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Training in progress, epoch 1

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final/README.md CHANGED
@@ -56,6 +56,9 @@ model-index:
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  - type: cosine_accuracy
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  value: 0.9632217288017273
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  name: Cosine Accuracy
 
 
 
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  ---
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  # SentenceTransformer
@@ -119,9 +122,9 @@ print(embeddings.shape)
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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)
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- # tensor([[1.0000, 0.8920, 0.3277],
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- # [0.8920, 1.0000, 0.3290],
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- # [0.3277, 0.3290, 1.0000]])
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  ```
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  <!--
@@ -176,6 +179,14 @@ You can finetune this model on your own dataset.
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  |:--------------------|:-----------|
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  | **cosine_accuracy** | **0.9632** |
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  <!--
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  ## Bias, Risks and Limitations
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@@ -371,6 +382,13 @@ You can finetune this model on your own dataset.
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  | 3.0 | 129 | 1.1581 | - |
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  | 4.0 | 172 | 1.013 | - |
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  | 5.0 | 215 | 0.9318 | - |
 
 
 
 
 
 
 
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  ### Framework Versions
 
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  - type: cosine_accuracy
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  value: 0.9632217288017273
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  name: Cosine Accuracy
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+ - type: cosine_accuracy
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+ value: 0.9583539962768555
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+ name: Cosine Accuracy
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  ---
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  # SentenceTransformer
 
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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)
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+ # tensor([[1.0000, 0.8800, 0.2118],
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+ # [0.8800, 1.0000, 0.2279],
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+ # [0.2118, 0.2279, 1.0000]])
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  ```
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  <!--
 
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  |:--------------------|:-----------|
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  | **cosine_accuracy** | **0.9632** |
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+ #### Triplet
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+
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+ * Evaluated with [<code>TripletEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.TripletEvaluator)
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+
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+ | Metric | Value |
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+ |:--------------------|:-----------|
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+ | **cosine_accuracy** | **0.9584** |
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+
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  <!--
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  ## Bias, Risks and Limitations
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  | 3.0 | 129 | 1.1581 | - |
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  | 4.0 | 172 | 1.013 | - |
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  | 5.0 | 215 | 0.9318 | - |
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+ | -1 | -1 | - | 0.9584 |
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+ | 0.0233 | 1 | 0.6549 | - |
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+ | 1.0 | 43 | 0.5541 | - |
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+ | 2.0 | 86 | 0.5269 | - |
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+ | 3.0 | 129 | 0.6036 | - |
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+ | 4.0 | 172 | 0.6677 | - |
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+ | 5.0 | 215 | 0.7634 | - |
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  ### Framework Versions
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