Add new SentenceTransformer model.

README.md

@@ -372,19 +372,19 @@ model-index:
       type: bge-base-en-train
     metrics:
     - type: cosine_accuracy
-      value: 0.8269230769230769
+      value: 0.8076923076923077
       name: Cosine Accuracy
     - type: dot_accuracy
-      value: 0.17307692307692307
+      value: 0.19230769230769232
       name: Dot Accuracy
     - type: manhattan_accuracy
-      value: 0.8269230769230769
+      value: 0.8076923076923077
       name: Manhattan Accuracy
     - type: euclidean_accuracy
-      value: 0.8269230769230769
+      value: 0.8076923076923077
       name: Euclidean Accuracy
     - type: max_accuracy
-      value: 0.8269230769230769
+      value: 0.8076923076923077
       name: Max Accuracy
   - task:
       type: triplet
@@ -400,13 +400,13 @@ model-index:
       value: 0.015151515151515152
       name: Dot Accuracy
     - type: manhattan_accuracy
-      value: 0.9696969696969697
+      value: 1.0
       name: Manhattan Accuracy
     - type: euclidean_accuracy
       value: 0.9848484848484849
       name: Euclidean Accuracy
     - type: max_accuracy
-      value: 0.9848484848484849
+      value: 1.0
       name: Max Accuracy
 ---
 
@@ -508,23 +508,23 @@ You can finetune this model on your own dataset.
 
 | Metric             | Value      |
 |:-------------------|:-----------|
-| cosine_accuracy    | 0.8269     |
-| dot_accuracy       | 0.1731     |
-| manhattan_accuracy | 0.8269     |
-| euclidean_accuracy | 0.8269     |
-| **max_accuracy**   | **0.8269** |
+| cosine_accuracy    | 0.8077     |
+| dot_accuracy       | 0.1923     |
+| manhattan_accuracy | 0.8077     |
+| euclidean_accuracy | 0.8077     |
+| **max_accuracy**   | **0.8077** |
 
 #### Triplet
 * Dataset: `bge-base-en-eval`
 * Evaluated with [<code>TripletEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.TripletEvaluator)
 
-| Metric             | Value      |
-|:-------------------|:-----------|
-| cosine_accuracy    | 0.9848     |
-| dot_accuracy       | 0.0152     |
-| manhattan_accuracy | 0.9697     |
-| euclidean_accuracy | 0.9848     |
-| **max_accuracy**   | **0.9848** |
+| Metric             | Value   |
+|:-------------------|:--------|
+| cosine_accuracy    | 0.9848  |
+| dot_accuracy       | 0.0152  |
+| manhattan_accuracy | 1.0     |
+| euclidean_accuracy | 0.9848  |
+| **max_accuracy**   | **1.0** |
 
 <!--
 ## Bias, Risks and Limitations
@@ -713,8 +713,8 @@ You can finetune this model on your own dataset.
 ### Training Logs
 | Epoch | Step | bge-base-en-eval_max_accuracy | bge-base-en-train_max_accuracy |
 |:-----:|:----:|:-----------------------------:|:------------------------------:|
-| 0     | 0    | -                             | 0.8269                         |
-| 5.0   | 65   | 0.9848                        | -                              |
+| 0     | 0    | -                             | 0.8077                         |
+| 5.0   | 65   | 1.0                           | -                              |
 
 
 ### Framework Versions