | 2940000 | 0.0752 |
1374
+ | 0.7843 | 2941000 | 0.076 |
1375
+ | 0.7846 | 2942000 | 0.0772 |
1376
+ | 0.7848 | 2943000 | 0.0774 |
1377
+ | 0.7851 | 2944000 | 0.0799 |
1378
+ | 0.7854 | 2945000 | 0.0715 |
1379
+ | 0.7856 | 2946000 | 0.0696 |
1380
+ | 0.7859 | 2947000 | 0.0787 |
1381
+ | 0.7862 | 2948000 | 0.0817 |
1382
+ | 0.7864 | 2949000 | 0.066 |
1383
+ | 0.7867 | 2950000 | 0.0738 |
1384
+ | 0.7870 | 2951000 | 0.0749 |
1385
+ | 0.7872 | 2952000 | 0.0796 |
1386
+ | 0.7875 | 2953000 | 0.0761 |
1387
+ | 0.7878 | 2954000 | 0.0706 |
1388
+ | 0.7880 | 2955000 | 0.0716 |
1389
+ | 0.7883 | 2956000 | 0.0712 |
1390
+ | 0.7886 | 2957000 | 0.0699 |
1391
+ | 0.7888 | 2958000 | 0.0736 |
1392
+ | 0.7891 | 2959000 | 0.078 |
1393
+ | 0.7894 | 2960000 | 0.0735 |
1394
+ | 0.7896 | 2961000 | 0.0698 |
1395
+ | 0.7899 | 2962000 | 0.07 |
1396
+ | 0.7902 | 2963000 | 0.081 |
1397
+ | 0.7904 | 2964000 | 0.0737 |
1398
+ | 0.7907 | 2965000 | 0.0753 |
1399
+ | 0.7910 | 2966000 | 0.0694 |
1400
+ | 0.7912 | 2967000 | 0.0772 |
1401
+ | 0.7915 | 2968000 | 0.0779 |
1402
+ | 0.7918 | 2969000 | 0.0677 |
1403
+ | 0.7920 | 2970000 | 0.074 |
1404
+ | 0.7923 | 2971000 | 0.0737 |
1405
+ | 0.7926 | 2972000 | 0.0822 |
1406
+ | 0.7928 | 2973000 | 0.0697 |
1407
+ | 0.7931 | 2974000 | 0.0795 |
1408
+ | 0.7934 | 2975000 | 0.0734 |
1409
+ | 0.7936 | 2976000 | 0.0712 |
1410
+ | 0.7939 | 2977000 | 0.0794 |
1411
+ | 0.7942 | 2978000 | 0.0753 |
1412
+ | 0.7944 | 2979000 | 0.07 |
1413
+ | 0.7947 | 2980000 | 0.0759 |
1414
+ | 0.7950 | 2981000 | 0.0754 |
1415
+ | 0.7952 | 2982000 | 0.0735 |
1416
+ | 0.7955 | 2983000 | 0.0778 |
1417
+ | 0.7958 | 2984000 | 0.0659 |
1418
+ | 0.7960 | 2985000 | 0.0799 |
1419
+ | 0.7963 | 2986000 | 0.0734 |
1420
+ | 0.7966 | 2987000 | 0.0741 |
1421
+ | 0.7968 | 2988000 | 0.073 |
1422
+ | 0.7971 | 2989000 | 0.0714 |
1423
+ | 0.7974 | 2990000 | 0.0703 |
1424
+ | 0.7976 | 2991000 | 0.0748 |
1425
+ | 0.7979 | 2992000 | 0.0783 |
1426
+ | 0.7982 | 2993000 | 0.0756 |
1427
+ | 0.7984 | 2994000 | 0.0782 |
1428
+ | 0.7987 | 2995000 | 0.0813 |
1429
+ | 0.7990 | 2996000 | 0.0746 |
1430
+ | 0.7992 | 2997000 | 0.0713 |
1431
+ | 0.7995 | 2998000 | 0.08 |
1432
+ | 0.7998 | 2999000 | 0.0716 |
1433
+ | 0.8000 | 3000000 | 0.077 |
1434
+ | 0.8003 | 3001000 | 0.0726 |
1435
+ | 0.8006 | 3002000 | 0.0719 |
1436
+ | 0.8008 | 3003000 | 0.0741 |
1437
+ | 0.8011 | 3004000 | 0.0722 |
1438
+ | 0.8014 | 3005000 | 0.0723 |
1439
+ | 0.8016 | 3006000 | 0.0761 |
1440
+ | 0.8019 | 3007000 | 0.0737 |
1441
+ | 0.8022 | 3008000 | 0.0733 |
1442
+ | 0.8024 | 3009000 | 0.0733 |
1443
+ | 0.8027 | 3010000 | 0.0766 |
1444
+ | 0.8030 | 3011000 | 0.0742 |
1445
+ | 0.8032 | 3012000 | 0.0701 |
1446
+ | 0.8035 | 3013000 | 0.074 |
1447
+ | 0.8038 | 3014000 | 0.0724 |
1448
+ | 0.8040 | 3015000 | 0.0746 |
1449
+ | 0.8043 | 3016000 | 0.0748 |
1450
+ | 0.8046 | 3017000 | 0.0703 |
1451
+ | 0.8048 | 3018000 | 0.074 |
1452
+ | 0.8051 | 3019000 | 0.0718 |
1453
+ | 0.8054 | 3020000 | 0.0732 |
1454
+ | 0.8056 | 3021000 | 0.0761 |
1455
+ | 0.8059 | 3022000 | 0.0683 |
1456
+ | 0.8062 | 3023000 | 0.0739 |
1457
+ | 0.8064 | 3024000 | 0.0703 |
1458
+ | 0.8067 | 3025000 | 0.069 |
1459
+ | 0.8070 | 3026000 | 0.071 |
1460
+ | 0.8072 | 3027000 | 0.0722 |
1461
+ | 0.8075 | 3028000 | 0.0781 |
1462
+ | 0.8078 | 3029000 | 0.0743 |
1463
+ | 0.8080 | 3030000 | 0.0759 |
1464
+ | 0.8083 | 3031000 | 0.0706 |
1465
+ | 0.8086 | 3032000 | 0.0749 |
1466
+ | 0.8088 | 3033000 | 0.0795 |
1467
+ | 0.8091 | 3034000 | 0.0741 |
1468
+ | 0.8094 | 3035000 | 0.0677 |
1469
+ | 0.8096 | 3036000 | 0.0737 |
1470
+ | 0.8099 | 3037000 | 0.0745 |
1471
+ | 0.8102 | 3038000 | 0.0729 |
1472
+ | 0.8104 | 3039000 | 0.0725 |
1473
+ | 0.8107 | 3040000 | 0.0724 |
1474
+ | 0.8110 | 3041000 | 0.0734 |
1475
+ | 0.8112 | 3042000 | 0.0706 |
1476
+ | 0.8115 | 3043000 | 0.0728 |
1477
+ | 0.8118 | 3044000 | 0.0801 |
1478
+ | 0.8120 | 3045000 | 0.068 |
1479
+ | 0.8123 | 3046000 | 0.0805 |
1480
+ | 0.8126 | 3047000 | 0.069 |
1481
+ | 0.8128 | 3048000 | 0.0688 |
1482
+ | 0.8131 | 3049000 | 0.0716 |
1483
+ | 0.8134 | 3050000 | 0.0726 |
1484
+ | 0.8136 | 3051000 | 0.0742 |
