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1
- ---
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- license: cc-by-sa-4.0
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: sentence-transformers/all-mpnet-base-v2
3
+ datasets: []
4
+ language: []
5
+ library_name: sentence-transformers
6
+ metrics:
7
+ - pearson_cosine
8
+ - spearman_cosine
9
+ - pearson_manhattan
10
+ - spearman_manhattan
11
+ - pearson_euclidean
12
+ - spearman_euclidean
13
+ - pearson_dot
14
+ - spearman_dot
15
+ - pearson_max
16
+ - spearman_max
17
+ pipeline_tag: sentence-similarity
18
+ tags:
19
+ - sentence-transformers
20
+ - sentence-similarity
21
+ - feature-extraction
22
+ - generated_from_trainer
23
+ - dataset_size:129
24
+ - loss:CoSENTLoss
25
+ widget:
26
+ - source_sentence: 'traces historical and scientific advancement of our understanding
27
+ of earths cosmic context introduces basic physical principles by which planets
28
+ form and create their associated features of rings satellites diverse landscapes
29
+ atmospheres and climates includes the physics of asteroids and comets and their
30
+ orbital characteristics and links to meteorites considers one of the most fundamental
31
+ questions whether or not we are alone by detailing the scientific exploration
32
+ goals to be achieved at the moon mars and beyond '
33
+ sentences:
34
+ - 'this is an introduction to the study of the solar system with emphasis on the
35
+ latest spacecraft results the subject covers basic principles rather than detailed
36
+ mathematical and physical models topics include an overview of the solar system planetary
37
+ orbits rings planetary formation meteorites asteroids comets planetary surfaces
38
+ and cratering planetary interiors planetary atmospheres and life in the solar
39
+ system '
40
+ - 'in this course describes the largescale circulation systems of the tropical atmosphere
41
+ are used to infer the nalyses the dynamics of such systems the course includes
42
+ phase equilibria of homogeneous and heterogeneous systems and thermodynamic modeling
43
+ of nonideal crystalline solutions it also surveys the processes that lead to
44
+ the formation of metamorphic and igneous rocks in the major tectonic environments
45
+ in the earths crust and mantle '
46
+ - this introductory course presents a basic study in oceanography and the utilization
47
+ of seismic waves for the study of ocean it introduces techniques necessary for
48
+ understanding of elastic wave propagation in layered media
49
+ - source_sentence: introduction to the physics of atmospheric radiation remote sensing
50
+ and convection including use of computer codes risotopic contents occurrence
51
+ in modern organisms and environments diagenetic pathways analytical techniques physics
52
+ of dry and moist convection including moist thermodynamics radiativeconvective
53
+ equilibrium solution of inverse problems in remote sensing of atmospheric temperature
54
+ and composition students taking the graduate version complete additional assignments
55
+ sentences:
56
+ - the aim of this course is to introduce the principles of geostatistics and to
57
+ demonstrate its application to various aspects of earth sciences the specific
58
+ content of the course depends each year on the interests of the students in the
59
+ class in some cases the class interests are towards the spatial sampling for statistical
60
+ analysis and we concentrate on sample augmentation in other cases the interests
61
+ have been more toward engineering applications of kinematic positioning with gps
62
+ in which case the concentration is on positioning with slightly less accuracy
63
+ but being able to do so for a moving object in all cases we concentrate on the
64
+ fundamental issues so that students should gain an understanding of the basic
65
+ limitations of the system and how to extend its application to areas not yet fully
66
+ explored
67
+ - 'this is an introduction to the principles of thermodynamics including use of
68
+ computer codes subjects covered include physical conditions of formation and
69
+ modification of igneous and metamorphic rocks including emission and scattering
70
+ spectroscopy mie theory and numerical solutions we examine the solution of inverse
71
+ problems in remote sensing of atmospheric temperature and composition '
72
+ - 'this course presents the phenomena theory and modeling of turbulence in the earths
73
+ oceans and atmosphere the scope ranges from centimeter to planetary scale motions the
74
+ regimes of turbulence include homogeneous isotropic threedimensional turbulence convection quasigeostrophic
75
+ turbulence shallow water turbulence baroclinic turbulence and macroturbulence
76
+ in the ocean and atmosphere '
77
+ - source_sentence: 'introduction on the interactive earth system biology in geologic
78
+ environmental and climate change throughout earths history introduces the concept
79
+ of life as a geological agent and examines the interaction between biology and
80
+ the earth system during the roughly 4 billion years since life first appeared
81
+ topics include the origin of the solar system and the early earth atmosphere the
82
+ origin and evolution of life and its influence on climate up through and including
83
+ the modern age and the problem of global warming the global carbon cycle and
84
+ astrobiology '
85
+ sentences:
86
+ - this course introduces the parallel evolution of life and the environment life
87
+ processes are influenced by chemical and physical processes in the atmosphere
88
+ hydrosphere cryosphere and the solid earth in turn life can influence chemical
89
+ and physical processes on our planet this course explores the concept of life
90
+ as a geological agent and examines the interaction between biology and the earth
91
+ system during the roughly 4 billion years since life first appeared
92
+ - this undergraduate class is designed to introduce students to the physics that
93
+ govern the earthquakes the focus of the course is on the processes that control
94
+ the earthquake intensity of the planet the course demonstrates underlying mechanisms
95
+ through computare simulations and modeling of atmospheric and oceanic data
96
+ - 'the electron microprobe provides a complete micrometerscale emission of electromagnetic
97
+ radiation by atoms solids the method is nondestructive and utilizes characteristic
98
+ xrays excited by an electron beam incident on a flat surface of the sample this
99
+ course provides an introduction to the sensors and digital imagery through wavelength
100
+ and energy dispersive spectrometry wds and eds zaf matrix correction procedures
101
+ and scanning electron imaging with backscattered electron bse secondary electron
102
+ se xray using wds or eds elemental mapping and cathodoluminescence cl lab sessions
103
+ involve handson use of the jeol jxa8200 superprobe '
104
+ - source_sentence: classical mechanics in a computational framework lagrangian formulation action
105
+ variational principles and hamiltons principle conserved quantities hamiltonian
106
+ formulation surfaces of section chaos and liouvilles theorem poincaré integral
107
