Add new SentenceTransformer model

README.md

@@ -4,23 +4,23 @@ tags:
 - sentence-similarity
 - feature-extraction
 - generated_from_trainer
-- dataset_size:208
+- dataset_size:416
 - loss:BatchSemiHardTripletLoss
 base_model: BAAI/bge-base-en
 widget:
 - source_sentence: '
 
-    Name : Alegro
+    Name : CloudMetric Solutions
 
-    Category: Dining Services, Catering
+    Category: Data Analytics, Virtual Infrastructure Management
 
-    Department: Sales
+    Department: Engineering
 
-    Location: Barcelona, Spain
+    Location: Toronto, Canada
 
-    Amount: 432.75
+    Amount: 1644.75
 
-    Card: Client Relationship Dinner
+    Card: Real-Time Resource Monitoring
 
     Trip Name: unknown
 
@@ -28,23 +28,6 @@ widget:
   sentences:
   - '
 
-    Name : Pardalis Digital
-
-    Category: Data Analytics Platform, Professional Networking Service
-
-    Department: Sales
-
-    Location: Dublin, Ireland
-
-    Amount: 1456.75
-
-    Card: Sales Intelligence & Networking Platform
-
-    Trip Name: unknown
-
-    '
-  - '
-
     Name : Nimbus Networks Inc.
 
     Category: Cloud Services, Application Hosting
@@ -62,71 +45,71 @@ widget:
     '
   - '
 
-    Name : Rising Tide Solutions
+    Name : Allianz
 
-    Category: IT Resource Management
+    Category: Insurance Services, Financial Services
 
-    Department: Engineering
+    Department: Finance
 
-    Location: Amsterdam, Netherlands
+    Location: New York, NY
 
-    Amount: 1423.57
+    Amount: 2547.39
 
-    Card: Cloud Transition Project
+    Card: Quarterly Coverage Evaluation
 
     Trip Name: unknown
 
     '
-- source_sentence: '
+  - '
 
-    Name : Freenet AG
+    Name : Connexis Group
 
-    Category: Telecommunication Services
+    Category: Venue Logistics Services, Corporate Membership Consultancy
 
-    Department: IT Operations
+    Department: Sales
 
-    Location: Zurich, Switzerland
+    Location: Berlin, Germany
 
-    Amount: 2794.37
+    Amount: 1478.55
 
-    Card: Infrastructure Support Services
+    Card: International Trade Show Engagement
 
     Trip Name: unknown
 
     '
-  sentences:
-  - '
+- source_sentence: '
 
-    Name : True Grid Consulting
+    Name : BuroPro Services
 
-    Category: Workspace Optimization, Productivity Tools
+    Category: Facilities Management, Maintenance Solutions
 
     Department: Office Administration
 
-    Location: Tokyo, Japan
+    Location: Berlin, Germany
 
-    Amount: 1532.75
+    Amount: 879.99
 
-    Card: Enhanced Collaborative Environment
+    Card: Monthly Equipment Oversight
 
     Trip Name: unknown
 
     '
+  sentences:
   - '
 
-    Name : SentBe
+    Name : SynthioSolutions Global
 
-    Category: Business Services,
+    Category: Technology Consulting, Research Services
 
-    Department: Finance
+    Department: Research & Development
 
-    Location: Korea
+    Location: Singapore
 
-    Amount: 734.99
+    Amount: 1342.67
 
-    Card: Cross-Border Business Solutions
+    Card: Advanced Data Integration Project
 
-    Trip Name: 2024Q2-Seoul
+    Trip Name: unknown
 
     '
   - '
@@ -145,20 +128,37 @@ widget:
 
     Trip Name: unknown
 
+    '
+  - '
+
+    Name : City Shuttle Services
+
+    Category: Transportation, Logistics
+
+    Department: Sales
+
+    Location: San Francisco, CA
+
+    Amount: 85.0
+
+    Card: Sales Team Travel Fund
+
+    Trip Name: Client Meeting in Bay Area
+
     '
 - source_sentence: '
 
