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tomaarsen
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ModernBERT-base-msmarco-margin-mse

Sentence Similarity
sentence-transformers
Safetensors
English
modernbert
feature-extraction
dense
Generated from Trainer
dataset_size:10000
loss:MarginMSELoss
Eval Results
text-embeddings-inference
Model card Files
xet
Community
tomaarsen HF Staff commited on
Commit
13d7f9a
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verified ·
1 Parent(s): 0dedae4

Add new SentenceTransformer model

Browse files
Files changed (10) hide show
  1. 1_Pooling/config.json +10 -0
  2. README.md +939 -0
  3. config.json +45 -0
  4. config_sentence_transformers.json +14 -0
  5. model.safetensors +3 -0
  6. modules.json +14 -0
  7. sentence_bert_config.json +4 -0
  8. special_tokens_map.json +37 -0
  9. tokenizer.json +0 -0
  10. tokenizer_config.json +945 -0
1_Pooling/config.json ADDED
@@ -0,0 +1,10 @@
 
 
 
 
 
 
 
 
 
 
 
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+ {
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+ "word_embedding_dimension": 768,
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+ "pooling_mode_cls_token": false,
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+ "pooling_mode_mean_tokens": true,
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+ "pooling_mode_max_tokens": false,
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+ "pooling_mode_mean_sqrt_len_tokens": false,
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+ "pooling_mode_weightedmean_tokens": false,
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+ "pooling_mode_lasttoken": false,
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+ "include_prompt": true
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+ }
README.md ADDED
@@ -0,0 +1,939 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
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+ language:
3
+ - en
4
+ license: apache-2.0
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+ tags:
6
+ - sentence-transformers
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+ - sentence-similarity
8
+ - feature-extraction
9
+ - dense
10
+ - generated_from_trainer
11
+ - dataset_size:10000
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+ - loss:MarginMSELoss
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+ base_model: answerdotai/ModernBERT-base
14
+ widget:
15
+ - source_sentence: driving distance miami to fort lauderdale
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+ sentences:
17
+ - "This Distance calculator provides both the by air, and by road distance between\
18
+ \ cities in both miles and kms, along with a map and driving directions â\x80\x93\
19
+ \ please scroll down to see it, and a little further for the city to city driving\
20
+ \ directions. This is the by air, as the crow flies distance between the two cities."
21
+ - Driving distance from Fort Lauderdale, FL to Miami, FL. The total driving distance
22
+ from Fort Lauderdale, FL to Miami, FL is 27 miles or 43 kilometers. Your trip
23
+ begins in Fort Lauderdale, Florida. It ends in Miami, Florida. If you are planning
24
+ a road trip, you might also want to calculate the total driving time from Fort
25
+ Lauderdale, FL to Miami, FL so you can see when you'll arrive at your destination.
26
+ - The total driving distance from Fort Lauderdale to Miami Beach, FL is 32 miles.
27
+ It can take 1 hour to 1.5 hours depending on how bad the traffic is or in rush
28
+ hour. Or 11.30 at night it may be 1 hour, but will be less 1 hour.
29
+ - Distance Between Cordova Tennessee United States and Memphis International Airport
30
+ (MEM) Tennessee United States, flight and driving distances and airport information.
31
+ Distance calculator.
32
+ - Distance Map Info. Optimal route map between New Smyrna Beach, FL and Melbourne,
33
+ FL. This route will be about 75 Miles. The driving route information(distance,
34
+ estimated time, directions), flight route, traffic information and print the map
35
+ features are placed on the top right corner of the map.
36
+ - Driving distance from Fort Lauderdale, FL to Miami, FL. The total driving distance
37
+ from Fort Lauderdale, FL to Miami, FL is 27 miles or 43 kilometers.Your trip begins
38
+ in Fort Lauderdale, Florida. It ends in Miami, Florida.ou can also calculate the
39
+ cost of driving from Fort Lauderdale, FL to Miami, FL based on current local fuel
40
+ prices and an estimate of your car's best gas mileage.
41
+ - There are 25.15 miles from Miami to Fort Lauderdale in north direction and 29.11
42
+ miles (46.85 kilometers) by car, following the I-95 route. Miami and Fort Lauderdale
43
+ are 31 minutes far apart, if you drive non-stop. This is the fastest route from
44
+ Miami, FL to Fort Lauderdale, FL. The halfway point is Aventura, FL.
45
+ - Need to know towns or cities within a specific radius of other places try this
46
+ Towns within a Radius of Treasure Island tool. The distance between Treasure Island
47
+ and St Augustine in a straight line is 172 miles or 276.75 Kilometers.
48
+ - Distance calculator helps you to find the distance between cities and calculate
49
+ the flying and driving distance in both kilometers and miles. Distance Calculator
50
+ Distance calculator is a tool for calculating distance between cities or places
51
+ on map.
52
+ - source_sentence: datsun 1200 starter motor diagram
53
+ sentences:
54
+ - Here you will find scans of the original wiring diagram for the 1971, 1972, and
55
+ 1973 Datsun 1200. 1971 Datsun 1200 Wiring Diagram. 1972 Datsun 1200 Wiring Diagram.
56
+ 1973 Datsun 1200 Wiring Diagram.
57
+ - Free Universal VIN decoder to check vehicle data and history. This is a universal
58
+ VIN decoder. Every car has a unique identifier code called a VIN. This number
59
+ contains vital information about the car, such as its manufacturer, year of production,
60
+ the plant it was produced in, type of engine, model and more.
61
+ - 'This review is from: Powerhorse Portable Generator with Electric Start - 9000
62
+ Surge Watts, 7250 Rated Watts (Misc.) Update Jan. 4, 2012... I found out the motor
63
+ for this generator is manufactured by a company called Ducar. I found this out
64
+ by speaking with a customer Service rep at Northern Tool.'
65
+ - Starter Motor. The engine starter is an electrical motor that is bolted to the
66
+ engine crankcase. The starter turns the engine flywheel teeth with the teeth on
67
+ the starter motor plunger which starts the riding lawnmower engine. Once the battery,
68
+ electrical connectors, wiring and starter solenoid have been tested and are functioning
69
+ properly, the problem likely lies with the engine starter motor.
70
+ - "Datsun is a Japanese car manufacturer that produced a great number of cars, starting\
71
+ \ with the first Datsun model in 1931 and on until the brand was discontinued\
72
+ \ in 1983. The Datsun brand became particularly famous because of one of their\
73
+ \ sports cars, the Fairlady model. Headquartered in Japan, Datsun was absorbed\
74
+ \ by another Japanese carmaker, Nissan, and the Datsun models were rebadged as\
75
+ \ Nissanâ\x80\x99s from 1983 onwards."
76
+ - Datsun is an automobile brand owned by Nissan. Datsun's original production run
77
+ began in 1931. From 1958 to 1986, only vehicles exported by Nissan were identified
78
+ as Datsun. By 1986 Nissan had phased out the Datsun name, but re-launched it in
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+ 2013 as the brand for low-cost vehicles manufactured for emerging markets.
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+ - The dial reading should be 12 volts or more. Work the starter switch, and the
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+ reading should fall, but not below 10.5 volts. If the reading does not fall, there
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+ is a fault in the ignition-switch circuit or in the solenoid.
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+ - echo dot. Controls lights, fans, switches, thermostats, garage doors, sprinklers,
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+ and more with compatible connected devices. Connects to speakers or headphones
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+ through Bluetooth or 3.5 mm stereo cable to play music.
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+ - Acura TSX vs Honda Accord. Compare price, expert/user reviews, mpg, engines, safety,
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+ cargo capacity and other specs at a glance.
88
+ - source_sentence: what primary plant tissue is involved in transport of minerals
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+ sentences:
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+ - The ground tissue comprises the bulk of the primary plant body. Parenchyma, collenchyma,
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+ and sclerenchyma cells are common in the ground tissue. Vascular tissue transports
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+ food, water, hormones and minerals within the plant. Vascular tissue includes
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+ xylem, phloem, parenchyma, and cambium cells. Two views of the structure of the
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+ root and root meristem.
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+ - · just now. Report Abuse. 1.Water transport-in xylem from the roots up the plant.
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+ A passive process = transpiration 2.Sugar transport-sucrose is the main sugar
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+ transported in phloem from leaves up and down the plant. An active process-needs
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+ ATP.Process called translocation Look up transpiration and translocation Discuss
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+ the cells used in each, the direction and the mechanism. Peter S · 6 years ago.ugar
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+ i.e. glucose is produced in leaves (green parts of the plant) and it is transported
101
+ to other parts of the plants such as reproductive organs, fruits and seeds, roots
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+ and stem (growing tips etc) through phloem tissue. Xylems are made up of dead
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+ cells while phloem tissue is made up of living cells.
104
+ - 1 of 6. Plants have tissues to transport water, nutrients and minerals. Xylem
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+ transports water and mineral salts from the roots up to other parts of the plant,
106
+ while phloem transports sucrose and amino acids between the leaves and other parts
107
+ of the plant. Xylem and phloem in the centre of the plant root.