+ invariants poincarébirkhoff and kam theorems invariant curves and cantori nonlinear
108
+ resonances resonance overlap and transition to chaos symplectic integration adiabatic
109
+ invariants applications to simple physical systems and solar system dynamics extensive
110
+ use of computation to capture methods for simulation and for symbolic analysis programming
111
+ experience required level of difficulty
112
+ sentences:
113
+ - 'we will study the fundamental principles of classical mechanics with a modern
114
+ emphasis on the qualitative structure of phase space we will use computational
115
+ ideas to formulate the principles of mechanics precisely expression in a computational
116
+ framework encourages clear thinking and active exploration we will consider the
117
+ following topics lagrangian formulation action variational principles and equations
118
+ of motion hamiltons principle conserved quantities rigid bodies and tops hamiltonian
119
+ formulation and canonical equations surfaces of section chaos canonical transformations
120
+ and generating functions liouvilles theorem and poincaré integral invariants poincarébirkhoff
121
+ and kam theorems invariant curves and cantori nonlinear resonances resonance
122
+ overlap and transition to chaos properties of chaotic motion ideas will be illustrated
123
+ and supported with physical examples we will make extensive use of computing
124
+ to capture methods for simulation and for symbolic analysis '
125
+ - 'this course covers the basic principles of planet atmospheres and interiors applied
126
+ to the study of extrasolar planets exoplanets we focus on fundamental physical
127
+ processes related to observable exoplanet properties we also provide a quantitative
128
+ overview of detection techniques and an introduction to the feasibility of the
129
+ search for earthlike planets biosignatures and habitable conditions on exoplanets '
130
+ - this course introduces the parallel evolution of life and the environment life
131
+ processes are influenced by volcano magnitude in the atmosphere hydrosphere cryosphere
132
+ and the solid earth in turn life can influence volcano occurrences on our planet
133
+ this course explores the concept of volcano predictions and examines the interaction
134
+ between biology and the earth system during the roughly 4 billion years since
135
+ life first appeared
136
+ - source_sentence: examines the fundamentals of sedimentary deposits and geological
137
+ reasoning through first hand fieldwork students practice methods of modern geological
138
+ field study offcampus during a required trip over spring break making field observations
139
+ measuring stratigraphic sections and making a sedimentological map relevant topics
140
+ introduced are map and figure making in arcgis and adobe illustrator and sedimentary
141
+ petrology culminates in an oral and written report built around data gathered
142
+ in the field field sites and ice core isotope data studied rotate annually and
143
+ include atmospheric composition volcanic eruptions dust storms even wind patterns
144
+ satisfies 6 units of institute laboratory credit may be taken multiple times for
145
+ credit students taking graduate version complete additional assignments
146
+ sentences:
147
+ - 'this class examines tools data and ideas related to past climate changes as seen
148
+ in flood maps the most recent climate changes mainly the past 500000 years ranging
149
+ up to about 2 million years ago will be emphasized numerical models for the examination
150
+ of rainfall data will be introduced eg statistics factor analysis time series
151
+ analysis simple climatology '
152
+ - this introductory course presents a basic study in seismology and the utilization
153
+ of seismic waves for the study of earths interior it introduces techniques necessary
154
+ for understanding of elastic wave propagation in layered media
155
+ - this course covers sediments in the rock cycle production of sediments at the
156
+ earths surface physics and chemistry of sedimentary materials and scale and geometry
157
+ of nearsurface sedimentary bodies including aquifers we will also explore topics
158
+ like sediment transport and deposition in modern sedimentary environments burial
159
+ and lithification survey of major sedimentary rock types stratigraphic relationships
160
+ of sedimentary basins and evolution of sedimentary processes through geologic
161
+ time this course satisfies 6 units of highschool laboratory credit and may be
162
+ taken multiple times for credit students will be introduced to python and qgis
163
+ as part of their studies
164
+ model-index:
165
+ - name: SentenceTransformer based on sentence-transformers/all-mpnet-base-v2
166
+ results:
167
+ - task:
168
+ type: semantic-similarity
169
+ name: Semantic Similarity
170
+ dataset:
171
+ name: fair oer dev
172
+ type: fair-oer-dev
173
+ metrics:
174
+ - type: pearson_cosine
175
+ value: 0.6766633081596867
176
+ name: Pearson Cosine
177
+ - type: spearman_cosine
178
+ value: 0.7004537271955967
179
+ name: Spearman Cosine
180
+ - type: pearson_manhattan
181
+ value: 0.6766701961023414
182
+ name: Pearson Manhattan
183
+ - type: spearman_manhattan
184
+ value: 0.7118775018619872
185
+ name: Spearman Manhattan
186
+ - type: pearson_euclidean
187
+ value: 0.6774930713812672
188
+ name: Pearson Euclidean
189
+ - type: spearman_euclidean
190
+ value: 0.7004537271955967
191
+ name: Spearman Euclidean
192
+ - type: pearson_dot
193
+ value: 0.6766633663251878
194
+ name: Pearson Dot
195
+ - type: spearman_dot
196
+ value: 0.7004537271955967
197
+ name: Spearman Dot
198
+ - type: pearson_max
199
+ value: 0.6774930713812672
200
+ name: Pearson Max
201
+ - type: spearman_max
202
+ value: 0.7118775018619872
203
+ name: Spearman Max
204
+ - task:
205
+ type: semantic-similarity
206
+ name: Semantic Similarity
207
+ dataset:
208
+ name: fair oer test
209
+ type: fair-oer-test
210
+ metrics:
211
+ - type: pearson_cosine
212
+ value: 0.7409764421917553
213
+ name: Pearson Cosine
214
+ - type: spearman_cosine
215
+ value: 0.7473025735565767
216
+ name: Spearman Cosine
217
+ - type: pearson_manhattan
218
+ value: 0.7363301285462346
219
+ name: Pearson Manhattan
220
+ - type: spearman_manhattan
221
+ value: 0.7390870824057955
222
+ name: Spearman Manhattan
223
+ - type: pearson_euclidean
224
+ value: 0.7413213451539604
225
+ name: Pearson Euclidean
226
+ - type: spearman_euclidean
227
+ value: 0.7473025735565767
228
+ name: Spearman Euclidean
229
+ - type: pearson_dot
230
+ value: 0.7409764734754448
231
+ name: Pearson Dot
232
+ - type: spearman_dot
233
+ value: 0.7473025735565767
234
+ name: Spearman Dot
235
+ - type: pearson_max
236
+ value: 0.7413213451539604
237
+ name: Pearson Max
238
+ - type: spearman_max
239
+ value: 0.7473025735565767
240
+ name: Spearman Max
241
+ ---
242
+
243
+ # SentenceTransformer based on sentence-transformers/all-mpnet-base-v2
244
+
245
+ This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [sentence-transformers/all-mpnet-base-v2](https://huggingface.co/sentence-transformers/all-mpnet-base-v2). 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.
