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  1. README.md +43 -7
README.md CHANGED
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  language:
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  - tr
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  license: apache-2.0
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- library_name: transformers
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  tags:
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  - sentence-embeddings
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  - sentence-similarity
 
 
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  - turkish
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  - contrastive-learning
 
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  pipeline_tag: sentence-similarity
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  # Turkish Sentence Encoder
@@ -61,12 +97,12 @@ embeddings = model.encode(["Merhaba dünya!", "Selam dünya!"])
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  | Metric | Score |
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  |--------|-------|
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- | Spearman Correlation | 0.8488 |
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- | Pearson Correlation | 0.875 |
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- | Paraphrase Accuracy | 0.8333 |
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- | MRR | 0.95 |
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- | Recall@1 | 0.9 |
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- | Recall@5 | 1.0 |
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  ## Training Details
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  language:
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  - tr
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  license: apache-2.0
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+ library_name: sentence-transformers
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  tags:
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  - sentence-embeddings
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  - sentence-similarity
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+ - sentence-transformers
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+ - feature-extraction
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  - turkish
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  - contrastive-learning
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+ - mteb
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  pipeline_tag: sentence-similarity
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+ model-index:
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+ - name: turkish-sentence-encoder
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+ results:
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+ - task:
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+ type: Classification
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+ dataset:
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+ name: MTEB MassiveIntentClassification (tr)
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+ type: mteb/amazon_massive_intent
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+ config: tr
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+ split: test
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+ metrics:
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+ - type: accuracy
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+ value: 0.0
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+ - task:
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+ type: Classification
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+ dataset:
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+ name: MTEB MassiveScenarioClassification (tr)
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+ type: mteb/amazon_massive_scenario
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+ config: tr
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+ split: test
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+ metrics:
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+ - type: accuracy
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+ value: 0.0
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+ - task:
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+ type: STS
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+ dataset:
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+ name: MTEB STS22 (tr)
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+ type: mteb/sts22-crosslingual-sts
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+ config: tr
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+ split: test
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+ metrics:
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+ - type: cosine_spearman
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+ value: 0.0
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  ---
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  # Turkish Sentence Encoder
 
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  | Metric | Score |
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  |--------|-------|
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+ | Spearman Correlation | 0.7315 |
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+ | Pearson Correlation | 0.8593 |
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+ | Paraphrase Accuracy | 0.9695 |
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+ | MRR | 0.9172 |
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+ | Recall@1 | 0.87 |
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+ | Recall@5 | 0.97 |
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  ## Training Details
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