108
+ - Xylem is one of two types of vascular tissues found in plant (the other being
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+ Phloem). The word Xylem is derived from the Greek for wood. The xylem is responsible
110
+ for the transport (translocation) of water and soluble mineral nutrients from
111
+ the roots throughout the plant, this facilitates the replacement of water lost
112
+ during transpiration and photosynthesis.
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+ - Various vascular tissues in the root allow for transportation of water and nutrients
114
+ to the rest of theplant.Plant cells have a cell wall to provide support, a large
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+ vacuole for storage of minerals, food, andchloroplasts where photosynthesis takes
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+ place.
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+ - The function of the phloem tissue is to transport food nutrients such as glucose
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+ and amino acids from the leaves and to all other cells of the plant, this is called
119
+ translocation.
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+ - Plants have tissues to transport water, nutrients and minerals. Xylem transports
121
+ water and mineral salts from the roots up to other parts of the plant, while phloem
122
+ transports sucrose and amino acids between the leaves and other parts of the plant.
123
+ Xylem and phloem in the centre of the plant root
124
+ - Seed plants contain 2 types of vascular tissue (xylem & phloem) to help transport
125
+ water, minerals, & food throughout the root & shoot systems.Plant cells have several
126
+ specialized structures including a central vacuole for storage, plastids for storage
127
+ of pigments, and a thick cell wall of cellulose.lants have 3 tissue systems ---
128
+ ground, dermal, and vascular tissues. Plant tissues make up the main organs of
129
+ a plant --- root, stem, leaf, & flower.
130
+ - 'This article is about vascular tissue in plants. For transport in animals, see
131
+ Circulatory system. Vascular tissue is a complex conducting tissue, formed of
132
+ more than one cell type, found in vascular plants. The primary components of vascular
133
+ tissue are the xylem and phloem. These two tissues transport fluid and nutrients
134
+ internally. There are also two meristems associated with vascular tissue: the
135
+ vascular cambium and the cork cambium. All the vascular tissues within a particular
136
+ plant together constitute the vascular tissue system of that plant. The cells
137
+ in vascular tissue are typically long and slender. Since the xylem and phloem
138
+ function in the conduction of water, minerals, and nutrients throughout the plant,
139
+ it is not surprising that their form should be similar to pipes.'
140
+ - source_sentence: Julia name meaning
141
+ sentences:
142
+ - 'In American the meaning of the name Julie is: Young. French Meaning: The name
143
+ Julie is a French baby name. In French the meaning of the name Julie is: Downy.
144
+ French form of Julia. Also can be a feminine form of Julian: Youthful.'
145
+ - Jelisa Name Meaning. You are honest, benevolent, brilliant and often inventive,
146
+ full of high inspirations. You are courageous, honest, determined, original and
147
+ creative. You are a leader, especially for a cause.
148
+ - The name Julius is of Latin and Greek origin. The meaning of Julius is downy-bearded,
149
+ soft haired, implying youthful. Julius is generally used as a boy's name. It consists
150
+ of 6 letters and 3 syllables and is pronounced Ju-li-us.
151
+ - 'The name Julia is a Greek baby name. In Greek the meaning of the name Julia is:
152
+ Downy. Hairy. Derived from the clan name of Roman dictator Gaius Julius Caesar.
153
+ Latin Meaning: The name Julia is a Latin baby name.'
154
+ - 'The name Julia is an American baby name. In American the meaning of the name
155
+ Julia is: Youthful. Swedish Meaning: The name Julia is a Swedish baby name. In
156
+ Swedish the meaning of the name Julia is: Youth.Greek Meaning: The name Julia
157
+ is a Greek baby name. In Greek the meaning of the name Julia is: Downy. Hairy.
158
+ Derived from the clan name of Roman dictator Gaius Julius Caesar.Latin Meaning:
159
+ The name Julia is a Latin baby name.In Latin the meaning of the name Julia is:
160
+ Young. The feminine form of Julius. A character in Shakespeare''s play ''Two Gentlemen
161
+ of Verona''. Shakespearean Meaning: The name Julia is a Shakespearean baby name.he
162
+ name Julia is a Latin baby name. In Latin the meaning of the name Julia is: Young.
163
+ The feminine form of Julius. A character in Shakespeare''s play ''Two Gentlemen
164
+ of Verona''.'
165
+ - The meaning of Julius is Downy-bearded youth. Its origin is Variant of the Roman
166
+ name Iulius. Julius is a form of Iulius and is generally pronounced like JOO lee
167
+ es. This name is mostly being used as a boys name. Last year it ranked 312th in
168
+ the U.S. Social Security Administration list of most popular baby boy names. Show
169
+ popularity chart.
170
+ - "What does Julianna mean? Julianna [ju-lian-na] as a name for girls is a Latin\
171
+ \ name, and Julianna means youthful; Jove's child. Julianna is a version of Juliana\
172
+ \ (Latin): feminine of Julius. Associated with: youthful. Juliannaâ\x96² has 1\
173
+ \ variant: Julieanna."
174
+ - 'The name Jelena is a Russian baby name. In Russian the meaning of the name Jelena
175
+ is: Shining light. SoulUrge Number: 11. Expression Number: 2. People with this
176
+ name have a deep inner desire to inspire others in a higher cause, and to share
177
+ their own strongly held views on spiritual matters.'
178
+ - 'The name Julia is a Latin baby name. In Latin the meaning of the name Julia is:
179
+ Young. The feminine form of Julius. A character in Shakespeare''s play ''Two Gentlemen
180
+ of Verona''.he name Julia is a Latin baby name. In Latin the meaning of the name
181
+ Julia is: Young. The feminine form of Julius. A character in Shakespeare''s play
182
+ ''Two Gentlemen of Verona''.'
183
+ - source_sentence: what does ly mean in a blood test
184
+ sentences:
185
+ - According to the Hormone-Refractory Prostate Cancer Association, LY on a blood
186
+ test stands for lymphocytes. The number in the results represents the percentage
187
+ of lymphocytes in the white blood count. Lymphocytes should count for 15 to 46.8
188
+ percent of white blood cells. Continue Reading.
189
+ - FROM OUR EXPERTS. Trace lysed blood refers to a finding that is usually reported
190
+ from a urinary dip stick analysis. It implies that there is a small quantity of
191
+ red cells in the urine that have broken open. The developer on the dip stick reacts
192
+ with the hemoglobin that is released when the red cells are lysed.
193
+ - Does anybody know what LM and TFT in blood testing is please? Does anybody know
194
+ what LM and TFT in blood testing is please? TFT is Thyroid Function Tests , usually
195
+ done as a series of tests for TSH (Thyroid-stimulating hormone) and for the T3
196
+ (Triiodothyronine) and T4 ( Thyroxine), which are the hormones produced by the
197
+ thyroid gland.
198
+ - Uses. A blood lipid test measures the levels of HDL (high-density lipoprotein)
199
+ cholesterol and LDL (low-density lipoprotein) cholesterol in the blood as well
200
+ as triglycerides. These results can help doctors determine patients' health status.
201
+ - It is found in almost all body tissues and can be measured by a simple blood test.
202
+ Normal LDH levels are generally low and range between 140 IU/liter to 333 IU/
203
+ liter. Low LDH levels are usually no cause for concern. However, elevated LDH
204
+ levels may indicate cell damage.
205
+ - Usually, an LFT blood test measures the amount of bilirubin in the blood. Bilirubin
206
+ is released when red blood cells breakdown, and it is the liver that detoxifies
207
+ the bilirubin and helps to eliminate it from the body. Bilirubin is a part of
208
+ the digestive juice, bile, which the liver produces.
209
+ - 'Medical Definition of LYE. 1. : a strong alkaline liquor rich in potassium carbonate
210
+ leached from wood ashes and used especially in making soap and washing; broadly:
211
+ a strong alkaline solution (as of sodium hydroxide or potassium hydroxide). 2.:
212
+ a solid caustic (as sodium hydroxide).edical Definition of LYE. 1. : a strong
213
+ alkaline liquor rich in potassium carbonate leached from wood ashes and used especially
214
+ in making soap and washing; broadly: a strong alkaline solution (as of sodium
215
+ hydroxide or potassium hydroxide). 2. : a solid caustic (as sodium hydroxide).'
216
+ - FROM OUR COMMUNITY. Hi Terry, The LY (Lymphocytes) in your blood test is; the
217
+ type of white blood cell found in the blood and lymph systems; part of the immune
218
+ system. BUN/CREAT - Bun and Creatinine are tests done to monitor kidney function.
219
+ I'm sorry, but I've never heard of the other 2.
220
+ - The Lactic Acid Plasma Test, or Lactate Test, measures the amount of lactate in
221
+ the blood to determine if a patient has lactic acidosis.he test may be ordered
222
+ at prescribed intervals to monitor lactate levels. The Lactate Test is also known
223
+ as Lactic Acid, Plasma Lactate, and L-Lactate. Patients will be instructed to
224
+ fast prior to this blood test and be in a resting state.