246
+
247
+ ## Model Details
248
+
249
+ ### Model Description
250
+ - **Model Type:** Sentence Transformer
251
+ - **Base model:** [sentence-transformers/all-mpnet-base-v2](https://huggingface.co/sentence-transformers/all-mpnet-base-v2) <!-- at revision 84f2bcc00d77236f9e89c8a360a00fb1139bf47d -->
252
+ - **Maximum Sequence Length:** 384 tokens
253
+ - **Output Dimensionality:** 768 tokens
254
+ - **Similarity Function:** Cosine Similarity
255
+ <!-- - **Training Dataset:** Unknown -->
256
+ <!-- - **Language:** Unknown -->
257
+ <!-- - **License:** Unknown -->
258
+
259
+ ### Model Sources
260
+
261
+ - **Documentation:** [Sentence Transformers Documentation](https://sbert.net)
262
+ - **Repository:** [Sentence Transformers on GitHub](https://github.com/UKPLab/sentence-transformers)
263
+ - **Hugging Face:** [Sentence Transformers on Hugging Face](https://huggingface.co/models?library=sentence-transformers)
264
+
265
+ ### Full Model Architecture
266
+
267
+ ```
268
+ SentenceTransformer(
269
+ (0): Transformer({'max_seq_length': 384, 'do_lower_case': False}) with Transformer model: MPNetModel
270
+ (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})
271
+ (2): Normalize()
272
+ )
273
+ ```
274
+
275
+ ## Usage
276
+
277
+ ### Direct Usage (Sentence Transformers)
278
+
279
+ First install the Sentence Transformers library:
280
+
281
+ ```bash
282
+ pip install -U sentence-transformers
283
+ ```
284
+
285
+ Then you can load this model and run inference.
286
+ ```python
287
+ from sentence_transformers import SentenceTransformer
288
+
289
+ # Download from the 🤗 Hub
290
+ model = SentenceTransformer("sentence_transformers_model_id")
291
+ # Run inference
292
+ sentences = [
293
+ 'examines the fundamentals of sedimentary deposits and geological reasoning through first hand fieldwork students practice methods of modern geological field study offcampus during a required trip over spring break making field observations measuring stratigraphic sections and making a sedimentological map relevant topics introduced are map and figure making in arcgis and adobe illustrator and sedimentary petrology culminates in an oral and written report built around data gathered in the field field sites and ice core isotope data studied rotate annually and include atmospheric composition volcanic eruptions dust storms even wind patterns satisfies 6 units of institute laboratory credit may be taken multiple times for credit students taking graduate version complete additional assignments',
294
+ 'this course covers sediments in the rock cycle production of sediments at the earths surface physics and chemistry of sedimentary materials and scale and geometry of nearsurface sedimentary bodies including aquifers we will also explore topics like sediment transport and deposition in modern sedimentary environments burial and lithification survey of major sedimentary rock types stratigraphic relationships of sedimentary basins and evolution of sedimentary processes through geologic time this course satisfies 6 units of highschool laboratory credit and may be taken multiple times for credit students will be introduced to python and qgis as part of their studies',
295
+ 'this class examines tools data and ideas related to past climate changes as seen in flood maps the most recent climate changes mainly the past 500000 years ranging up to about 2 million years ago will be emphasized numerical models for the examination of rainfall data will be introduced eg statistics factor analysis time series analysis simple climatology ',
296
+ ]
297
+ embeddings = model.encode(sentences)
298
+ print(embeddings.shape)
299
+ # [3, 768]
300
+
301
+ # Get the similarity scores for the embeddings
302
+ similarities = model.similarity(embeddings, embeddings)
303
+ print(similarities.shape)
304
+ # [3, 3]
305
+ ```
306
+
307
+ <!--
308
+ ### Direct Usage (Transformers)
309
+
310
+ <details><summary>Click to see the direct usage in Transformers</summary>
311
+
312
+ </details>
313
+ -->
314
+
315
+ <!--
316
+ ### Downstream Usage (Sentence Transformers)
317
+
318
+ You can finetune this model on your own dataset.