1485
+ | 0.8139 | 3052000 | 0.073 |
1486
+ | 0.8142 | 3053000 | 0.0774 |
1487
+ | 0.8144 | 3054000 | 0.0692 |
1488
+ | 0.8147 | 3055000 | 0.0717 |
1489
+ | 0.8150 | 3056000 | 0.0805 |
1490
+ | 0.8152 | 3057000 | 0.074 |
1491
+ | 0.8155 | 3058000 | 0.0712 |
1492
+ | 0.8158 | 3059000 | 0.0752 |
1493
+ | 0.8160 | 3060000 | 0.0715 |
1494
+ | 0.8163 | 3061000 | 0.0761 |
1495
+ | 0.8166 | 3062000 | 0.0779 |
1496
+ | 0.8168 | 3063000 | 0.0716 |
1497
+ | 0.8171 | 3064000 | 0.076 |
1498
+ | 0.8174 | 3065000 | 0.071 |
1499
+ | 0.8176 | 3066000 | 0.0717 |
1500
+ | 0.8179 | 3067000 | 0.0726 |
1501
+ | 0.8182 | 3068000 | 0.0747 |
1502
+ | 0.8184 | 3069000 | 0.0736 |
1503
+ | 0.8187 | 3070000 | 0.0772 |
1504
+ | 0.8190 | 3071000 | 0.071 |
1505
+ | 0.8192 | 3072000 | 0.0715 |
1506
+ | 0.8195 | 3073000 | 0.0769 |
1507
+ | 0.8198 | 3074000 | 0.071 |
1508
+ | 0.8200 | 3075000 | 0.073 |
1509
+ | 0.8203 | 3076000 | 0.0659 |
1510
+ | 0.8206 | 3077000 | 0.0797 |
1511
+ | 0.8208 | 3078000 | 0.072 |
1512
+ | 0.8211 | 3079000 | 0.0726 |
1513
+ | 0.8214 | 3080000 | 0.0729 |
1514
+ | 0.8216 | 3081000 | 0.0773 |
1515
+ | 0.8219 | 3082000 | 0.0768 |
1516
+ | 0.8222 | 3083000 | 0.0691 |
1517
+ | 0.8224 | 3084000 | 0.0771 |
1518
+ | 0.8227 | 3085000 | 0.0685 |
1519
+ | 0.8230 | 3086000 | 0.0684 |
1520
+ | 0.8232 | 3087000 | 0.0727 |
1521
+ | 0.8235 | 3088000 | 0.0768 |
1522
+ | 0.8238 | 3089000 | 0.0776 |
1523
+ | 0.8240 | 3090000 | 0.0708 |
1524
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1525
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1526
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1527
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1528
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1529
+ | 0.8256 | 3096000 | 0.0745 |
1530
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1531
+ | 0.8262 | 3098000 | 0.0774 |
1532
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1533
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1534
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1535
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1536
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1537
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1538
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1539
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1540
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1541
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1542
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1543
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1544
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1545
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1546
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1547
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1548
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1549
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1550
+ | 0.8312 | 3117000 | 0.0718 |
1551
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1552
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1553
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1554
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1555
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1556
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1557
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1558
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1559
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1560
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1561
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1562
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1563
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1564
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1565
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1566
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1567
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1568
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1569
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1570
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1571