-    Name : Technika Solutions
+    Name : SkillAdvance Academy
 
-    Category: Networking Equipment Services, System Security
+    Category: Online Learning Platform, Professional Development
 
-    Department: IT Operations
+    Department: Engineering
 
-    Location: Zurich, Switzerland
+    Location: Austin, TX
 
-    Amount: 1384.29
+    Amount: 1875.67
 
-    Card: Integrated Systems Update
+    Card: Continuous Improvement Initiative
 
     Trip Name: unknown
 
@@ -166,68 +166,68 @@ widget:
   sentences:
   - '
 
-    Name : Connexis Group
+    Name : ComplyTech Solutions
 
-    Category: Venue Logistics Services, Corporate Membership Consultancy
+    Category: Regulatory Software, Consultancy Services
 
-    Department: Sales
+    Department: Compliance
 
-    Location: Berlin, Germany
+    Location: Brussels, Belgium
 
-    Amount: 1478.55
+    Amount: 1095.45
 
-    Card: International Trade Show Engagement
+    Card: Regulatory Compliance Optimization Plan
 
     Trip Name: unknown
 
     '
   - '
 
-    Name : SkillAdvance Academy
+    Name : AlphaTech Solutions
 
-    Category: Online Learning Platform, Professional Development
+    Category: Computer & Electronics Retail
 
-    Department: Engineering
+    Department: Research & Development
 
-    Location: Austin, TX
+    Location: Toronto, Canada
 
-    Amount: 1875.67
+    Amount: 1599.99
 
-    Card: Continuous Improvement Initiative
+    Card: Innovative Hardware Acquisition
 
     Trip Name: unknown
 
     '
   - '
 
-    Name : Apex Global Solutions
+    Name : Craft Gate Systems
 
-    Category: Risk Management Services, Consulting
+    Category: Payment Processing Gateway, Data Analytics Software
 
-    Department: Legal
+    Department: Finance
 
-    Location: Sydney, Australia
+    Location: Austin, TX
 
-    Amount: 1750.45
+    Amount: 1132.58
 
-    Card: Annual Compliance Review
+    Card: Quarterly Revenue Analysis
 
     Trip Name: unknown
 
     '
 - source_sentence: '
 
-    Name : Global Wellness Network
+    Name : Rising Tide Solutions
 
-    Category: Corporate Wellness Programs, Employee Engagement
+    Category: IT Resource Management
 
-    Department: HR
+    Department: Engineering
 
-    Location: Berlin, Germany
+    Location: Amsterdam, Netherlands
 
-    Amount: 1285.75
+    Amount: 1423.57
 
-    Card: Wellness and Engagement Program
+    Card: Cloud Transition Project
 
     Trip Name: unknown
 
@@ -235,68 +235,68 @@ widget:
   sentences:
   - '
 
-    Name : Analytix Global Solutions
+    Name : GigaTrend
 
-    Category: Business Intelligence Services, Regulatory Compliance Tools
+    Category: Data Services, Cloud Software Solutions
 
-    Department: Finance
+    Department: Research & Development
 
     Location: London, UK
 
-    Amount: 1323.67
+    Amount: 1345.67
 
-    Card: Financial Compliance Enhancement
+    Card: Data-Driven Innovation Project
 
     Trip Name: unknown
 
     '
   - '
 
-    Name : InfiniTech Systems
+    Name : Apex Innovations Group
 
-    Category: Technical Hardware Management, Software Solutions
+    Category: Business Consulting, Training Services
 
-    Department: IT Operations
+    Department: Executive
 
-    Location: New York, USA
+    Location: Sydney, Australia
 
-    Amount: 1099.47
+    Amount: 1575.34
 
-    Card: Integrated Support Package
+    Card: Leadership Development Program
 
     Trip Name: unknown
 
     '
   - '
 
-    Name : Veritas Insights
+    Name : Aegis Risk Consultants
 
-    Category: Consulting, Recruitment Services
+    Category: Executive Risk Management, Enterprise Solutions
 