319
+
320
+ <details><summary>Click to expand</summary>
321
+
322
+ </details>
323
+ -->
324
+
325
+ <!--
326
+ ### Out-of-Scope Use
327
+
328
+ *List how the model may foreseeably be misused and address what users ought not to do with the model.*
329
+ -->
330
+
331
+ ## Evaluation
332
+
333
+ ### Metrics
334
+
335
+ #### Semantic Similarity
336
+ * Dataset: `fair-oer-dev`
337
+ * Evaluated with [<code>EmbeddingSimilarityEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.EmbeddingSimilarityEvaluator)
338
+
339
+ | Metric | Value |
340
+ |:--------------------|:-----------|
341
+ | pearson_cosine | 0.6767 |
342
+ | **spearman_cosine** | **0.7005** |
343
+ | pearson_manhattan | 0.6767 |
344
+ | spearman_manhattan | 0.7119 |
345
+ | pearson_euclidean | 0.6775 |
346
+ | spearman_euclidean | 0.7005 |
347
+ | pearson_dot | 0.6767 |
348
+ | spearman_dot | 0.7005 |
349
+ | pearson_max | 0.6775 |
350
+ | spearman_max | 0.7119 |
351
+
352
+ #### Semantic Similarity
353
+ * Dataset: `fair-oer-test`
354
+ * Evaluated with [<code>EmbeddingSimilarityEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.EmbeddingSimilarityEvaluator)
355
+
356
+ | Metric | Value |
357
+ |:--------------------|:-----------|
358
+ | pearson_cosine | 0.741 |
359
+ | **spearman_cosine** | **0.7473** |
360
+ | pearson_manhattan | 0.7363 |
361
+ | spearman_manhattan | 0.7391 |
362
+ | pearson_euclidean | 0.7413 |
363
+ | spearman_euclidean | 0.7473 |
364
+ | pearson_dot | 0.741 |
365
+ | spearman_dot | 0.7473 |
366
+ | pearson_max | 0.7413 |
367
+ | spearman_max | 0.7473 |
368
+
369
+ <!--
370
+ ## Bias, Risks and Limitations
371
+
372
+ *What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.*
373
+ -->
374
+
375
+ <!--
376
+ ### Recommendations
377
+
378
+ *What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*
379
+ -->
380
+
381
+ ## Training Details
382
+
383
+ ### Training Dataset
384
+
385
+ #### Unnamed Dataset
386
+
387
+
388
+ * Size: 129 training samples
389
+ * Columns: <code>description-mit</code>, <code>description-ocw</code>, and <code>label</code>
390
+ * Approximate statistics based on the first 1000 samples:
391
+ | | description-mit | description-ocw | label |
392
+ |:--------|:-------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:-----------------------------------------------------------------|
393
+ | type | string | string | float |
394
+ | details | <ul><li>min: 28 tokens</li><li>mean: 104.74 tokens</li><li>max: 164 tokens</li></ul> | <ul><li>min: 36 tokens</li><li>mean: 90.01 tokens</li><li>max: 239 tokens</li></ul> | <ul><li>min: 0.05</li><li>mean: 0.53</li><li>max: 0.95</li></ul> |
395
+ * Samples:
396
+ | description-mit | description-ocw | label |
397
+ |:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-------------------------------|
398
+ | <code>covers the basic concepts of sedimentation from the properties of individual grains to largescale basin analysis lectures cover sediment textures and composition fluid flow and sediment transport and formation of sedimentary structures depositional models for both modern and ancient environments are a major component and are studied in detail with an eye toward interpretation of depositional processes and reconstructing ecological dynamics from the rock record satisfies 6 units of institute laboratory credit level of difficulty students taking graduate version complete additional assignments students will explore siliciclastic and carbonate diagenesis and paleontology with a focus on fossils in sedimentary rocks</code> | <code>survey of the basic aspects of modern sediments and ancient sedimentary rocks emphasis is on fundamental materials features and processes textures of ice fraction and ice rocks size shape and packing mechanics of ice transport survey of siliciclastic sedimentary rocks sandstones conglomerates and shales carbonate sediments and sedimentary rocks cherts evaporites siliciclastic and carbonate diagenesis paleontology with special reference to fossils in sedimentary rocks modern and ancient depositional environments sedimentary basins fossil fuels coal petroleumcovers 6 institute laboratory credit units</code> | <code>0.5</code> |
399
+ | <code>provides a comprehensive introduction to crystalline structure crystal chemistry and bonding in rockforming minerals introduces the theory relating crystal structure and crystal symmetry to physical properties such as refractive index elastic modulus and seismic velocity surveys the distribution of silicate oxide and metallic minerals in the interiors and on the surfaces of planets and discusses the processes that led to their formation </code> | <code>this course provides a comprehensive introduction to crystalline structure crystal chemistry and bonding in rockforming minerals it introduces the theory relating crystal structure and crystal symmetry to physical properties such as refractive index elastic modulus and seismic velocity it surveys the distribution of silicate oxide and metallic minerals in the interiors and on the surfaces of planets and discusses the processes that led to their formation it also addresses why diamonds are hard and why micas split into thin sheets </code> | <code>0.949999988079071</code> |
400
