Hugging Face's logo

TextModel
/
Embedding-crime-indo

Sentence Similarity
sentence-transformers
Safetensors
gemma3_text
feature-extraction
dense
Generated from Trainer
dataset_size:2609
loss:MultipleNegativesRankingLoss
Eval Results (legacy)
text-embeddings-inference
Model card Files
xet
 Community
TextModel commited on
Commit
6095780
·
verified ·
1 Parent(s): 6cbf52b

Add new SentenceTransformer model

Browse files
Files changed (4) hide show
  1. 2_Dense/model.safetensors +1 -1
  2. 3_Dense/model.safetensors +1 -1
  3. README.md +12 -12
  4. model.safetensors +1 -1
2_Dense/model.safetensors CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:daaf4704057b68f49b287cd4b18d847bb4c70f10f88d8c39b1db9577ab0e0730
3
  size 9437272
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:bd47a06904e2227963bc08edd2ac82e2d54130b6676ef5efddbaa44aa9e84fc8
3
  size 9437272
3_Dense/model.safetensors CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:9acabe76e2b4b50789feae81f6ad351e001c9f90766a4799c08436d8800e9d66
3
  size 9437272
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:f84cfba6a5e5a50f210d275d559f6fbb58766490c4beb9407419a5cd7e0ad0d3
3
  size 9437272
README.md CHANGED
@@ -104,7 +104,7 @@ model-index:
104
  type: val
105
  metrics:
106
  - type: cosine_accuracy
107
- value: 0.9479451775550842
108
  name: Cosine Accuracy
109
  - task:
110
  type: triplet
@@ -114,7 +114,7 @@ model-index:
114
  type: test
115
  metrics:
116
  - type: cosine_accuracy
117
- value: 0.9439124464988708
118
  name: Cosine Accuracy
119
  ---
120
 
@@ -185,7 +185,7 @@ print(query_embeddings.shape, document_embeddings.shape)
185
  # Get the similarity scores for the embeddings
186
  similarities = model.similarity(query_embeddings, document_embeddings)
187
  print(similarities)
188
- # tensor([[0.6594, 0.5887, 0.0372]])
189
  ```
190
 
191
  <!--
@@ -223,7 +223,7 @@ You can finetune this model on your own dataset.
223
 
224
  | Metric | val | test |
225
  |:--------------------|:-----------|:-----------|
226
- | **cosine_accuracy** | **0.9479** | **0.9439** |
227
 
228
  <!--
229
  ## Bias, Risks and Limitations
@@ -413,14 +413,14 @@ You can finetune this model on your own dataset.
413
  </details>
414
 
415
  ### Training Logs
416
- | Epoch | Step | Training Loss | Validation Loss | val_cosine_accuracy | test_cosine_accuracy |
417
- |:-------:|:------:|:-------------:|:---------------:|:-------------------:|:--------------------:|
418
- | -1 | -1 | - | - | 0.9192 | 0.9097 |
419
- | **1.0** | **82** | **0.3002** | **0.1993** | **0.9479** | **-** |
420
- | 2.0 | 164 | 0.1061 | 0.2260 | 0.9452 | - |
421
- | 3.0 | 246 | 0.0421 | 0.2254 | 0.9452 | - |
422
- | 4.0 | 328 | 0.0189 | 0.2207 | 0.9425 | - |
423
- | -1 | -1 | - | - | 0.9479 | 0.9439 |
424
 
425
  * The bold row denotes the saved checkpoint.
426
 
 
104
  type: val
105
  metrics:
106
  - type: cosine_accuracy
107
+ value: 0.9465753436088562
108
  name: Cosine Accuracy
109
  - task:
110
  type: triplet
 
114
  type: test
115
  metrics:
116
  - type: cosine_accuracy
117
+ value: 0.9357045292854309
118
  name: Cosine Accuracy
119
  ---
120
 
 
185
  # Get the similarity scores for the embeddings
186
  similarities = model.similarity(query_embeddings, document_embeddings)
187
  print(similarities)
188
+ # tensor([[0.7065, 0.5494, 0.1299]])
189
  ```
190
 
191
  <!--
 
223
 
224
  | Metric | val | test |
225
  |:--------------------|:-----------|:-----------|
226
+ | **cosine_accuracy** | **0.9466** | **0.9357** |
227
 
228
  <!--
229
  ## Bias, Risks and Limitations
 
413
  </details>
414
 
415
  ### Training Logs
416
+ | Epoch | Step | Training Loss | Validation Loss | val_cosine_accuracy | test_cosine_accuracy |
417
+ |:-------:|:-------:|:-------------:|:---------------:|:-------------------:|:--------------------:|
418
+ | -1 | -1 | - | - | 0.9192 | 0.9097 |
419
+ | 1.0 | 82 | 0.2979 | 0.2212 | 0.9438 | - |
420
+ | **2.0** | **164** | **0.1132** | **0.2597** | **0.9466** | **-** |
421
+ | 3.0 | 246 | 0.0371 | 0.2365 | 0.9411 | - |
422
+ | 4.0 | 328 | 0.0233 | 0.2106 | 0.9411 | - |
423
+ | -1 | -1 | - | - | 0.9466 | 0.9357 |
424
 
425
  * The bold row denotes the saved checkpoint.
426
 
model.safetensors CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:df7339ab34a264685e69962c11d619c8c5e8b74a7b035676534808e74f748ea3
3
  size 1211486072
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:b06c1283581cb3ba0c854f909f1470fdfbbea8f0eb9c7ee34d460fc307e1ecd2
3
  size 1211486072