225
+ datasets:
226
+ - tomaarsen/msmarco-Qwen3-Reranker-0.6B
227
+ pipeline_tag: sentence-similarity
228
+ library_name: sentence-transformers
229
+ metrics:
230
+ - cosine_accuracy@1
231
+ - cosine_accuracy@3
232
+ - cosine_accuracy@5
233
+ - cosine_accuracy@10
234
+ - cosine_precision@1
235
+ - cosine_precision@3
236
+ - cosine_precision@5
237
+ - cosine_precision@10
238
+ - cosine_recall@1
239
+ - cosine_recall@3
240
+ - cosine_recall@5
241
+ - cosine_recall@10
242
+ - cosine_ndcg@10
243
+ - cosine_mrr@10
244
+ - cosine_map@100
245
+ model-index:
246
+ - name: ModernBERT-base finetuned on MSMARCO via distillation
247
+ results:
248
+ - task:
249
+ type: information-retrieval
250
+ name: Information Retrieval
251
+ dataset:
252
+ name: msmarco eval 1kq 1kd
253
+ type: msmarco-eval-1kq-1kd
254
+ metrics:
255
+ - type: cosine_accuracy@1
256
+ value: 0.781
257
+ name: Cosine Accuracy@1
258
+ - type: cosine_accuracy@3
259
+ value: 0.887
260
+ name: Cosine Accuracy@3
261
+ - type: cosine_accuracy@5
262
+ value: 0.917
263
+ name: Cosine Accuracy@5
264
+ - type: cosine_accuracy@10
265
+ value: 0.943
266
+ name: Cosine Accuracy@10
267
+ - type: cosine_precision@1
268
+ value: 0.781
269
+ name: Cosine Precision@1
270
+ - type: cosine_precision@3
271
+ value: 0.29566666666666663
272
+ name: Cosine Precision@3
273
+ - type: cosine_precision@5
274
+ value: 0.18340000000000004
275
+ name: Cosine Precision@5
276
+ - type: cosine_precision@10
277
+ value: 0.09430000000000001
278
+ name: Cosine Precision@10
279
+ - type: cosine_recall@1
280
+ value: 0.781
281
+ name: Cosine Recall@1
282
+ - type: cosine_recall@3
283
+ value: 0.887
284
+ name: Cosine Recall@3
285
+ - type: cosine_recall@5
286
+ value: 0.917
287
+ name: Cosine Recall@5
288
+ - type: cosine_recall@10
289
+ value: 0.943
290
+ name: Cosine Recall@10
291
+ - type: cosine_ndcg@10
292
+ value: 0.8655823808772907
293
+ name: Cosine Ndcg@10
294
+ - type: cosine_mrr@10
295
+ value: 0.8404488095238101
296
+ name: Cosine Mrr@10
297
+ - type: cosine_map@100
298
+ value: 0.8423984809497023
299
+ name: Cosine Map@100
300
+ - task:
301
+ type: information-retrieval
302
+ name: Information Retrieval
303
+ dataset:
304
+ name: NanoMSMARCO
305
+ type: NanoMSMARCO
306
+ metrics:
307
+ - type: cosine_accuracy@1
308
+ value: 0.1
309
+ name: Cosine Accuracy@1
310
+ - type: cosine_accuracy@3
311
+ value: 0.28
312
+ name: Cosine Accuracy@3
313
+ - type: cosine_accuracy@5
314
+ value: 0.36
315
+ name: Cosine Accuracy@5
316
+ - type: cosine_accuracy@10
317
+ value: 0.56
318
+ name: Cosine Accuracy@10
319
+ - type: cosine_precision@1
320
+ value: 0.1
321
+ name: Cosine Precision@1
322
+ - type: cosine_precision@3
323
+ value: 0.09333333333333332
324
+ name: Cosine Precision@3
325
+ - type: cosine_precision@5
326
+ value: 0.07200000000000001
327
+ name: Cosine Precision@5
328
+ - type: cosine_precision@10
329
+ value: 0.05600000000000001
330
+ name: Cosine Precision@10
331
+ - type: cosine_recall@1
332
+ value: 0.1
333
+ name: Cosine Recall@1
334
+ - type: cosine_recall@3
335
+ value: 0.28
336
+ name: Cosine Recall@3
337
+ - type: cosine_recall@5
338
+ value: 0.36
339
+ name: Cosine Recall@5
340
+ - type: cosine_recall@10
341
+ value: 0.56
342
+ name: Cosine Recall@10
343
+ - type: cosine_ndcg@10
344
+ value: 0.3024724428473199
345
+ name: Cosine Ndcg@10
346
+ - type: cosine_mrr@10
347
+ value: 0.22331746031746025
348
+ name: Cosine Mrr@10
349
+ - type: cosine_map@100
350
+ value: 0.23964016128375398
351
+ name: Cosine Map@100
352
+ - task:
353
+ type: information-retrieval
354
+ name: Information Retrieval
355
+ dataset:
356
+ name: NanoNFCorpus
357
+ type: NanoNFCorpus
358
+ metrics:
359
+ - type: cosine_accuracy@1
360
+ value: 0.12
361
+ name: Cosine Accuracy@1
362
+ - type: cosine_accuracy@3
363
+ value: 0.16
364
+ name: Cosine Accuracy@3
365
+ - type: cosine_accuracy@5
366
+ value: 0.24
367
+ name: Cosine Accuracy@5
368
+ - type: cosine_accuracy@10
369
+ value: 0.34
370
+ name: Cosine Accuracy@10
371
+ - type: cosine_precision@1
372
+ value: 0.12
373
+ name: Cosine Precision@1
374
+ - type: cosine_precision@3
375
+ value: 0.05999999999999999
376
+ name: Cosine Precision@3
377
+ - type: cosine_precision@5
378
+ value: 0.068
379
+ name: Cosine Precision@5
380
+ - type: cosine_precision@10
381
+ value: 0.068
382
+ name: Cosine Precision@10
383
+ - type: cosine_recall@1
384
+ value: 0.002236456626220743
385
+ name: Cosine Recall@1
386
+ - type: cosine_recall@3
387
+ value: 0.002789859912543284
388
+ name: Cosine Recall@3
389
+ - type: cosine_recall@5
390
+ value: 0.010512144339555038
391
+ name: Cosine Recall@5
392
+ - type: cosine_recall@10
393
+ value: 0.03263772196662673
394
+ name: Cosine Recall@10
395
+ - type: cosine_ndcg@10
396
+ value: 0.07431301845929561
397
+ name: Cosine Ndcg@10
398
+ - type: cosine_mrr@10
399
+ value: 0.16880158730158734
400
+ name: Cosine Mrr@10
401
+ - type: cosine_map@100
402
+ value: 0.021674198565261597
403
+ name: Cosine Map@100
404
+ - task:
405
+ type: information-retrieval
406
+ name: Information Retrieval
407
+ dataset:
408
+ name: NanoNQ
409
+ type: NanoNQ
410
+ metrics:
411
+ - type: cosine_accuracy@1
412
+ value: 0.06
413
+ name: Cosine Accuracy@1
414
+ - type: cosine_accuracy@3
415
+ value: 0.1
416
+ name: Cosine Accuracy@3
417
+ - type: cosine_accuracy@5
418
+ value: 0.16
419
+ name: Cosine Accuracy@5
420
+ - type: cosine_accuracy@10
421
+ value: 0.24
422
+ name: Cosine Accuracy@10
423
+ - type: cosine_precision@1
424
+ value: 0.06
425
+ name: Cosine Precision@1
426
+ - type: cosine_precision@3
427
+ value: 0.039999999999999994
428
+ name: Cosine Precision@3
429
+ - type: cosine_precision@5
430
+ value: 0.036000000000000004
431
+ name: Cosine Precision@5
432
+ - type: cosine_precision@10
433
+ value: 0.026000000000000006
434
+ name: Cosine Precision@10
435
+ - type: cosine_recall@1
436
+ value: 0.04
437
+ name: Cosine Recall@1
438
+ - type: cosine_recall@3
439
+ value: 0.08
440
+ name: Cosine Recall@3
441
+ - type: cosine_recall@5
442
+ value: 0.13
443
+ name: Cosine Recall@5
444
+ - type: cosine_recall@10
445
+ value: 0.21
446
+ name: Cosine Recall@10
447
+ - type: cosine_ndcg@10
448
+ value: 0.11989547330112625
449
+ name: Cosine Ndcg@10
450
+ - type: cosine_mrr@10
451
+ value: 0.10407936507936508
452
+ name: Cosine Mrr@10
453
+ - type: cosine_map@100
454
+ value: 0.10392112551414794
455
+ name: Cosine Map@100
456
+ - task:
457
+ type: nano-beir
458
+ name: Nano BEIR
459
+ dataset:
460
+ name: NanoBEIR mean
461
+ type: NanoBEIR_mean
462
+ metrics:
463
+ - type: cosine_accuracy@1
464
+ value: 0.09333333333333334
465
+ name: Cosine Accuracy@1
466
+ - type: cosine_accuracy@3
467
+ value: 0.18000000000000002
468
+ name: Cosine Accuracy@3
469
+ - type: cosine_accuracy@5
470
+ value: 0.25333333333333335
471
+ name: Cosine Accuracy@5
472
+ - type: cosine_accuracy@10
473
+ value: 0.38000000000000006
474
+ name: Cosine Accuracy@10
475
+ - type: cosine_precision@1
476
+ value: 0.09333333333333334
477
+ name: Cosine Precision@1
478
+ - type: cosine_precision@3
479
+ value: 0.06444444444444443
480
+ name: Cosine Precision@3
481
+ - type: cosine_precision@5
482
+ value: 0.05866666666666667
483
+ name: Cosine Precision@5
484
+ - type: cosine_precision@10
485
+ value: 0.05000000000000001
486
+ name: Cosine Precision@10
487
+ - type: cosine_recall@1
488
+ value: 0.04741215220874025
489
+ name: Cosine Recall@1
490
+ - type: cosine_recall@3
491
+ value: 0.1209299533041811
492
+ name: Cosine Recall@3
493
+ - type: cosine_recall@5
494
+ value: 0.16683738144651836
495
+ name: Cosine Recall@5
496
+ - type: cosine_recall@10
497
+ value: 0.2675459073222089
498
+ name: Cosine Recall@10
499
+ - type: cosine_ndcg@10
500
+ value: 0.1655603115359139
501
+ name: Cosine Ndcg@10
502
+ - type: cosine_mrr@10
503
+ value: 0.1653994708994709
504
+ name: Cosine Mrr@10
505
+ - type: cosine_map@100
506
+ value: 0.12174516178772117
507
+ name: Cosine Map@100
508
+ ---
509
+
510
+ # ModernBERT-base finetuned on MSMARCO via distillation
511
+
512
+ This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on the [msmarco-qwen3-reranker-0.6_b](https://huggingface.co/datasets/tomaarsen/msmarco-Qwen3-Reranker-0.6B) dataset. It maps sentences & paragraphs to a 768-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more.