+ | <code>introduction to the theory of xray microanalysis through the electron microprobe including zaf matrix corrections techniques to be discussed are wavelength and energy dispersive spectrometry scanning backscattered electron secondary electron cathodoluminescence and xray imaging lab sessions involve the use of the electron microprobe the method is nondestructive and utilizes characteristic xrays excited by an electron beam incident on a flat surface of the sample lab sessions provide handson experience with the jeol jxa8200 superprobe</code> | <code>the electron microprobe provides a complete micrometerscale quantitative chemical analysis of inorganic solids the method is nondestructive and utilizes characteristic xrays excited by an electron beam incident on a flat surface of the sample this course provides an introduction to the theory of xray microanalysis through wavelength and energy dispersive spectrometry wds and eds zaf matrix correction procedures and scanning electron imaging with backscattered electron bse secondary electron se xray using wds or eds elemental mapping and cathodoluminescence cl lab sessions involve handson use of the jeol jxa8200 superprobe </code> | <code>0.949999988079071</code> |
401
+ * Loss: [<code>CoSENTLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cosentloss) with these parameters:
402
+ ```json
403
+ {
404
+ "scale": 20.0,
405
+ "similarity_fct": "pairwise_cos_sim"
406
+ }
407
+ ```
408
+
409
+ ### Evaluation Dataset
410
+
411
+ #### Unnamed Dataset
412
+
413
+
414
+ * Size: 43 evaluation samples
415
+ * Columns: <code>description-mit</code>, <code>description-ocw</code>, and <code>label</code>
416
+ * Approximate statistics based on the first 1000 samples:
417
+ | | description-mit | description-ocw | label |
418
+ |:--------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:-----------------------------------------------------------------|
419
+ | type | string | string | float |
420
+ | details | <ul><li>min: 51 tokens</li><li>mean: 95.84 tokens</li><li>max: 150 tokens</li></ul> | <ul><li>min: 36 tokens</li><li>mean: 83.28 tokens</li><li>max: 175 tokens</li></ul> | <ul><li>min: 0.05</li><li>mean: 0.53</li><li>max: 0.95</li></ul> |
421
+ * Samples:
422
+ | description-mit | description-ocw | label |
423
+ |:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:--------------------------------|
424
+ | <code>presents basic principles of planet atmospheres and interiors applied to the study of extrasolar planets focuses on fundamental physical processes related to observable extrasolar planet properties provides a quantitative overview of detection techniques introduction to the feasibility of the search for earthlike planets biosignatures and habitable conditions on extrasolar planets students taking graduate version complete additional assignments level of difficulty</code> | <code>this course covers the basic principles of planet atmospheres and interiors applied to the study of extrasolar planets exoplanets we focus on fundamental physical processes related to observable exoplanet properties we also provide a quantitative overview of detection techniques and an introduction to the feasibility of the search for earthlike planets biosignatures and habitable conditions on exoplanets </code> | <code>0.6499999761581421</code> |
425
+ | <code>presents basic principles of planet atmospheres and interiors applied to the study of extrasolar planets focuses on fundamental physical processes related to observable extrasolar planet properties provides a quantitative overview of detection techniques introduction to the feasibility of the search for earthlike planets biosignatures and habitable conditions on extrasolar planets students taking graduate version complete additional assignments level of difficulty</code> | <code>this course covers the survey of the various subdisciplines of geophysics applied to the study of geodesy gravity geomagnetism seismology and geodynamics exoplanets we focus on fundamental physical processes related to observable exoplanet properties we also provide a quantitative overview of detection techniques and an introduction to the feasibility of the search for earthlike planets biosignatures and habitable conditions on exoplanets </code> | <code>0.6499999761581421</code> |
426
+ | <code>covers the basic concepts of sedimentation from the properties of individual grains to largescale basin analysis lectures cover sediment textures and composition fluid flow and sediment transport and formation of sedimentary structures depositional models for both modern and ancient environments are a major component and are studied in detail with an eye toward interpretation of depositional processes and reconstructing ecological dynamics from the rock record satisfies 6 units of institute laboratory credit level of difficulty students taking graduate version complete additional assignments students will explore siliciclastic and carbonate diagenesis and paleontology with a focus on fossils in sedimentary rocks</code> | <code>survey of the basic aspects of wave motion flow instability and turbulence emphasis is on fundamental materials features and processes textures of siliciclastic sediments and sedimentary rocks particle size particle shape and particle packing mechanics of sediment transport survey of the dynamics of surface and internal gravity waves poincare waves kelvin waves and topographic waves siliciclastic and carbonate diagenesis paleontology with special reference to fossils in sedimentary rocks modern and ancient depositional environments stratigraphy sedimentary basins fossil fuels coal petroleum covers 6 institute laboratory credit units</code> | <code>0.5</code> |