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1572
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1573
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1574
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1575
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1576
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1577
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1578
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1579
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1580
+ | 0.8392 | 3147000 | 0.0724 |
1581
+ | 0.8395 | 3148000 | 0.0688 |
1582
+ | 0.8398 | 3149000 | 0.0683 |
1583
+ | 0.8400 | 3150000 | 0.0739 |
1584
+ | 0.8403 | 3151000 | 0.0759 |
1585
+ | 0.8406 | 3152000 | 0.0708 |
1586
+ | 0.8408 | 3153000 | 0.0772 |
1587
+ | 0.8411 | 3154000 | 0.0719 |
1588
+ | 0.8414 | 3155000 | 0.0702 |
1589
+ | 0.8416 | 3156000 | 0.0777 |
1590
+ | 0.8419 | 3157000 | 0.0729 |
1591
+ | 0.8422 | 3158000 | 0.0733 |
1592
+ | 0.8424 | 3159000 | 0.0718 |
1593
+ | 0.8427 | 3160000 | 0.0765 |
1594
+ | 0.8430 | 3161000 | 0.0714 |
1595
+ | 0.8432 | 3162000 | 0.071 |
1596
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1597
+ | 0.8438 | 3164000 | 0.0734 |
1598
+ | 0.8440 | 3165000 | 0.0755 |
1599
+ | 0.8443 | 3166000 | 0.0681 |
1600
+ | 0.8446 | 3167000 | 0.0721 |
1601
+ | 0.8448 | 3168000 | 0.0678 |
1602
+ | 0.8451 | 3169000 | 0.062 |
1603
+ | 0.8454 | 3170000 | 0.076 |
1604
+ | 0.8456 | 3171000 | 0.0668 |
1605
+ | 0.8459 | 3172000 | 0.076 |
1606
+ | 0.8462 | 3173000 | 0.0665 |
1607
+ | 0.8464 | 3174000 | 0.076 |
1608
+ | 0.8467 | 3175000 | 0.0716 |
1609
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1610
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1611
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1612
+ | 0.8478 | 3179000 | 0.0691 |
1613
+ | 0.8480 | 3180000 | 0.0675 |
1614
+ | 0.8483 | 3181000 | 0.0661 |
1615
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1616
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1617
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1618
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1619
+ | 0.8496 | 3186000 | 0.0775 |
1620
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1621
+ | 0.8502 | 3188000 | 0.074 |
1622
+ | 0.8504 | 3189000 | 0.0705 |
1623
+ | 0.8507 | 3190000 | 0.0778 |
1624
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1625
+ | 0.8512 | 3192000 | 0.0708 |
1626
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1627
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1628
+ | 0.8520 | 3195000 | 0.0742 |
1629
+ | 0.8523 | 3196000 | 0.0753 |
1630
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1631
+ | 0.8528 | 3198000 | 0.0737 |
1632
+ | 0.8531 | 3199000 | 0.0726 |
1633
+ | 0.8534 | 3200000 | 0.0792 |
1634
+ | 0.8536 | 3201000 | 0.0697 |
1635
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1636
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1637
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1638
+ | 0.8547 | 3205000 | 0.0714 |
1639
+ | 0.8550 | 3206000 | 0.0675 |
1640
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1641
+ | 0.8555 | 3208000 | 0.0741 |
1642
+ | 0.8558 | 3209000 | 0.0708 |
1643
+ | 0.8560 | 3210000 | 0.0777 |
1644
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1645
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1646
+ | 0.8568 | 3213000 | 0.0707 |
1647
+ | 0.8571 | 3214000 | 0.0716 |
1648
+ | 0.8574 | 3215000 | 0.0726 |
1649
+ | 0.8576 | 3216000 | 0.0743 |
1650
+ | 0.8579 | 3217000 | 0.0754 |
1651
+ | 0.8582 | 3218000 | 0.0713 |
1652
+ | 0.8584 | 3219000 | 0.0776 |
1653
+ | 0.8587 | 3220000 | 0.0754 |
1654
+ | 0.8590 | 3221000 | 0.0716 |
1655
+ | 0.8592 | 3222000 | 0.0762 |
1656
+ | 0.8595 | 3223000 | 0.079 |
1657
+ | 0.8598 | 3224000 | 0.0647 |
1658
+ | 0.8600 | 3225000 | 0.0733 |
1659
+ | 0.8603 | 3226000 | 0.0811 |
1660
+ | 0.8606 | 3227000 | 0.0683 |
1661
+ | 0.8608 | 3228000 | 0.0753 |
1662
+ | 0.8611 | 3229000 | 0.0718 |
1663
+ | 0.8614 | 3230000 | 0.0673 |
1664
+ | 0.8616 | 3231000 | 0.0738 |
1665
+ | 0.8619 | 3232000 | 0.0688 |