-    Department: HR
+    Department: Legal
 
-    Location: Amsterdam, Netherlands
+    Location: London, UK
 
-    Amount: 2890.75
+    Amount: 1743.56
 
-    Card: Talent Acquisition Initiative
+    Card: Leadership Liability Initiative
 
     Trip Name: unknown
 
     '
 - source_sentence: '
 
-    Name : Viacom Solutions
+    Name : Allegro Integrations
 
-    Category: Telecom Hardware, Network Architecture
+    Category: Payment Processing Solutions, Financial Technology Services
 
-    Department: Engineering
+    Department: Finance
 
-    Location: Tokyo, Japan
+    Location: Dublin, Ireland
 
-    Amount: 1450.67
+    Amount: 1298.75
 
-    Card: Global Network Optimization Project
+    Card: Bi-annual Financial Systems Audit
 
     Trip Name: unknown
 
@@ -304,51 +304,51 @@ widget:
   sentences:
   - '
 
-    Name : InfoCircle Global
+    Name : Banyan Tree Pte Ltd
 
-    Category: Business Intelligence Tools, Enterprise Solutions
+    Category: General Contractors - Residential and Commercial
 
-    Department: Finance
+    Department: Office Administration
 
-    Location: Singapore
+    Location: Houston, TX
 
-    Amount: 1897.34
+    Amount: 987.65
 
-    Card: Enterprise Intelligence Subscription
+    Card: Operational Infrastructure Management
 
     Trip Name: unknown
 
     '
   - '
 
-    Name : Kepler Dynamics
+    Name : InsightWave Research
 
-    Category: Strategic Consultancy, Tech Solutions
+    Category: Business Intelligence Consultations, Market Expansion Strategy Services
 
-    Department: Finance
+    Department: Marketing
 
-    Location: Zurich, Switzerland
+    Location: Tokyo, Japan
 
-    Amount: 2375.88
+    Amount: 2034.67
 
-    Card: Integration Strategy Review
+    Card: Global Market Insights Program
 
     Trip Name: unknown
 
     '
   - '
 
-    Name : GlobalCert Compliance Ltd.
+    Name : ComplyTech Solutions
 
-    Category: Legal Consulting, Regulatory Services
+    Category: Regulatory Software, Consultancy Services
 
     Department: Compliance
 
-    Location: Boston, MA
+    Location: Brussels, Belgium
 
-    Amount: 1342.67
+    Amount: 1095.45
 
-    Card: Annual Regulatory Certification Program
+    Card: Regulatory Compliance Optimization Plan
 
     Trip Name: unknown
 
@@ -368,7 +368,7 @@ model-index:
       type: bge-base-en-train
     metrics:
     - type: cosine_accuracy
-      value: 0.8557692170143127
+      value: 0.4759615361690521
       name: Cosine Accuracy
   - task:
       type: triplet
@@ -378,7 +378,7 @@ model-index:
       type: bge-base-en-eval
     metrics:
     - type: cosine_accuracy
-      value: 0.4848484992980957
+      value: 0.0
       name: Cosine Accuracy
 ---
 