513
+
514
+ ## Model Details
515
+
516
+ ### Model Description
517
+ - **Model Type:** Sentence Transformer
518
+ - **Base model:** [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) <!-- at revision 8949b909ec900327062f0ebf497f51aef5e6f0c8 -->
519
+ - **Maximum Sequence Length:** 8192 tokens
520
+ - **Output Dimensionality:** 768 dimensions
521
+ - **Similarity Function:** Cosine Similarity
522
+ - **Training Dataset:**
523
+ - [msmarco-qwen3-reranker-0.6_b](https://huggingface.co/datasets/tomaarsen/msmarco-Qwen3-Reranker-0.6B)
524
+ - **Language:** en
525
+ - **License:** apache-2.0
526
+
527
+ ### Model Sources
528
+
529
+ - **Documentation:** [Sentence Transformers Documentation](https://sbert.net)
530
+ - **Repository:** [Sentence Transformers on GitHub](https://github.com/UKPLab/sentence-transformers)
531
+ - **Hugging Face:** [Sentence Transformers on Hugging Face](https://huggingface.co/models?library=sentence-transformers)
532
+
533
+ ### Full Model Architecture
534
+
535
+ ```
536
+ SentenceTransformer(
537
+ (0): Transformer({'max_seq_length': 8192, 'do_lower_case': False, 'architecture': 'ModernBertModel'})
538
+ (1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
539
+ )
540
+ ```
541
+
542
+ ## Usage
543
+
544
+ ### Direct Usage (Sentence Transformers)
545
+
546
+ First install the Sentence Transformers library:
547
+
548
+ ```bash
549
+ pip install -U sentence-transformers
550
+ ```
551
+
552
+ Then you can load this model and run inference.
553
+ ```python
554
+ from sentence_transformers import SentenceTransformer
555
+
556
+ # Download from the 🤗 Hub
557
+ model = SentenceTransformer("tomaarsen/ModernBERT-base-msmarco-margin-mse")
558
+ # Run inference
559
+ queries = [
560
+ "what does ly mean in a blood test",
561
+ ]
562
+ documents = [
563
+ 'According to the Hormone-Refractory Prostate Cancer Association, LY on a blood test stands for lymphocytes. The number in the results represents the percentage of lymphocytes in the white blood count. Lymphocytes should count for 15 to 46.8 percent of white blood cells. Continue Reading.',
564
+ "FROM OUR COMMUNITY. Hi Terry, The LY (Lymphocytes) in your blood test is; the type of white blood cell found in the blood and lymph systems; part of the immune system. BUN/CREAT - Bun and Creatinine are tests done to monitor kidney function. I'm sorry, but I've never heard of the other 2.",
565
+ 'FROM OUR EXPERTS. Trace lysed blood refers to a finding that is usually reported from a urinary dip stick analysis. It implies that there is a small quantity of red cells in the urine that have broken open. The developer on the dip stick reacts with the hemoglobin that is released when the red cells are lysed.',
566
+ ]
567
+ query_embeddings = model.encode_query(queries)
568
+ document_embeddings = model.encode_document(documents)
569
+ print(query_embeddings.shape, document_embeddings.shape)
570
+ # [1, 768] [3, 768]
571
+
572
+ # Get the similarity scores for the embeddings
573
+ similarities = model.similarity(query_embeddings, document_embeddings)
574
+ print(similarities)
575
+ # tensor([[0.9409, 0.9409, 0.9366]])
576
+ ```
577
+
578
+ <!--
579
+ ### Direct Usage (Transformers)
580
+
581
+ <details><summary>Click to see the direct usage in Transformers</summary>
582
+
583
+ </details>
584
+ -->
585
+
586
+ <!--
587
+ ### Downstream Usage (Sentence Transformers)
588
+
589
+ You can finetune this model on your own dataset.
590
+
591
+ <details><summary>Click to expand</summary>
592
+
593
+ </details>
594
+ -->
595
+
596
+ <!--
597
+ ### Out-of-Scope Use
598
+
599
+ *List how the model may foreseeably be misused and address what users ought not to do with the model.*
600
+ -->
601
+
602
+ ## Evaluation
603
+
604
+ ### Metrics
605
+
606
+ #### Information Retrieval
607
+
608
+ * Datasets: `msmarco-eval-1kq-1kd`, `NanoMSMARCO`, `NanoNFCorpus` and `NanoNQ`
609
+ * Evaluated with [<code>InformationRetrievalEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.InformationRetrievalEvaluator)
610
+
611
+ | Metric | msmarco-eval-1kq-1kd | NanoMSMARCO | NanoNFCorpus | NanoNQ |
612
+ |:--------------------|:---------------------|:------------|:-------------|:-----------|
613
+ | cosine_accuracy@1 | 0.781 | 0.1 | 0.12 | 0.06 |
614
+ | cosine_accuracy@3 | 0.887 | 0.28 | 0.16 | 0.1 |
615
+ | cosine_accuracy@5 | 0.917 | 0.36 | 0.24 | 0.16 |
616
+ | cosine_accuracy@10 | 0.943 | 0.56 | 0.34 | 0.24 |
617
+ | cosine_precision@1 | 0.781 | 0.1 | 0.12 | 0.06 |
618
+ | cosine_precision@3 | 0.2957 | 0.0933 | 0.06 | 0.04 |
619
+ | cosine_precision@5 | 0.1834 | 0.072 | 0.068 | 0.036 |
620
+ | cosine_precision@10 | 0.0943 | 0.056 | 0.068 | 0.026 |
621
+ | cosine_recall@1 | 0.781 | 0.1 | 0.0022 | 0.04 |
622
+ | cosine_recall@3 | 0.887 | 0.28 | 0.0028 | 0.08 |
623
+ | cosine_recall@5 | 0.917 | 0.36 | 0.0105 | 0.13 |
624
+ | cosine_recall@10 | 0.943 | 0.56 | 0.0326 | 0.21 |
625
+ | **cosine_ndcg@10** | **0.8656** | **0.3025** | **0.0743** | **0.1199** |
626
+ | cosine_mrr@10 | 0.8404 | 0.2233 | 0.1688 | 0.1041 |
627
+ | cosine_map@100 | 0.8424 | 0.2396 | 0.0217 | 0.1039 |
628
+
629
+ #### Nano BEIR
630
+
631
+ * Dataset: `NanoBEIR_mean`
632
+ * Evaluated with [<code>NanoBEIREvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.NanoBEIREvaluator) with these parameters:
633
+ ```json
634
+ {
635
+ "dataset_names": [
636
+ "msmarco",
637
+ "nfcorpus",
638
+ "nq"
639
+ ]
640
+ }
641
+ ```
642
+
643
+ | Metric | Value |
644
+ |:--------------------|:-----------|
645
+ | cosine_accuracy@1 | 0.0933 |
646
+ | cosine_accuracy@3 | 0.18 |
647
+ | cosine_accuracy@5 | 0.2533 |
648
+ | cosine_accuracy@10 | 0.38 |
649
+ | cosine_precision@1 | 0.0933 |
650
+ | cosine_precision@3 | 0.0644 |
651
+ | cosine_precision@5 | 0.0587 |
652
+ | cosine_precision@10 | 0.05 |
653
+ | cosine_recall@1 | 0.0474 |
654
+ | cosine_recall@3 | 0.1209 |
655
+ | cosine_recall@5 | 0.1668 |
656
+ | cosine_recall@10 | 0.2675 |
657
+ | **cosine_ndcg@10** | **0.1656** |
658
+ | cosine_mrr@10 | 0.1654 |
659
+ | cosine_map@100 | 0.1217 |
660
+
661
+ <!--
662
+ ## Bias, Risks and Limitations
663
+
664
+ *What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.*
665
+ -->
666
+
667
+ <!--
668
+ ### Recommendations
669
+
670
+ *What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*
671
+ -->
672
+
673
+ ## Training Details
674
+
675
+ ### Training Dataset
676
+
677
+ #### msmarco-qwen3-reranker-0.6_b
678
+
679
+ * Dataset: [msmarco-qwen3-reranker-0.6_b](https://huggingface.co/datasets/tomaarsen/msmarco-Qwen3-Reranker-0.6B) at [20c25c8](https://huggingface.co/datasets/tomaarsen/msmarco-Qwen3-Reranker-0.6B/tree/20c25c858f80ba96bdb58f1558746e077001303a)
680
+ * Size: 10,000 training samples
681
+ * Columns: <code>query</code>, <code>positive</code>, <code>negative_1</code>, <code>negative_2</code>, <code>negative_3</code>, <code>negative_4</code>, <code>negative_5</code>, <code>negative_6</code>, <code>negative_7</code>, <code>negative_8</code>, and <code>score</code>
682
+ * Approximate statistics based on the first 1000 samples:
683
+ | | query | positive | negative_1 | negative_2 | negative_3 | negative_4 | negative_5 | negative_6 | negative_7 | negative_8 | score |
684
+ |:--------|:---------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:-----------------------------------|
685
+ | type | string | string | string | string | string | string | string | string | string | string | list |
686
+ | details | <ul><li>min: 5 tokens</li><li>mean: 9.32 tokens</li><li>max: 40 tokens</li></ul> | <ul><li>min: 17 tokens</li><li>mean: 81.37 tokens</li><li>max: 288 tokens</li></ul> | <ul><li>min: 16 tokens</li><li>mean: 68.92 tokens</li><li>max: 208 tokens</li></ul> | <ul><li>min: 12 tokens</li><li>mean: 70.8 tokens</li><li>max: 204 tokens</li></ul> | <ul><li>min: 15 tokens</li><li>mean: 70.5 tokens</li><li>max: 260 tokens</li></ul> | <ul><li>min: 16 tokens</li><li>mean: 71.64 tokens</li><li>max: 244 tokens</li></ul> | <ul><li>min: 13 tokens</li><li>mean: 72.57 tokens</li><li>max: 226 tokens</li></ul> | <ul><li>min: 11 tokens</li><li>mean: 72.34 tokens</li><li>max: 198 tokens</li></ul> | <ul><li>min: 15 tokens</li><li>mean: 73.57 tokens</li><li>max: 202 tokens</li></ul> | <ul><li>min: 15 tokens</li><li>mean: 71.21 tokens</li><li>max: 200 tokens</li></ul> | <ul><li>size: 9 elements</li></ul> |