1666
+ | 0.8622 | 3233000 | 0.0705 |
1667
+ | 0.8624 | 3234000 | 0.0715 |
1668
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1669
+ | 0.8630 | 3236000 | 0.0737 |
1670
+ | 0.8632 | 3237000 | 0.0709 |
1671
+ | 0.8635 | 3238000 | 0.0677 |
1672
+ | 0.8638 | 3239000 | 0.0663 |
1673
+ | 0.8640 | 3240000 | 0.0783 |
1674
+ | 0.8643 | 3241000 | 0.0719 |
1675
+ | 0.8646 | 3242000 | 0.0715 |
1676
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1677
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1678
+ | 0.8654 | 3245000 | 0.0758 |
1679
+ | 0.8656 | 3246000 | 0.0756 |
1680
+ | 0.8659 | 3247000 | 0.07 |
1681
+ | 0.8662 | 3248000 | 0.0716 |
1682
+ | 0.8664 | 3249000 | 0.0696 |
1683
+ | 0.8667 | 3250000 | 0.0743 |
1684
+ | 0.8670 | 3251000 | 0.0728 |
1685
+ | 0.8672 | 3252000 | 0.067 |
1686
+ | 0.8675 | 3253000 | 0.0706 |
1687
+ | 0.8678 | 3254000 | 0.0696 |
1688
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1689
+ | 0.8683 | 3256000 | 0.0741 |
1690
+ | 0.8686 | 3257000 | 0.0812 |
1691
+ | 0.8688 | 3258000 | 0.0734 |
1692
+ | 0.8691 | 3259000 | 0.0732 |
1693
+ | 0.8694 | 3260000 | 0.0725 |
1694
+ | 0.8696 | 3261000 | 0.0681 |
1695
+ | 0.8699 | 3262000 | 0.0703 |
1696
+ | 0.8702 | 3263000 | 0.0717 |
1697
+ | 0.8704 | 3264000 | 0.0721 |
1698
+ | 0.8707 | 3265000 | 0.0725 |
1699
+ | 0.8710 | 3266000 | 0.072 |
1700
+ | 0.8712 | 3267000 | 0.0732 |
1701
+ | 0.8715 | 3268000 | 0.0717 |
1702
+ | 0.8718 | 3269000 | 0.0717 |
1703
+ | 0.8720 | 3270000 | 0.0696 |
1704
+ | 0.8723 | 3271000 | 0.069 |
1705
+ | 0.8726 | 3272000 | 0.0674 |
1706
+ | 0.8728 | 3273000 | 0.0715 |
1707
+ | 0.8731 | 3274000 | 0.0726 |
1708
+ | 0.8734 | 3275000 | 0.0738 |
1709
+ | 0.8736 | 3276000 | 0.064 |
1710
+ | 0.8739 | 3277000 | 0.0783 |
1711
+ | 0.8742 | 3278000 | 0.072 |
1712
+ | 0.8744 | 3279000 | 0.0709 |
1713
+ | 0.8747 | 3280000 | 0.0695 |
1714
+ | 0.8750 | 3281000 | 0.0715 |
1715
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1716
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1717
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1718
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1719
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1720
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1721
+ | 0.8768 | 3288000 | 0.0695 |
1722
+ | 0.8771 | 3289000 | 0.0679 |
1723
+ | 0.8774 | 3290000 | 0.0762 |
1724
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1725
+ | 0.8779 | 3292000 | 0.0723 |
1726
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1727
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1728
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1729
+ | 0.8790 | 3296000 | 0.0693 |
1730
+ | 0.8792 | 3297000 | 0.0765 |
1731
+ | 0.8795 | 3298000 | 0.0701 |
1732
+ | 0.8798 | 3299000 | 0.0635 |
1733
+ | 0.8800 | 3300000 | 0.0713 |
1734
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1735
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1736
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1737
+ | 0.8811 | 3304000 | 0.0676 |
1738
+ | 0.8814 | 3305000 | 0.0693 |
1739
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1740
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1741
+ | 0.8822 | 3308000 | 0.0656 |
1742
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1743
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1744
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1745
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1746
+ | 0.8835 | 3313000 | 0.0708 |
1747
+ | 0.8838 | 3314000 | 0.0697 |
1748
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1749
+ | 0.8843 | 3316000 | 0.0739 |
1750
+ | 0.8846 | 3317000 | 0.077 |
1751
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1752
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1753
+ | 0.8854 | 3320000 | 0.0708 |
1754
+ | 0.8856 | 3321000 | 0.0728 |
1755
+ | 0.8859 | 3322000 | 0.0723 |
1756
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1757
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1758
+ | 0.8867 | 3325000 | 0.0775 |
1759
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1760