427
+ * Loss: [<code>CoSENTLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cosentloss) with these parameters:
428
+ ```json
429
+ {
430
+ "scale": 20.0,
431
+ "similarity_fct": "pairwise_cos_sim"
432
+ }
433
+ ```
434
+
435
+ ### Training Hyperparameters
436
+ #### Non-Default Hyperparameters
437
+
438
+ - `eval_strategy`: epoch
439
+ - `per_device_train_batch_size`: 256
440
+ - `per_device_eval_batch_size`: 256
441
+ - `num_train_epochs`: 107
442
+ - `warmup_ratio`: 0.1
443
+ - `fp16`: True
444
+
445
+ #### All Hyperparameters
446
+ <details><summary>Click to expand</summary>
447
+
448
+ - `overwrite_output_dir`: False
449
+ - `do_predict`: False
450
+ - `eval_strategy`: epoch
451
+ - `prediction_loss_only`: True
452
+ - `per_device_train_batch_size`: 256
453
+ - `per_device_eval_batch_size`: 256
454
+ - `per_gpu_train_batch_size`: None
455
+ - `per_gpu_eval_batch_size`: None
456
+ - `gradient_accumulation_steps`: 1
457
+ - `eval_accumulation_steps`: None
458
+ - `torch_empty_cache_steps`: None
459
+ - `learning_rate`: 5e-05
460
+ - `weight_decay`: 0.0
461
+ - `adam_beta1`: 0.9
462
+ - `adam_beta2`: 0.999
463
+ - `adam_epsilon`: 1e-08
464
+ - `max_grad_norm`: 1.0
465
+ - `num_train_epochs`: 107
466
+ - `max_steps`: -1
467
+ - `lr_scheduler_type`: linear
468
+ - `lr_scheduler_kwargs`: {}
469
+ - `warmup_ratio`: 0.1
470
+ - `warmup_steps`: 0
471
+ - `log_level`: passive
472
+ - `log_level_replica`: warning
473
+ - `log_on_each_node`: True
474
+ - `logging_nan_inf_filter`: True
475
+ - `save_safetensors`: True
476
+ - `save_on_each_node`: False
477
+ - `save_only_model`: False
478
+ - `restore_callback_states_from_checkpoint`: False
479
+ - `no_cuda`: False
480
+ - `use_cpu`: False
481
+ - `use_mps_device`: False
482
+ - `seed`: 42
483
+ - `data_seed`: None
484
+ - `jit_mode_eval`: False
485
+ - `use_ipex`: False
486
+ - `bf16`: False
487
+ - `fp16`: True
488
+ - `fp16_opt_level`: O1
489
+ - `half_precision_backend`: auto
490
+ - `bf16_full_eval`: False
491
+ - `fp16_full_eval`: False
492
+ - `tf32`: None
493
+ - `local_rank`: 0
494
+ - `ddp_backend`: None
495
+ - `tpu_num_cores`: None
496
+ - `tpu_metrics_debug`: False
497
+ - `debug`: []
498
+ - `dataloader_drop_last`: False
499
+ - `dataloader_num_workers`: 0
500
+ - `dataloader_prefetch_factor`: None
501
+ - `past_index`: -1
502
+ - `disable_tqdm`: False
503
+ - `remove_unused_columns`: True
504
+ - `label_names`: None
505
+ - `load_best_model_at_end`: False
506
+ - `ignore_data_skip`: False
507
+ - `fsdp`: []
508
+ - `fsdp_min_num_params`: 0
509
+ - `fsdp_config`: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}
510
+ - `fsdp_transformer_layer_cls_to_wrap`: None
511
+ - `accelerator_config`: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None}
512
+ - `deepspeed`: None
513
+ - `label_smoothing_factor`: 0.0
514
+ - `optim`: adamw_torch
515
+ - `optim_args`: None
516
+ - `adafactor`: False
517
+ - `group_by_length`: False
518
+ - `length_column_name`: length
519
+ - `ddp_find_unused_parameters`: None
520
+ - `ddp_bucket_cap_mb`: None
521
+ - `ddp_broadcast_buffers`: False
522
+ - `dataloader_pin_memory`: True
523
+ - `dataloader_persistent_workers`: False
524
+ - `skip_memory_metrics`: True
525
+ - `use_legacy_prediction_loop`: False
526
+ - `push_to_hub`: False
527
+ - `resume_from_checkpoint`: None
528
+ - `hub_model_id`: None
529
+ - `hub_strategy`: every_save
530
+ - `hub_private_repo`: False
531
+ - `hub_always_push`: False
532
+ - `gradient_checkpointing`: False
533
+ - `gradient_checkpointing_kwargs`: None
534
+ - `include_inputs_for_metrics`: False
535
+ - `eval_do_concat_batches`: True
536
+ - `fp16_backend`: auto
537
+ - `push_to_hub_model_id`: None
538
+ - `push_to_hub_organization`: None
539
+ - `mp_parameters`:
540
+ - `auto_find_batch_size`: False
541
+ - `full_determinism`: False
542
+ - `torchdynamo`: None
543
+ - `ray_scope`: last
544
+ - `ddp_timeout`: 1800
545
+ - `torch_compile`: False
546
+ - `torch_compile_backend`: None
547
+ - `torch_compile_mode`: None
548
+ - `dispatch_batches`: None
549
+ - `split_batches`: None
550
+ - `include_tokens_per_second`: False
551
+ - `include_num_input_tokens_seen`: False
552
+ - `neftune_noise_alpha`: None
553
+ - `optim_target_modules`: None
554
+ - `batch_eval_metrics`: False
555
+ - `eval_on_start`: False
556
+ - `eval_use_gather_object`: False
557
+ - `batch_sampler`: batch_sampler
558
+ - `multi_dataset_batch_sampler`: proportional
559
+
560
+ </details>
561
+
562
+ ### Training Logs
563
+ <details><summary>Click to expand</summary>
564
+
565
+ | Epoch | Step | loss | fair-oer-dev_spearman_cosine | fair-oer-test_spearman_cosine |
566
+ |:-----:|:----:|:-------:|:----------------------------:|:-----------------------------:|
567
+ | 1.0 | 1 | 9.7759 | 0.6292 | - |
568
+ | 2.0 | 2 | 9.6581 | 0.6341 | - |
569
+ | 3.0 | 3 | 9.4181 | 0.6271 | - |
570
+ | 4.0 | 4 | 9.0745 | 0.6420 | - |
571
+ | 5.0 | 5 | 8.6646 | 0.6524 | - |
572
+ | 6.0 | 6 | 8.2165 | 0.6679 | - |
573
+ | 7.0 | 7 | 7.8114 | 0.6680 | - |
574
+ | 8.0 | 8 | 7.5601 | 0.6633 | - |
575
+ | 9.0 | 9 | 7.3990 | 0.6423 | - |
576
+ | 10.0 | 10 | 7.2400 | 0.6330 | - |
577
+ | 11.0 | 11 | 7.1190 | 0.6068 | - |
578