687
+ * Samples:
688
+ | query | positive | negative_1 | negative_2 | negative_3 | negative_4 | negative_5 | negative_6 | negative_7 | negative_8 | score |
689
+ |:-------------------------------------------------------|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-----------------------------------------------------------------------------|
690
+ | <code>what is clomiphene</code> | <code>Uses of This Medicine. Clomiphene is used as a fertility medicine in some women who are unable to become pregnant. Clomiphene probably works by changing the hormone balance of the body. In women, this causes ovulation to occur and prepares the body for pregnancy.ses of This Medicine. Clomiphene is used as a fertility medicine in some women who are unable to become pregnant. Clomiphene probably works by changing the hormone balance of the body. In women, this causes ovulation to occur and prepares the body for pregnancy.</code> | <code>Clomiphene citrate, a synthetic hormone commonly used to induce or regulate ovulation, is the most often prescribed fertility pill. Brand names for clomiphene citrate include Clomid and Serophene. Clomiphene works indirectly to stimulate ovulation.</code> | <code>Occasionally, clomiphene can stimulate the ovaries too much, causing multiple eggs to be released, which can result in multiple births, such as twins or triplets (see Clomid and Twins) . Clomiphene is one of the least expensive and easiest-to-use fertility drugs. However, it will not work for all types of infertility. Your healthcare provider needs to try to find your cause of infertility before you try clomiphene.</code> | <code>Clomiphene Citrate offers two benefits to the performance enhancing athlete with one being primary. Most commonly, this SERM is used for post cycle recovery purposes; specifically to stimulate natural testosterone production that has been suppressed due to the use of anabolic steroids.</code> | <code>PCOS and ovulation problems and Clomid treatment. Clomid (clomiphene citrate or Serophene) is an oral medication that is commonly used for the treatment of infertility. It is often given to try to induce ovulation in women that do not develop and release an egg (ovulate) on their own.</code> | <code>Indication: Clomid (clomiphene citrate) is often the first choice for treating infertility, because it's effective and been used for more than 40 years.</code> | <code>Clomid Description. 1 Clomid (clomiphene citrate tablets USP) is an orally administered, nonsteroidal, ovulatory stimulant designated chemically as 2-[p-(2-chloro-1,2-diphenylvinyl)phenoxy] triethylamine citrate (1:1). It has the molecular formula of C26H28ClNO • C6H8O7 and a molecular weight of 598.09.</code> | <code>PCOS and ovulation problems and Clomid treatment. Clomid (clomiphene citrate or Serophene) is an oral medication that is commonly used for the treatment of infertility. 1 It is often given to try to induce ovulation in women that do not develop and release an egg (ovulate) on their own. Clomid is started early in the menstrual cycle and is taken for five days either from cycle days 3 through 7, or from day 5 through 9. 2 Clomid is usually started at a dose of one tablet (50mg) daily-taken any time of day.</code> | <code>Clomid is taken as a pill. This is unlike the stronger fertility drugs, which require injection. Clomid is also very effective, stimulating ovulation 80 percent of the time. Clomid may also be marketed under the name Serophene, or you may see it sold under its generic name, clomiphene citrate. Note: Clomid can also be used as a treatment for male infertility. This article focuses on Clomid treatment in women.</code> | <code>[4.75390625, 6.9375, 3.92578125, 1.0400390625, 5.61328125, ...]</code> |
691
+ | <code>typical accountant cost for it contractor</code> | <code>In the current market, we’ve seen rates as low as £50 +VAT, and as high as £180 +VAT for dedicated contractor accountants. Interestingly, the average cost of contractor accounting has not risen in line with inflation over the past decade.</code> | <code>So, how much does a contractor cost, anywhere from 5% to 25% of the total project cost, with the average ranging 10-15%.ypically the contractor' s crew will be general carpentry trades people, some who may have more specialized skills. Exactly how a general contractor charges for a project depends on the type of contract you agree to. There are three common types of cost contracts, fixed price, time & materials and cost plus a fee.</code> | <code>1 Accountants charge $150-$400 or more an hour, depending on the type of work, the size of the firm and its location. 2 You'll pay lower rates for routine work done by a less-experienced associate or lesser-trained employee, such as $30-$50 for bookkeeping services. 3 An accountant's total fee depends on the project. For a simple start-up, expect a minimum of 0.5-1.5 hours of consultation ($75-$600) to go over your business structure and basic tax issues.</code> | <code>So, how much does a contractor cost, anywhere from 5% to 25% of the total project cost, with the average ranging 10-15%.xactly how a general contractor charges for a project depends on the type of contract you agree to. There are three common types of cost contracts, fixed price, time & materials and cost plus a fee. Each contract type has pros and cons for both the consumer and for the contractor.</code> | <code>1 Accountants charge $150-$400 or more an hour, depending on the type of work, the size of the firm and its location. 2 You'll pay lower rates for routine work done by a less-experienced associate or lesser-trained employee, such as $30-$50 for bookkeeping services. 3 An accountant's total fee depends on the project.</code> | <code>average data entry keystrokes per hour salaries the average salary for data entry keystrokes per hour jobs is $ 20000</code> | <code>Accounting services are typically $250 to $400 per month, or $350 to $500 per quarter. Sales tax and bank recs included. We do all the processing, filing and tax deposits. 5 employees, bi-weekly payroll, direct deposit, $135 per month.</code> | <code>The less that is outsourced, the cheaper it will be for you. A bookkeeper should be paid between $15 and $18 per hour. An accountant with a undergraduate degree (4-years) should be paid somewhere around $20/hour but that still depends on what you're having them do. An accountant with a graduate degree (masters) should be paid between $25 and $30 per hour.</code> | <code>Pay by Experience Level for Intelligence Analyst. Median of all compensation (including tips, bonus, and overtime) by years of experience. Intelligence Analysts with a lot of experience tend to enjoy higher earnings.</code> | <code>[7.44921875, 3.271484375, 5.859375, 3.234375, 5.421875, ...]</code> |
692