+ | 0.8872 | 3327000 | 0.0687 |
1761
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1762
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1763
+ | 0.8880 | 3330000 | 0.0711 |
1764
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1765
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1766
+ | 0.8888 | 3333000 | 0.0712 |
1767
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1768
+ | 0.8894 | 3335000 | 0.0721 |
1769
+ | 0.8896 | 3336000 | 0.0683 |
1770
+ | 0.8899 | 3337000 | 0.0773 |
1771
+ | 0.8902 | 3338000 | 0.0632 |
1772
+ | 0.8904 | 3339000 | 0.0695 |
1773
+ | 0.8907 | 3340000 | 0.0696 |
1774
+ | 0.8910 | 3341000 | 0.0687 |
1775
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1776
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1777
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1778
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1779
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1780
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1781
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1782
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1783
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1784
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1785
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1786
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1787
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1788
+ | 0.8947 | 3355000 | 0.0723 |
1789
+ | 0.8950 | 3356000 | 0.0779 |
1790
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1791
+ | 0.8955 | 3358000 | 0.0717 |
1792
+ | 0.8958 | 3359000 | 0.0734 |
1793
+ | 0.8960 | 3360000 | 0.0731 |
1794
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1795
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1796
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1797
+ | 0.8971 | 3364000 | 0.0728 |
1798
+ | 0.8974 | 3365000 | 0.0664 |
1799
+ | 0.8976 | 3366000 | 0.0695 |
1800
+ | 0.8979 | 3367000 | 0.0735 |
1801
+ | 0.8982 | 3368000 | 0.0705 |
1802
+ | 0.8984 | 3369000 | 0.0765 |
1803
+ | 0.8987 | 3370000 | 0.073 |
1804
+ | 0.8990 | 3371000 | 0.07 |
1805
+ | 0.8992 | 3372000 | 0.0734 |
1806
+ | 0.8995 | 3373000 | 0.0716 |
1807
+ | 0.8998 | 3374000 | 0.0746 |
1808
+ | 0.9000 | 3375000 | 0.062 |
1809
+ | 0.9003 | 3376000 | 0.0677 |
1810
+ | 0.9006 | 3377000 | 0.069 |
1811
+ | 0.9008 | 3378000 | 0.0708 |
1812
+ | 0.9011 | 3379000 | 0.0704 |
1813
+ | 0.9014 | 3380000 | 0.0701 |
1814
+ | 0.9016 | 3381000 | 0.066 |
1815
+ | 0.9019 | 3382000 | 0.0667 |
1816
+ | 0.9022 | 3383000 | 0.0637 |
1817
+ | 0.9024 | 3384000 | 0.0697 |
1818
+ | 0.9027 | 3385000 | 0.0682 |
1819
+ | 0.9030 | 3386000 | 0.069 |
1820
+ | 0.9032 | 3387000 | 0.0728 |
1821
+ | 0.9035 | 3388000 | 0.0748 |
1822
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1823
+ | 0.9040 | 3390000 | 0.0618 |
1824
+ | 0.9043 | 3391000 | 0.0735 |
1825
+ | 0.9046 | 3392000 | 0.0707 |
1826
+ | 0.9048 | 3393000 | 0.0769 |
1827
+ | 0.9051 | 3394000 | 0.0759 |
1828
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1829
+ | 0.9056 | 3396000 | 0.0744 |
1830
+ | 0.9059 | 3397000 | 0.0771 |
1831
+ | 0.9062 | 3398000 | 0.0676 |
1832
+ | 0.9064 | 3399000 | 0.0721 |
1833
+ | 0.9067 | 3400000 | 0.0711 |
1834
+ | 0.9070 | 3401000 | 0.0751 |
1835
+ | 0.9072 | 3402000 | 0.0699 |
1836
+ | 0.9075 | 3403000 | 0.0682 |
1837
+ | 0.9078 | 3404000 | 0.0706 |
1838
+ | 0.9080 | 3405000 | 0.0738 |
1839
+ | 0.9083 | 3406000 | 0.0694 |
1840
+ | 0.9086 | 3407000 | 0.071 |
1841
+ | 0.9088 | 3408000 | 0.0715 |
1842
+ | 0.9091 | 3409000 | 0.0671 |
1843
+ | 0.9094 | 3410000 | 0.0702 |
1844
+ | 0.9096 | 3411000 | 0.0745 |
1845
+ | 0.9099 | 3412000 | 0.0727 |
1846
+ | 0.9102 | 3413000 | 0.0718 |
1847
+ | 0.9104 | 3414000 | 0.0643 |
1848
+ | 0.9107 | 3415000 | 0.0713 |
1849
+ | 0.9110 | 3416000 | 0.0705 |
1850
+ | 0.9112 | 3417000 | 0.0673 |
1851
+ | 0.9115 | 3418000 | 0.0666 |
1852
+ | 0.9118 | 3419000 | 0.0736 |
1853
+ | 0.9120 | 3420000 | 0.0689 |
1854
+ | 0.9123 | 3421000 | 0.0706 |
1855
+ | 0.9126 | 3422000 | 0.0716 |
1856
+ | 0.9128 | 3423000 | 0.0697 |
1857
+ | 0.9131 | 3424000 | 0.0736 |