@@ -432,9 +432,9 @@ from sentence_transformers import SentenceTransformer
 model = SentenceTransformer("ppuva1/finetuned-bge-base-en")
 # Run inference
 sentences = [
-    '\nName : Viacom Solutions\nCategory: Telecom Hardware, Network Architecture\nDepartment: Engineering\nLocation: Tokyo, Japan\nAmount: 1450.67\nCard: Global Network Optimization Project\nTrip Name: unknown\n',
-    '\nName : GlobalCert Compliance Ltd.\nCategory: Legal Consulting, Regulatory Services\nDepartment: Compliance\nLocation: Boston, MA\nAmount: 1342.67\nCard: Annual Regulatory Certification Program\nTrip Name: unknown\n',
-    '\nName : Kepler Dynamics\nCategory: Strategic Consultancy, Tech Solutions\nDepartment: Finance\nLocation: Zurich, Switzerland\nAmount: 2375.88\nCard: Integration Strategy Review\nTrip Name: unknown\n',
+    '\nName : Allegro Integrations\nCategory: Payment Processing Solutions, Financial Technology Services\nDepartment: Finance\nLocation: Dublin, Ireland\nAmount: 1298.75\nCard: Bi-annual Financial Systems Audit\nTrip Name: unknown\n',
+    '\nName : Banyan Tree Pte Ltd\nCategory: General Contractors - Residential and Commercial\nDepartment: Office Administration\nLocation: Houston, TX\nAmount: 987.65\nCard: Operational Infrastructure Management\nTrip Name: unknown\n',
+    '\nName : ComplyTech Solutions\nCategory: Regulatory Software, Consultancy Services\nDepartment: Compliance\nLocation: Brussels, Belgium\nAmount: 1095.45\nCard: Regulatory Compliance Optimization Plan\nTrip Name: unknown\n',
 ]
 embeddings = model.encode(sentences)
 print(embeddings.shape)
@@ -481,7 +481,7 @@ You can finetune this model on your own dataset.
 
 | Metric              | bge-base-en-train | bge-base-en-eval |
 |:--------------------|:------------------|:-----------------|
-| **cosine_accuracy** | **0.8558**        | **0.4848**       |
+| **cosine_accuracy** | **0.476**         | **0.0**          |
 
 <!--
 ## Bias, Risks and Limitations
@@ -501,38 +501,38 @@ You can finetune this model on your own dataset.
 
 #### Unnamed Dataset
 
-* Size: 208 training samples
+* Size: 416 training samples
 * Columns: <code>sentence</code> and <code>label</code>
-* Approximate statistics based on the first 208 samples:
+* Approximate statistics based on the first 416 samples:
   |         | sentence                                                                           | label                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            |
   |:--------|:-----------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
   | type    | string                                                                             | int                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                              |
-  | details | <ul><li>min: 33 tokens</li><li>mean: 39.89 tokens</li><li>max: 49 tokens</li></ul> | <ul><li>0: ~4.81%</li><li>1: ~2.40%</li><li>2: ~4.81%</li><li>3: ~3.37%</li><li>4: ~2.88%</li><li>5: ~4.81%</li><li>6: ~4.33%</li><li>7: ~2.88%</li><li>8: ~2.88%</li><li>9: ~6.73%</li><li>10: ~5.77%</li><li>11: ~2.88%</li><li>12: ~2.40%</li><li>13: ~5.77%</li><li>14: ~4.81%</li><li>15: ~4.33%</li><li>16: ~5.29%</li><li>17: ~2.40%</li><li>18: ~3.85%</li><li>19: ~2.40%</li><li>20: ~3.37%</li><li>21: ~3.85%</li><li>22: ~1.92%</li><li>23: ~1.44%</li><li>24: ~4.33%</li><li>25: ~3.85%</li><li>26: ~1.44%</li></ul> |