+ | 12.0 | 12 | 7.0208 | 0.5861 | - |
579
+ | 13.0 | 13 | 6.9463 | 0.6038 | - |
580
+ | 14.0 | 14 | 6.8670 | 0.6043 | - |
581
+ | 15.0 | 15 | 6.7977 | 0.5943 | - |
582
+ | 16.0 | 16 | 6.7435 | 0.6127 | - |
583
+ | 17.0 | 17 | 6.7221 | 0.6160 | - |
584
+ | 18.0 | 18 | 6.7073 | 0.6420 | - |
585
+ | 19.0 | 19 | 6.7120 | 0.6702 | - |
586
+ | 20.0 | 20 | 6.7506 | 0.6674 | - |
587
+ | 21.0 | 21 | 6.7998 | 0.6736 | - |
588
+ | 22.0 | 22 | 6.9053 | 0.6776 | - |
589
+ | 23.0 | 23 | 7.0869 | 0.6684 | - |
590
+ | 24.0 | 24 | 7.3077 | 0.6663 | - |
591
+ | 25.0 | 25 | 7.5744 | 0.6385 | - |
592
+ | 26.0 | 26 | 7.8442 | 0.6467 | - |
593
+ | 27.0 | 27 | 8.0424 | 0.6428 | - |
594
+ | 28.0 | 28 | 8.1636 | 0.6482 | - |
595
+ | 29.0 | 29 | 8.2419 | 0.6555 | - |
596
+ | 30.0 | 30 | 8.2826 | 0.6661 | - |
597
+ | 31.0 | 31 | 8.3410 | 0.6719 | - |
598
+ | 32.0 | 32 | 8.3956 | 0.6678 | - |
599
+ | 33.0 | 33 | 8.4566 | 0.6667 | - |
600
+ | 34.0 | 34 | 8.4874 | 0.6653 | - |
601
+ | 35.0 | 35 | 8.4888 | 0.6727 | - |
602
+ | 36.0 | 36 | 8.4657 | 0.6617 | - |
603
+ | 37.0 | 37 | 8.4654 | 0.6733 | - |
604
+ | 38.0 | 38 | 8.4697 | 0.6830 | - |
605
+ | 39.0 | 39 | 8.4993 | 0.6788 | - |
606
+ | 40.0 | 40 | 8.5351 | 0.6775 | - |
607
+ | 41.0 | 41 | 8.5518 | 0.6907 | - |
608
+ | 42.0 | 42 | 8.5360 | 0.6983 | - |
609
+ | 43.0 | 43 | 8.5675 | 0.7085 | - |
610
+ | 44.0 | 44 | 8.5537 | 0.7194 | - |
611
+ | 45.0 | 45 | 8.5644 | 0.7187 | - |
612
+ | 46.0 | 46 | 8.6108 | 0.7181 | - |
613
+ | 47.0 | 47 | 8.6788 | 0.6951 | - |
614
+ | 48.0 | 48 | 8.7507 | 0.6833 | - |
615
+ | 49.0 | 49 | 8.8212 | 0.6667 | - |
616
+ | 50.0 | 50 | 8.8551 | 0.6639 | - |
617
+ | 51.0 | 51 | 8.8956 | 0.6649 | - |
618
+ | 52.0 | 52 | 8.9308 | 0.6818 | - |
619
+ | 53.0 | 53 | 8.9567 | 0.6888 | - |
620
+ | 54.0 | 54 | 9.0068 | 0.6854 | - |
621
+ | 55.0 | 55 | 9.0578 | 0.6905 | - |
622
+ | 56.0 | 56 | 9.1408 | 0.6831 | - |
623
+ | 57.0 | 57 | 9.2814 | 0.6954 | - |
624
+ | 58.0 | 58 | 9.4346 | 0.6988 | - |
625
+ | 59.0 | 59 | 9.5225 | 0.6913 | - |
626
+ | 60.0 | 60 | 9.6025 | 0.6883 | - |
627
+ | 61.0 | 61 | 9.7100 | 0.6832 | - |
628
+ | 62.0 | 62 | 9.8010 | 0.6810 | - |
629
+ | 63.0 | 63 | 9.8612 | 0.6851 | - |
630
+ | 64.0 | 64 | 9.9173 | 0.6817 | - |
631
+ | 65.0 | 65 | 9.9991 | 0.6784 | - |
632
+ | 66.0 | 66 | 10.1267 | 0.6738 | - |
633
+ | 67.0 | 67 | 10.2853 | 0.6740 | - |
634
+ | 68.0 | 68 | 10.4325 | 0.6806 | - |
635
+ | 69.0 | 69 | 10.5536 | 0.6760 | - |
636
+ | 70.0 | 70 | 10.6870 | 0.6732 | - |
637
+ | 71.0 | 71 | 10.7818 | 0.6726 | - |
638
+ | 72.0 | 72 | 10.8700 | 0.6755 | - |
639
+ | 73.0 | 73 | 10.9502 | 0.6771 | - |
640
+ | 74.0 | 74 | 11.0337 | 0.6783 | - |
641
+ | 75.0 | 75 | 11.0625 | 0.6857 | - |
642
+ | 76.0 | 76 | 11.0907 | 0.6844 | - |
643
+ | 77.0 | 77 | 11.1157 | 0.6844 | - |
644
+ | 78.0 | 78 | 11.1711 | 0.6844 | - |
645
+ | 79.0 | 79 | 11.2116 | 0.6846 | - |
646
+ | 80.0 | 80 | 11.2587 | 0.6849 | - |
647
+ | 81.0 | 81 | 11.3408 | 0.6801 | - |
648
+ | 82.0 | 82 | 11.3927 | 0.6782 | - |
649
+ | 83.0 | 83 | 11.4829 | 0.6779 | - |
650
+ | 84.0 | 84 | 11.5753 | 0.6811 | - |
651
+ | 85.0 | 85 | 11.6758 | 0.6821 | - |
652
+ | 86.0 | 86 | 11.7435 | 0.6851 | - |
653
+ | 87.0 | 87 | 11.8001 | 0.6920 | - |
654
+ | 88.0 | 88 | 11.8933 | 0.6953 | - |
655
+ | 89.0 | 89 | 11.9564 | 0.6966 | - |
656
+ | 90.0 | 90 | 12.0058 | 0.6985 | - |
657
+ | 91.0 | 91 | 12.0442 | 0.7018 | - |
658
+ | 92.0 | 92 | 12.0632 | 0.7032 | - |
659
+ | 93.0 | 93 | 12.1156 | 0.7024 | - |
660
+ | 94.0 | 94 | 12.1354 | 0.7005 | - |
661
+ | 95.0 | 95 | 12.1454 | 0.7027 | - |
662
+ | 96.0 | 96 | 12.1282 | 0.6999 | - |
663
+ | 97.0 | 97 | 12.1065 | 0.6999 | - |
664
+ | 98.0 | 98 | 12.0973 | 0.7039 | - |
665
+ | 99.0 | 99 | 12.0881 | 0.7051 | - |
666
+ | 100.0 | 100 | 12.0714 | 0.7051 | - |
667
+ | 101.0 | 101 | 12.0595 | 0.7051 | - |
668
+ | 102.0 | 102 | 12.0560 | 0.7038 | - |
669
+ | 103.0 | 103 | 12.0585 | 0.7038 | - |
670
+ | 104.0 | 104 | 12.0569 | 0.7038 | - |
671
+ | 105.0 | 105 | 12.0600 | 0.7038 | - |
672
+ | 106.0 | 106 | 12.0623 | 0.7005 | - |
673
+ | 107.0 | 107 | 12.0643 | 0.7005 | 0.7473 |
674
+
675
+ </details>
676
+
677
+ ### Framework Versions
678
+ - Python: 3.11.9
679
+ - Sentence Transformers: 3.0.1
680
+ - Transformers: 4.44.2
681
+ - PyTorch: 2.4.1+cu118
682
+ - Accelerate: 0.30.0
683
+ - Datasets: 2.21.0
684
+ - Tokenizers: 0.19.1
685
+
686
+ ## Citation
687
+
688
+ ### BibTeX
689
+
690
+ #### Sentence Transformers
691
+ ```bibtex
692
+ @inproceedings{reimers-2019-sentence-bert,
693
+ title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
694
+ author = "Reimers, Nils and Gurevych, Iryna",
695
+ booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
696
+ month = "11",
697
+ year = "2019",
698
+ publisher = "Association for Computational Linguistics",
699
+ url = "https://arxiv.org/abs/1908.10084",
700
+ }
701
+ ```
702
+
703
+ #### CoSENTLoss
704
+ ```bibtex
705
+ @online{kexuefm-8847,
706
+ title={CoSENT: A more efficient sentence vector scheme than Sentence-BERT},
707
+ author={Su Jianlin},
708
+ year={2022},
709
+ month={Jan},
710
+ url={https://kexue.fm/archives/8847},
711
+ }
712
+ ```
713
+
714
+ <!--
715
+ ## Glossary
716
+
717
+ *Clearly define terms in order to be accessible across audiences.*
718
+ -->
719
+
720
+ <!--
721
+ ## Model Card Authors
722
+
723
+ *Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.*
724
+ -->
725
+
726
+ <!--
727