1858
+ | 0.9134 | 3425000 | 0.0679 |
1859
+ | 0.9136 | 3426000 | 0.0683 |
1860
+ | 0.9139 | 3427000 | 0.0735 |
1861
+ | 0.9142 | 3428000 | 0.0669 |
1862
+ | 0.9144 | 3429000 | 0.0688 |
1863
+ | 0.9147 | 3430000 | 0.0689 |
1864
+ | 0.9150 | 3431000 | 0.0707 |
1865
+ | 0.9152 | 3432000 | 0.0752 |
1866
+ | 0.9155 | 3433000 | 0.0741 |
1867
+ | 0.9158 | 3434000 | 0.0721 |
1868
+ | 0.9160 | 3435000 | 0.0605 |
1869
+ | 0.9163 | 3436000 | 0.0721 |
1870
+ | 0.9166 | 3437000 | 0.072 |
1871
+ | 0.9168 | 3438000 | 0.0681 |
1872
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1873
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1970
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1971
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1972
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1973
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1974
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1975
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1976
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1977
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1978
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1979
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1980
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1981
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1982
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1983
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1984
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1985
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1986
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1987
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1988
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1989
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1990
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1991
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1992
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1993
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1994
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1995
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1996
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1997
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1998
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1999
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2000
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2001
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2002
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2003
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2004
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2005
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2006
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2007
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2009
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2010
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2011
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2012
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2013
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2014
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2015
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2016
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2017
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2018
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2019
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2020
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2021
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2022
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2023
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2024
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2025
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2026
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2027
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2028
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2029
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2030