+  | details | <ul><li>min: 32 tokens</li><li>mean: 39.99 tokens</li><li>max: 49 tokens</li></ul> | <ul><li>0: ~3.12%</li><li>1: ~3.12%</li><li>2: ~3.85%</li><li>3: ~4.81%</li><li>4: ~2.16%</li><li>5: ~4.33%</li><li>6: ~4.57%</li><li>7: ~3.85%</li><li>8: ~5.05%</li><li>9: ~4.09%</li><li>10: ~2.88%</li><li>11: ~4.33%</li><li>12: ~2.16%</li><li>13: ~4.09%</li><li>14: ~3.61%</li><li>15: ~5.77%</li><li>16: ~3.12%</li><li>17: ~6.01%</li><li>18: ~5.05%</li><li>19: ~2.64%</li><li>20: ~3.37%</li><li>21: ~2.88%</li><li>22: ~4.57%</li><li>23: ~2.64%</li><li>24: ~2.64%</li><li>25: ~3.85%</li><li>26: ~1.44%</li></ul> |
 * Samples:
-  | sentence                                                                                                                                                                                                                                              | label          |
-  |:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------|
-  | <code><br>Name : Wong & Lim<br>Category: Technical Equipment Services, Facility Services<br>Department: Office Administration<br>Location: Berlin, Germany<br>Amount: 458.29<br>Card: Monthly Equipment Care Program<br>Trip Name: unknown<br></code> | <code>0</code> |
-  | <code><br>Name : InterGlobal Tech<br>Category: Business Software Solutions, Data Processing Services<br>Department: Marketing<br>Location: New York, NY<br>Amount: 1249.95<br>Card: Marketing Automation Tools<br>Trip Name: unknown<br></code>       | <code>1</code> |
-  | <code><br>Name : Garrison Transport Group<br>Category: Transportation Services, Logistics Management<br>Department: Sales<br>Location: New York, NY<br>Amount: 317.45<br>Card: Client Acquisition Trip<br>Trip Name: Q3-Sales-Pitch<br></code>        | <code>2</code> |
+  | sentence                                                                                                                                                                                                                                               | label          |
+  |:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------|
+  | <code><br>Name : InnovaThink Global<br>Category: Management Consultancy, Technical Training Services<br>Department: HR<br>Location: Zurich, Switzerland<br>Amount: 1675.32<br>Card: Innovation and Efficiency Program<br>Trip Name: unknown<br></code> | <code>0</code> |
+  | <code><br>Name : Global Wellness Network<br>Category: Corporate Wellness Programs, Employee Engagement<br>Department: HR<br>Location: Berlin, Germany<br>Amount: 1285.75<br>Card: Wellness and Engagement Program<br>Trip Name: unknown<br></code>     | <code>1</code> |
+  | <code><br>Name : Wong & Lim<br>Category: Technical Equipment Services, Facility Services<br>Department: Office Administration<br>Location: Berlin, Germany<br>Amount: 458.29<br>Card: Monthly Equipment Care Program<br>Trip Name: unknown<br></code>  | <code>2</code> |
 * Loss: [<code>BatchSemiHardTripletLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#batchsemihardtripletloss)
 