+ | <code>what is mch on a blood test</code> | <code>What High Levels Mean. MCH levels in blood tests are considered high if they are 35 or higher. A normal hemoglobin level is considered to be in the range between 26 and 33 picograms per red blood cell. High MCH levels can indicate macrocytic anemia, which can be caused by insufficient vitamin B12.acrocytic RBCs are large so tend to have a higher MCH, while microcytic red cells would have a lower value.”. MCH is one of three red blood cell indices (MCHC and MCV are the other two). The measurements are done by machine and can help with diagnosis of medical problems.</code> | <code>MCH stands for mean corpuscular hemoglobin. It estimates the average amount of hemoglobin in each red blood cell, measured in picograms (a trillionth of a gram). Automated cell counters calculate the MCH, which is reported as part of a complete blood count (CBC) test. MCH may be low in iron-deficiency anemia, and may be high in anemia due to vitamin B12 or folate deficiency. Other forms of anemia can also cause MCH to be abnormal. Doctors only use the MCH as supporting information, not to make a diagnosis.</code> | <code>A. MCH stands for mean corpuscular hemoglobin. It estimates the average amount of hemoglobin in each red blood cell, measured in picograms (a trillionth of a gram). Automated cell counters calculate the MCH, which is reported as part of a complete blood count (CBC) test. MCH may be low in iron-deficiency anemia, and may be high in anemia due to vitamin B12 or folate deficiency. Other forms of anemia can also cause MCH to be abnormal.</code> | <code>The test used to determine the quantity of hemoglobin in the blood is known as the MCH blood test. The full form of MCH is Mean Corpuscular Hemoglobin. This test is therefore used to determine the average amount of hemoglobin per red blood cell in the body. The results of the MCH blood test are therefore reported in picograms, a tiny measure of weight.</code> | <code>MCH blood test high indicates that there is a poor supply of oxygen to the blood where as MCH blood test low mean that hemoglobin is too little in the cells indicating a lack of iron. It is important that iron is maintained at a certain level as too much or too little iron can be dangerous to your body.</code> | <code>slide 1 of 7. What Is MCH? MCH is the initialism for Mean Corpuscular Hemoglobin. Taken from Latin, the term refers to the average amount of hemoglobin found in red blood cells. A CBC (complete blood count) blood test can be used to monitor MCH levels in the blood. Lab Tests Online explains that the MCH aspect of a CBC test “is a measurement of the average amount of oxygen-carrying hemoglobin inside a red blood cell. Macrocytic RBCs are large so tend to have a higher MCH, while microcytic red cells would have a lower value..</code> | <code>The test used to determine the quantity of hemoglobin in the blood is known as the MCH blood test. The full form of MCH is Mean Corpuscular Hemoglobin. This test is therefore used to determine the average amount of hemoglobin per red blood cell in the body. The results of the MCH blood test are therefore reported in picograms, a tiny measure of weight. The normal range of the MCH blood test is between 26 and 33 pg per cell.</code> | <code>A MCHC test is a test that is carried out to test a person for anemia. The MCHC in a MCHC test stands for Mean Corpuscular Hemoglobin Concentration. MCHC is the calculation of the average hemoglobin inside a red blood cell. A MCHC test can be performed along with a MCV test (Mean Corpuscular Volume).Both levels are used to test people for anemia.The MCHC test is also known as the MCH blood test which tests the levels of hemoglobin in the blood. The MCHC test can be ordered as part of a complete blood count (CBC) test.CHC is measured in grams per deciliter. Normal readings for MCHC are 31 grams per deciliter to 35 grams per deciliter. A MCHC blood test may be ordered when a person is showing signs of fatigue or weakness, when there is an infection, is bleeding or bruising easily or when there is an inflammation.</code> | <code>The test looks at the average amount of hemoglobin per red cell. So MCHC = the amount of hemoglobin present in each red blood cell. A MCHC blood test could be ordered for someone who has signs of fatigue or weakness, when there is an infection, is bleeding or bruising easily or when there is noticeable inflammation.</code> | <code>[6.44921875, 7.05078125, 7.2109375, 8.40625, 6.53515625, ...]</code> |
693
+ * Loss: [<code>MarginMSELoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#marginmseloss)
694
+
695
+ ### Evaluation Dataset
696
+
697
+ #### msmarco-qwen3-reranker-0.6_b
698
+
699
+ * Dataset: [msmarco-qwen3-reranker-0.6_b](https://huggingface.co/datasets/tomaarsen/msmarco-Qwen3-Reranker-0.6B) at [20c25c8](https://huggingface.co/datasets/tomaarsen/msmarco-Qwen3-Reranker-0.6B/tree/20c25c858f80ba96bdb58f1558746e077001303a)
700
+ * Size: 1,000 evaluation samples
701
+ * Columns: <code>query</code>, <code>positive</code>, <code>negative_1</code>, <code>negative_2</code>, <code>negative_3</code>, <code>negative_4</code>, <code>negative_5</code>, <code>negative_6</code>, <code>negative_7</code>, <code>negative_8</code>, and <code>score</code>
702
+ * Approximate statistics based on the first 1000 samples:
703
+ | | query | positive | negative_1 | negative_2 | negative_3 | negative_4 | negative_5 | negative_6 | negative_7 | negative_8 | score |
704
+ |:--------|:---------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:-----------------------------------|
705
+ | type | string | string | string | string | string | string | string | string | string | string | list |
706
+ | details | <ul><li>min: 4 tokens</li><li>mean: 9.27 tokens</li><li>max: 24 tokens</li></ul> | <ul><li>min: 22 tokens</li><li>mean: 82.29 tokens</li><li>max: 236 tokens</li></ul> | <ul><li>min: 11 tokens</li><li>mean: 69.82 tokens</li><li>max: 215 tokens</li></ul> | <ul><li>min: 11 tokens</li><li>mean: 69.4 tokens</li><li>max: 209 tokens</li></ul> | <ul><li>min: 16 tokens</li><li>mean: 71.47 tokens</li><li>max: 223 tokens</li></ul> | <ul><li>min: 14 tokens</li><li>mean: 70.96 tokens</li><li>max: 225 tokens</li></ul> | <ul><li>min: 14 tokens</li><li>mean: 73.09 tokens</li><li>max: 218 tokens</li></ul> | <ul><li>min: 16 tokens</li><li>mean: 69.31 tokens</li><li>max: 215 tokens</li></ul> | <ul><li>min: 14 tokens</li><li>mean: 72.3 tokens</li><li>max: 226 tokens</li></ul> | <ul><li>min: 11 tokens</li><li>mean: 70.66 tokens</li><li>max: 210 tokens</li></ul> | <ul><li>size: 9 elements</li></ul> |
707
+ * Samples:
708
+ | query | positive | negative_1 | negative_2 | negative_3 | negative_4 | negative_5 | negative_6 | negative_7 | negative_8 | score |
709
+ |:-------------------------------------------------|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-----------------------------------------------------------------------------|
710
+ | <code>how many people employed by shell</code> | <code>Shell worldwide. Royal Dutch Shell was formed in 1907, although our history dates back to the early 19th century, to a small shop in London where the Samuel family sold sea shells. Today, Shell is one of the world’s major energy companies, employing an average of 93,000 people and operating in more than 70 countries. Our headquarters are in The Hague, the Netherlands, and our Chief Executive Officer is Ben van Beurden.</code> | <code>Show sources information. This statistic shows the number of employees at SeaWorld Entertainment, Inc. in the United States, by type. As of December 2016, SeaWorld employed 5,000 full-time employees and counted approximately 13,000 seasonal employees during their peak operating season.</code> | <code>Jobs, companies, people, and articles for LinkedIn’s Payroll Specialist - Addus Homecare, Inc. members. Insights about Payroll Specialist - Addus Homecare, Inc. members on LinkedIn. Median salary $31,300.</code> | <code>As of July 2014, there are 139 million people employed in the United States. This number is up by 209,000 employees from June and by 1.47 million from the beginning of 2014.</code> | <code>average data entry keystrokes per hour salaries the average salary for data entry keystrokes per hour jobs is $ 20000</code> | <code>Research and review Plano Synergy jobs. Learn more about a career with Plano Synergy including all recent jobs, hiring trends, salaries, work environment and more. Find Jobs Company Reviews Find Salaries Find Resumes Employers / Post Job Upload your resume Sign in</code> | <code>From millions of real job salary data. 13 Customer Support Specialist salary data. Average Customer Support Specialist salary is $59,032 Detailed Customer Support Specialist starting salary, median salary, pay scale, bonus data report Register & Know how much $ you can earn \| Sign In</code> | <code>From millions of real job salary data. 1 Ceo Ally salary data. Average Ceo Ally salary is $55,000 Detailed Ceo Ally starting salary, median salary, pay scale, bonus data report</code> | <code>HelpSystems benefits and perks, including insurance benefits, retirement benefits, and vacation policy. Reported anonymously by HelpSystems employees. Glassdoor uses cookies to improve your site experience.</code> | <code>[6.265625, -1.3671875, -6.91796875, 1.111328125, -7.96875, ...]</code> |