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2031
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2032
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2035
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2037
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2038
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2039
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2040
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2041
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2042
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2043
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2044
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2045
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2046
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2047
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2048
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2049
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2054
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2182
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2183
+
2184
+ </details>
2185
+
2186
+ ### Framework Versions
2187
+ - Python: 3.12.2
2188
+ - Sentence Transformers: 3.2.1
2189
+ - Transformers: 4.46.1
2190
+ - PyTorch: 2.5.0
2191
+ - Accelerate: 1.0.1
2192
+ - Datasets: 3.0.2
2193
+ - Tokenizers: 0.20.1
2194
+
2195
+ ## Citation
2196
+
2197
+ ### BibTeX
2198
+
2199
+ #### Sentence Transformers
2200
+ ```bibtex
2201
+ @inproceedings{reimers-2019-sentence-bert,
2202
+ title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
2203
+ author = "Reimers, Nils and Gurevych, Iryna",
2204
+ booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
2205
+ month = "11",
2206
+ year = "2019",
2207
+ publisher = "Association for Computational Linguistics",
2208
+ url = "https://arxiv.org/abs/1908.10084",
2209
+ }
2210
+ ```
2211
+
2212
+ #### CustomTripletLoss
2213
+ ```bibtex
2214
+ @misc{hermans2017defense,
2215
+ title={In Defense of the Triplet Loss for Person Re-Identification},
2216
+ author={Alexander Hermans and Lucas Beyer and Bastian Leibe},
2217
+ year={2017},
2218
+ eprint={1703.07737},
2219
+ archivePrefix={arXiv},
2220
+ primaryClass={cs.CV}
2221
+ }
2222
+ ```
2223
+
2224
+ <!--
2225
+ ## Glossary
2226
+
2227
+ *Clearly define terms in order to be accessible across audiences.*
2228
+ -->
2229
+
2230
+ <!--
2231
+ ## Model Card Authors
2232
+
2233
+ *Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.*
2234
+ -->
2235
+
2236
+ <!--
2237
+ ## Model Card Contact
2238
+
2239
+ *Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.*
2240
+ -->
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+ },
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+ "path": "1_Pooling",
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+ "type": "sentence_transformers.models.Pooling"
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+ }
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+ ]
sentence_bert_config.json ADDED
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+ {
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+ "max_seq_length": 1024,
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+ "do_lower_case": false
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+ }
special_tokens_map.json ADDED
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+ {
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+ "cls_token": {
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tokenizer.json ADDED
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tokenizer_config.json ADDED
@@ -0,0 +1,64 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ {
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+ "tokenize_chinese_chars": true,
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+ "truncation_side": "right",
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+ "truncation_strategy": "longest_first",
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+ "unk_token": "[UNK]"
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+ }
vocab.txt ADDED
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