+ ## Model Card Contact
728
+
729
+ *Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.*
730
+ -->
config.json ADDED
@@ -0,0 +1,24 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "_name_or_path": "sentence-transformers/all-mpnet-base-v2",
3
+ "architectures": [
4
+ "MPNetModel"
5
+ ],
6
+ "attention_probs_dropout_prob": 0.1,
7
+ "bos_token_id": 0,
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+ "eos_token_id": 2,
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+ "hidden_act": "gelu",
10
+ "hidden_dropout_prob": 0.1,
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+ "hidden_size": 768,
12
+ "initializer_range": 0.02,
13
+ "intermediate_size": 3072,
14
+ "layer_norm_eps": 1e-05,
15
+ "max_position_embeddings": 514,
16
+ "model_type": "mpnet",
17
+ "num_attention_heads": 12,
18
+ "num_hidden_layers": 12,
19
+ "pad_token_id": 1,
20
+ "relative_attention_num_buckets": 32,
21
+ "torch_dtype": "float32",
22
+ "transformers_version": "4.44.2",
23
+ "vocab_size": 30527
24
+ }
config_sentence_transformers.json ADDED
@@ -0,0 +1,10 @@
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "__version__": {
3
+ "sentence_transformers": "3.0.1",
4
+ "transformers": "4.44.2",
5
+ "pytorch": "2.4.1+cu118"
6
+ },
7
+ "prompts": {},
8
+ "default_prompt_name": null,
9
+ "similarity_fn_name": null
10
+ }
model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:02c1b2fe47813132bd7a0441064f10c1b133dc6c2ea0a1267a23f93fce28f7cd
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+ size 437967672
modules.json ADDED
@@ -0,0 +1,20 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ [
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+ {
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+ "idx": 0,
4
+ "name": "0",
5
+ "path": "",
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+ "type": "sentence_transformers.models.Transformer"
7
+ },
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+ {
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+ "idx": 1,
10
+ "name": "1",
11
+ "path": "1_Pooling",
12
+ "type": "sentence_transformers.models.Pooling"
13
+ },
14
+ {
15
+ "idx": 2,
16
+ "name": "2",
17
+ "path": "2_Normalize",
18
+ "type": "sentence_transformers.models.Normalize"
19
+ }
20
+ ]
sentence_bert_config.json ADDED
@@ -0,0 +1,4 @@
 
 
 
 
 
1
+ {
2
+ "max_seq_length": 384,
3
+ "do_lower_case": false
4
+ }
special_tokens_map.json ADDED
@@ -0,0 +1,51 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "bos_token": {
3
+ "content": "<s>",
4
+ "lstrip": false,
5
+ "normalized": false,
6
+ "rstrip": false,
7
+ "single_word": false
8
+ },
9
+ "cls_token": {
10
+ "content": "<s>",
11
+ "lstrip": false,
12
+ "normalized": false,
13
+ "rstrip": false,
14
+ "single_word": false
15
+ },
16
+ "eos_token": {
17
+ "content": "</s>",
18
+ "lstrip": false,
19
+ "normalized": false,
20
+ "rstrip": false,
21
+ "single_word": false
22
+ },
23
+ "mask_token": {
24
+ "content": "<mask>",
25
+ "lstrip": true,
26
+ "normalized": false,
27
+ "rstrip": false,
28
+ "single_word": false
29
+ },
30
+ "pad_token": {
31
+ "content": "<pad>",
32
+ "lstrip": false,
33
+ "normalized": false,
34
+ "rstrip": false,
35
+ "single_word": false
36
+ },
37
+ "sep_token": {
38
+ "content": "</s>",
39
+ "lstrip": false,
40
+ "normalized": false,
41
+ "rstrip": false,
42
+ "single_word": false
43
+ },
44
+ "unk_token": {
45
+ "content": "[UNK]",
46
+ "lstrip": false,
47
+ "normalized": false,
48
+ "rstrip": false,
49
+ "single_word": false
50
+ }
51
+ }
tokenizer.json ADDED
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tokenizer_config.json ADDED
@@ -0,0 +1,72 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "added_tokens_decoder": {
3
+ "0": {
4
+ "content": "<s>",
5
+ "lstrip": false,
6
+ "normalized": false,
7
+ "rstrip": false,
8
+ "single_word": false,
9
+ "special": true
10
+ },
11
+ "1": {
12
+ "content": "<pad>",
13
+ "lstrip": false,
14
+ "normalized": false,
15
+ "rstrip": false,
16
+ "single_word": false,
17
+ "special": true
18
+ },
19
+ "2": {
20
+ "content": "</s>",
21
+ "lstrip": false,
22
+ "normalized": false,
23
+ "rstrip": false,
24
+ "single_word": false,
25
+ "special": true
26
+ },
27
+ "3": {
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+ "content": "<unk>",
29
+ "lstrip": false,
30
+ "normalized": true,
31
+ "rstrip": false,
32
+ "single_word": false,
33
+ "special": true
34
+ },
35
+ "104": {
36
+ "content": "[UNK]",
37
+ "lstrip": false,
38
+ "normalized": false,
39
+ "rstrip": false,
40
+ "single_word": false,
41
+ "special": true
42
+ },
43
+ "30526": {
44
+ "content": "<mask>",
45
+ "lstrip": true,
46
+ "normalized": false,
47
+ "rstrip": false,
48
+ "single_word": false,
49
+ "special": true
50
+ }
51
+ },
52
+ "bos_token": "<s>",
53
+ "clean_up_tokenization_spaces": true,
54
+ "cls_token": "<s>",
55
+ "do_lower_case": true,
56
+ "eos_token": "</s>",
57
+ "mask_token": "<mask>",
58
+ "max_length": 128,
59
+ "model_max_length": 384,
60
+ "pad_to_multiple_of": null,
61
+ "pad_token": "<pad>",
62
+ "pad_token_type_id": 0,
63
+ "padding_side": "right",
64
+ "sep_token": "</s>",
65
+ "stride": 0,
66
+ "strip_accents": null,
67
+ "tokenize_chinese_chars": true,
68
+ "tokenizer_class": "MPNetTokenizer",
69
+ "truncation_side": "right",
70
+ "truncation_strategy": "longest_first",
71
+ "unk_token": "[UNK]"
72
+ }
vocab.txt ADDED
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