711
+ | <code>what is a lcsw</code> | <code>LCSW is an acronym for licensed clinical social worker, and people with this title are skilled professionals who meet certain requirements and work in a variety of fields. The term social worker is not always synonymous with licensed clinical social worker.</code> | <code>LISW means the person is a Licensed Independent Social Worker. LCSW means the person is a Licensed Clinical Social Worker. Source(s): Introduction to Social Work 101 at University of Nevada, Las Vega (UNLV) Dorothy K. · 1 decade ago.</code> | <code>An LCSW is a licensed clinical social worker. A LMHC is the newest addition to the field of mental health. They are highly similar and can do most of the same things with few exceptions. One thing to keep in mind is that because the LMHC lincense is so new, there are fewer in number in the field.n LCSW is a licensed clinical social worker. A LMHC is the newest addition to the field of mental health. They are highly similar and can do most of the same things with few exceptions. One thing to keep in mind is that because the LMHC lincense is so new, there are fewer in number in the field.</code> | <code>The Licensed Clinical Social Worker or LCSW, is a sub-sector within the field of Social Work. They work with clients in order to help them deal with issues involving their mental and emotional health. This could be related to substance abuse, past trauma or mental illness.</code> | <code>Licensed Clinical Social Worker \| LCSW. The Licensed Clinical Social Worker or LCSW, is a sub-sector within the field of Social Work. LCSW's work with clients in order to help deal with issues involving mental and emotional health. There are a wide variety of specializations the Licensed Clinical Social Worker can focus on.</code> | <code>The LMSW exam is a computer-based test containing 170 multiple-choice questions designed to measure minimum competencies in four categories of social work practice: Human development, diversity, and behavior in the environment. Assessment and intervention planning.</code> | <code>The Licensed Clinical Social Worker, also known as the LCSW, is a branch of social work that specializes in mental health therapy in a counseling format. Becoming an LCSW requires a significant degree of training, including having earned a Master of Social Work (MSW) degree from a Council on Social Work Education (CSWE) accredited program.</code> | <code>a. The examination requirements for licensure as an LCSW include passing the Clinical Examination of the ASWB or the Clinical Social Workers Examination of the State of California. Scope of practice-Limitations. a.To the extent they are prepared through education and training, an LCSW can engage in all acts and practices defined as the practice of clinical social work. Certified Social Work (CSW): CSW means a licensed certified social worker. A CSW must have a master s degree.</code> | <code>The LTCM Client is a way for companies to stay in touch with you, their customers, in a way that is unobtrusive and completely under the users' control. It's an application that runs quietly on the computer. Users can and should customize the client to match their desired preferences.</code> | <code>[7.34375, 6.046875, 7.09765625, 6.46484375, 7.28515625, ...]</code> |
712
+ | <code>does oolong tea have much caffeine?</code> | <code>At a given weight, tea contains more caffeine than coffee, but this doesn’t mean that a usual portion of tea contains more caffeine than coffee because tea is usually brewed in a weak way. Some kinds of tea, such as oolong and black tea, contain higher level of caffeine than most other teas. Among six basic teas (green, black, yellow, white, oolong, dark), green tea contains less caffeine than black tea and white tea contains less than green tea. But many studies found that the caffeine content varies more among individual teas than it does among broad categories.</code> | <code>Actually, oolong tea has less caffeine than coffee and black tea. A cup of oolong tea only has about 1/3 of caffeine of a cup of coffee. According to a research conducted by HICKS M.B, the caffeine decreases whenever the tea leaves go through the process of brewing.</code> | <code>Oolong tea contains caffeine. Caffeine works by stimulating the central nervous system (CNS), heart, and muscles. Oolong tea also contains theophylline and theobromine, which are chemicals similar to caffeine. Too much oolong tea, more than five cups per day, can cause side effects because of the caffeine.</code> | <code>Oolong tea, made from more mature leaves, usually have less caffeine than green tea. On the flip side, mature leaves contain less theanine, a sweet, natural relaxant that makes a tea much less caffeinated than it actually is. That is the theory, anyway.</code> | <code>Oolong tea is a product made from the leaves, buds, and stems of the Camellia sinensis plant. This is the same plant that is also used to make black tea and green tea. The difference is in the processing.Oolong tea is partially fermented, black tea is fully fermented, and green tea is unfermented. Oolong tea is used to sharpen thinking skills and improve mental alertness. It is also used to prevent cancer, tooth decay, osteoporosis, and heart disease.owever, do not drink more than 2 cups a day of oolong tea. That amount of tea contains about 200 mg of caffeine. Too much caffeine during pregnancy might cause premature delivery, low birth weight, and harm to the baby.</code> | <code>A Department of Nutritional Services report provides the following ranges of caffeine content for a cup of tea made with loose leaves: 1 Black Tea: 23 - 110 mg. 2 Oolong Tea: 12 - 55 mg. Green Tea: 8 - 36 mg.</code> | <code>Oolong tea is a product made from the leaves, buds, and stems of the Camellia sinensis plant. This is the same plant that is also used to make black tea and green tea. The difference is in the processing. Oolong tea is partially fermented, black tea is fully fermented, and green tea is unfermented. Oolong tea is used to sharpen thinking skills and improve mental alertness. It is also used to prevent cancer, tooth decay, osteoporosis, and heart disease.</code> | <code>Health Effects of Tea – Caffeine. In dry form, a kilogram of black tea has twice the caffeine as a kilogram of coffee…. But one kilogram of black tea makes about 450 cups of tea and one kilogram of coffee makes about 100 cups of coffee, so…. There is less caffeine in a cup of tea than in a cup of coffee. Green teas have less caffeine than black teas, and white teas have even less caffeine than green teas. Oolong teas fall between black and green teas. Herbal tea, because it is not made from the same tea plant, is caffeine-free, naturally. Here is a graphical representation of their respective caffeine content.</code> | <code>The average 8-ounce serving of brewed black tea contains 14 to 70 mg of caffeine. This compares to 24 to 45 mg of caffeine found in green tea. An 8-ounce glass of instant iced tea prepared with water contains 11 to 47 mg of caffeine. Most ready-to-drink bottled teas contain 5 to 40 mg of caffeine. Just as with coffee, decaffeinated tea still contains 5 to 10 mg of caffeine per cup.</code> | <code>[7.60546875, 8.78125, 9.109375, 8.609375, 7.984375, ...]</code> |
713
+ * Loss: [<code>MarginMSELoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#marginmseloss)
714
+
715
+ ### Training Hyperparameters
716
+ #### Non-Default Hyperparameters
717
+
718
+ - `eval_strategy`: steps
719
+ - `per_device_train_batch_size`: 16
720
+ - `per_device_eval_batch_size`: 16
721
+ - `learning_rate`: 4e-05
722
+ - `num_train_epochs`: 1
723
+ - `warmup_ratio`: 0.1
724
+ - `bf16`: True
725
+
726
+ #### All Hyperparameters
727