 ### Evaluation Dataset
 
 #### Unnamed Dataset
 
-* Size: 52 evaluation samples
+* Size: 104 evaluation samples
 * Columns: <code>sentence</code> and <code>label</code>
-* Approximate statistics based on the first 52 samples:
-  |         | sentence                                                                           | label                                                                                                                                                                                                                                                                                                                                                                                                                                                                                       |
-  |:--------|:-----------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
-  | type    | string                                                                             | int                                                                                                                                                                                                                                                                                                                                                                                                                                                                                         |
-  | details | <ul><li>min: 32 tokens</li><li>mean: 39.19 tokens</li><li>max: 46 tokens</li></ul> | <ul><li>0: ~3.85%</li><li>2: ~1.92%</li><li>3: ~3.85%</li><li>4: ~1.92%</li><li>5: ~7.69%</li><li>6: ~3.85%</li><li>7: ~3.85%</li><li>8: ~3.85%</li><li>9: ~1.92%</li><li>10: ~3.85%</li><li>11: ~3.85%</li><li>12: ~1.92%</li><li>13: ~1.92%</li><li>14: ~1.92%</li><li>15: ~3.85%</li><li>16: ~1.92%</li><li>17: ~9.62%</li><li>18: ~5.77%</li><li>19: ~5.77%</li><li>20: ~5.77%</li><li>22: ~5.77%</li><li>23: ~1.92%</li><li>24: ~5.77%</li><li>25: ~1.92%</li><li>26: ~5.77%</li></ul> |
+* Approximate statistics based on the first 104 samples:
+  |         | sentence                                                                           | label                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                          |
+  |:--------|:-----------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+  | type    | string                                                                             | int                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            |
+  | details | <ul><li>min: 32 tokens</li><li>mean: 39.19 tokens</li><li>max: 46 tokens</li></ul> | <ul><li>0: ~1.92%</li><li>1: ~0.96%</li><li>2: ~4.81%</li><li>3: ~1.92%</li><li>5: ~5.77%</li><li>6: ~7.69%</li><li>7: ~4.81%</li><li>8: ~3.85%</li><li>9: ~5.77%</li><li>10: ~2.88%</li><li>11: ~4.81%</li><li>12: ~2.88%</li><li>13: ~1.92%</li><li>14: ~2.88%</li><li>15: ~0.96%</li><li>16: ~1.92%</li><li>17: ~3.85%</li><li>18: ~4.81%</li><li>19: ~3.85%</li><li>20: ~1.92%</li><li>21: ~0.96%</li><li>22: ~5.77%</li><li>23: ~7.69%</li><li>24: ~7.69%</li><li>25: ~4.81%</li><li>26: ~2.88%</li></ul> |
 * Samples:
-  | sentence                                                                                                                                                                                                                                                         | label           |
-  |:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:----------------|
-  | <code><br>Name : Freenet AG<br>Category: Telecommunication Services<br>Department: IT Operations<br>Location: Zurich, Switzerland<br>Amount: 2794.37<br>Card: Infrastructure Support Services<br>Trip Name: unknown<br></code>                                   | <code>20</code> |
-  | <code><br>Name : Analytix Global Solutions<br>Category: Business Intelligence Services, Regulatory Compliance Tools<br>Department: Finance<br>Location: London, UK<br>Amount: 1323.67<br>Card: Financial Compliance Enhancement<br>Trip Name: unknown<br></code> | <code>15</code> |
-  | <code><br>Name : Allianz<br>Category: Insurance Services, Financial Services<br>Department: Finance<br>Location: New York, NY<br>Amount: 2547.39<br>Card: Quarterly Coverage Evaluation<br>Trip Name: unknown<br></code>                                         | <code>6</code>  |
+  | sentence                                                                                                                                                                                                                                         | label           |
+  |:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:----------------|
+  | <code><br>Name : Aegis Risk Consultants<br>Category: Executive Risk Management, Enterprise Solutions<br>Department: Legal<br>Location: London, UK<br>Amount: 1743.56<br>Card: Leadership Liability Initiative<br>Trip Name: unknown<br></code>   | <code>11</code> |
+  | <code><br>Name : Vinobia Lounge<br>Category: Culinary Experiences, Networking Venues<br>Department: Marketing<br>Location: Dallas, TX<br>Amount: 651.58<br>Card: Innovative Marketing Strategies<br>Trip Name: Annual Marketing Event<br></code> | <code>8</code>  |
+  | <code><br>Name : Freenet AG<br>Category: Telecommunication Services<br>Department: IT Operations<br>Location: Zurich, Switzerland<br>Amount: 2794.37<br>Card: Infrastructure Support Services<br>Trip Name: unknown<br></code>                   | <code>25</code> |
 * Loss: [<code>BatchSemiHardTripletLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#batchsemihardtripletloss)
 
 ### Training Hyperparameters
@@ -668,9 +668,11 @@ You can finetune this model on your own dataset.
 </details>
 
 ### Training Logs
-| Epoch | Step | bge-base-en-train_cosine_accuracy | bge-base-en-eval_cosine_accuracy |
-|:-----:|:----:|:---------------------------------:|:--------------------------------:|
-| -1    | -1   | 0.8558                            | 0.4848                           |
+| Epoch  | Step | Training Loss | Validation Loss | bge-base-en-train_cosine_accuracy | bge-base-en-eval_cosine_accuracy |
+|:------:|:----:|:-------------:|:---------------:|:---------------------------------:|:--------------------------------:|
+| -1     | -1   | -             | -               | 0.8510                            | -                                |
+| 3.8462 | 100  | 4.9979        | 5.0174          | 0.4760                            | -                                |
+| -1     | -1   | -             | -               | -                                 | 0.0                              |
 
 
 ### Framework Versions

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:a47186f8526175cd887439afbc9998126d26374f7042a8ce8cfe1a1882911933
+oid sha256:898bb5668ad27dc6ca8570e6e3589dec57af7f79f4e35dbebed0c57142369f52
 size 437951328