+ <details><summary>Click to expand</summary>
728
+
729
+ - `overwrite_output_dir`: False
730
+ - `do_predict`: False
731
+ - `eval_strategy`: steps
732
+ - `prediction_loss_only`: True
733
+ - `per_device_train_batch_size`: 16
734
+ - `per_device_eval_batch_size`: 16
735
+ - `per_gpu_train_batch_size`: None
736
+ - `per_gpu_eval_batch_size`: None
737
+ - `gradient_accumulation_steps`: 1
738
+ - `eval_accumulation_steps`: None
739
+ - `torch_empty_cache_steps`: None
740
+ - `learning_rate`: 4e-05
741
+ - `weight_decay`: 0.0
742
+ - `adam_beta1`: 0.9
743
+ - `adam_beta2`: 0.999
744
+ - `adam_epsilon`: 1e-08
745
+ - `max_grad_norm`: 1.0
746
+ - `num_train_epochs`: 1
747
+ - `max_steps`: -1
748
+ - `lr_scheduler_type`: linear
749
+ - `lr_scheduler_kwargs`: {}
750
+ - `warmup_ratio`: 0.1
751
+ - `warmup_steps`: 0
752
+ - `log_level`: passive
753
+ - `log_level_replica`: warning
754
+ - `log_on_each_node`: True
755
+ - `logging_nan_inf_filter`: True
756
+ - `save_safetensors`: True
757
+ - `save_on_each_node`: False
758
+ - `save_only_model`: False
759
+ - `restore_callback_states_from_checkpoint`: False
760
+ - `no_cuda`: False
761
+ - `use_cpu`: False
762
+ - `use_mps_device`: False
763
+ - `seed`: 42
764
+ - `data_seed`: None
765
+ - `jit_mode_eval`: False
766
+ - `use_ipex`: False
767
+ - `bf16`: True
768
+ - `fp16`: False
769
+ - `fp16_opt_level`: O1
770
+ - `half_precision_backend`: auto
771
+ - `bf16_full_eval`: False
772
+ - `fp16_full_eval`: False
773
+ - `tf32`: None
774
+ - `local_rank`: 0
775
+ - `ddp_backend`: None
776
+ - `tpu_num_cores`: None
777
+ - `tpu_metrics_debug`: False
778
+ - `debug`: []
779
+ - `dataloader_drop_last`: False
780
+ - `dataloader_num_workers`: 0
781
+ - `dataloader_prefetch_factor`: None
782
+ - `past_index`: -1
783
+ - `disable_tqdm`: False
784
+ - `remove_unused_columns`: True
785
+ - `label_names`: None
786
+ - `load_best_model_at_end`: False
787
+ - `ignore_data_skip`: False
788
+ - `fsdp`: []
789
+ - `fsdp_min_num_params`: 0
790
+ - `fsdp_config`: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}
791
+ - `tp_size`: 0
792
+ - `fsdp_transformer_layer_cls_to_wrap`: None
793
+ - `accelerator_config`: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None}
794
+ - `deepspeed`: None
795
+ - `label_smoothing_factor`: 0.0
796
+ - `optim`: adamw_torch
797
+ - `optim_args`: None
798
+ - `adafactor`: False
799
+ - `group_by_length`: False
800
+ - `length_column_name`: length
801
+ - `ddp_find_unused_parameters`: None
802
+ - `ddp_bucket_cap_mb`: None
803
+ - `ddp_broadcast_buffers`: False
804
+ - `dataloader_pin_memory`: True
805
+ - `dataloader_persistent_workers`: False
806
+ - `skip_memory_metrics`: True
807
+ - `use_legacy_prediction_loop`: False
808
+ - `push_to_hub`: False
809
+ - `resume_from_checkpoint`: None
810
+ - `hub_model_id`: None
811
+ - `hub_strategy`: every_save
812
+ - `hub_private_repo`: None
813
+ - `hub_always_push`: False
814
+ - `gradient_checkpointing`: False
815
+ - `gradient_checkpointing_kwargs`: None
816
+ - `include_inputs_for_metrics`: False
817
+ - `include_for_metrics`: []
818
+ - `eval_do_concat_batches`: True
819
+ - `fp16_backend`: auto
820
+ - `push_to_hub_model_id`: None
821
+ - `push_to_hub_organization`: None
822
+ - `mp_parameters`:
823
+ - `auto_find_batch_size`: False
824
+ - `full_determinism`: False
825
+ - `torchdynamo`: None
826
+ - `ray_scope`: last
827
+ - `ddp_timeout`: 1800
828
+ - `torch_compile`: False
829
+ - `torch_compile_backend`: None
830
+ - `torch_compile_mode`: None
831
+ - `include_tokens_per_second`: False
832
+ - `include_num_input_tokens_seen`: False
833
+ - `neftune_noise_alpha`: None
834
+ - `optim_target_modules`: None
835
+ - `batch_eval_metrics`: False
836
+ - `eval_on_start`: False
837
+ - `use_liger_kernel`: False
838
+ - `eval_use_gather_object`: False
839
+ - `average_tokens_across_devices`: False
840
+ - `prompts`: None
841
+ - `batch_sampler`: batch_sampler
842
+ - `multi_dataset_batch_sampler`: proportional
843
+ - `router_mapping`: {}
844
+ - `learning_rate_mapping`: {}
845
+
846
+ </details>
847
+
848
+ ### Training Logs
849
+ | Epoch | Step | Training Loss | Validation Loss | msmarco-eval-1kq-1kd_cosine_ndcg@10 | NanoMSMARCO_cosine_ndcg@10 | NanoNFCorpus_cosine_ndcg@10 | NanoNQ_cosine_ndcg@10 | NanoBEIR_mean_cosine_ndcg@10 |
850
+ |:-----:|:----:|:-------------:|:---------------:|:-----------------------------------:|:--------------------------:|:---------------------------:|:---------------------:|:----------------------------:|
851
+ | 0.032 | 20 | 626.2853 | - | - | - | - | - | - |
852
+ | 0.064 | 40 | 150.4493 | - | - | - | - | - | - |
853
+ | 0.096 | 60 | 67.3182 | - | - | - | - | - | - |
854
+ | 0.128 | 80 | 53.5684 | - | - | - | - | - | - |
855
+ | 0.16 | 100 | 37.7594 | 37.6225 | 0.0996 | 0.0127 | 0.0160 | 0.0 | 0.0096 |
856
+ | 0.192 | 120 | 34.6859 | - | - | - | - | - | - |
857
+ | 0.224 | 140 | 36.1137 | - | - | - | - | - | - |
858
+ | 0.256 | 160 | 30.4027 | - | - | - | - | - | - |
859
+ | 0.288 | 180 | 29.148 | - | - | - | - | - | - |
860
+ | 0.32 | 200 | 33.1368 | 29.7916 | 0.2748 | 0.0432 | 0.0228 | 0.0 | 0.0220 |
861
+ | 0.352 | 220 | 27.5536 | - | - | - | - | - | - |
862
+ | 0.384 | 240 | 27.2182 | - | - | - | - | - | - |
863
+ | 0.416 | 260 | 25.0055 | - | - | - | - | - | - |
864
+ | 0.448 | 280 | 24.3704 | - | - | - | - | - | - |
865
+ | 0.48 | 300 | 23.1422 | 23.1264 | 0.5906 | 0.1270 | 0.0205 | 0.0261 | 0.0579 |
866
+ | 0.512 | 320 | 22.3186 | - | - | - | - | - | - |
867
+ | 0.544 | 340 | 24.1421 | - | - | - | - | - | - |
868
+ | 0.576 | 360 | 20.9064 | - | - | - | - | - | - |
869
+ | 0.608 | 380 | 18.2549 | - | - | - | - | - | - |
870
+ | 0.64 | 400 | 19.5288 | 19.2762 | 0.7293 | 0.2216 | 0.0404 | 0.0758 | 0.1126 |
871
+ | 0.672 | 420 | 19.1762 | - | - | - | - | - | - |
872
+ | 0.704 | 440 | 17.4021 | - | - | - | - | - | - |
873
+ | 0.736 | 460 | 18.0734 | - | - | - | - | - | - |
874
+ | 0.768 | 480 | 17.8102 | - | - | - | - | - | - |
875
+ | 0.8 | 500 | 18.1116 | 17.3469 | 0.8224 | 0.2664 | 0.0576 | 0.1053 | 0.1431 |
876
+ | 0.832 | 520 | 16.9641 | - | - | - | - | - | - |
877
+ | 0.864 | 540 | 17.378 | - | - | - | - | - | - |
878
+ | 0.896 | 560 | 16.3021 | - | - | - | - | - | - |
879
+ | 0.928 | 580 | 14.9917 | - | - | - | - | - | - |
880
+ | 0.96 | 600 | 17.5367 | 16.2952 | 0.8594 | 0.3014 | 0.0721 | 0.1187 | 0.1641 |
881
+ | 0.992 | 620 | 15.6708 | - | - | - | - | - | - |
882
+ | -1 | -1 | - | - | 0.8656 | 0.3025 | 0.0743 | 0.1199 | 0.1656 |
883
+
884
+
885
+ ### Framework Versions
886
+ - Python: 3.11.10
887
+ - Sentence Transformers: 5.1.0.dev0
888
+ - Transformers: 4.51.2
889
+ - PyTorch: 2.5.1+cu124
890
+ - Accelerate: 1.5.2
891
+ - Datasets: 3.5.0
892
+ - Tokenizers: 0.21.0
893
+
894
+ ## Citation
895
+
896
+ ### BibTeX
897
+
898
+ #### Sentence Transformers
899
+ ```bibtex
900
+ @inproceedings{reimers-2019-sentence-bert,
901
+ title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
902
+ author = "Reimers, Nils and Gurevych, Iryna",
903
+ booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
904
+ month = "11",
905
+ year = "2019",
906
+ publisher = "Association for Computational Linguistics",
907
+ url = "https://arxiv.org/abs/1908.10084",
908
+ }
909
+ ```
910
+
911
+ #### MarginMSELoss
912
+ ```bibtex
913
+ @misc{hofstätter2021improving,
914
+ title={Improving Efficient Neural Ranking Models with Cross-Architecture Knowledge Distillation},
915
+ author={Sebastian Hofstätter and Sophia Althammer and Michael Schröder and Mete Sertkan and Allan Hanbury},
916
+ year={2021},
917
+ eprint={2010.02666},
918
+ archivePrefix={arXiv},
919
+ primaryClass={cs.IR}
920
+ }
921
+ ```
922
+
923
+ <!--
924
+ ## Glossary
925
+
926
+ *Clearly define terms in order to be accessible across audiences.*
927
+ -->
928
+
929
+ <!--
930
+ ## Model Card Authors
931
+
932
+ *Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.*
933
+ -->
934
+
935
+ <!--
936
+ ## Model Card Contact
937
+
938
+ *Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.*
939
+ -->
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