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---
base_model: sentence-transformers/all-mpnet-base-v2
datasets: []
language: []
library_name: sentence-transformers
metrics:
- pearson_cosine
- spearman_cosine
- pearson_manhattan
- spearman_manhattan
- pearson_euclidean
- spearman_euclidean
- pearson_dot
- spearman_dot
- pearson_max
- spearman_max
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- feature-extraction
- generated_from_trainer
- dataset_size:129
- loss:CoSENTLoss
widget:
- source_sentence: 'traces historical and scientific advancement of our understanding
of earths cosmic context introduces basic physical principles by which planets
form and create their associated features of rings satellites diverse landscapes
atmospheres and climates includes the physics of asteroids and comets and their
orbital characteristics and links to meteorites considers one of the most fundamental
questions whether or not we are alone by detailing the scientific exploration
goals to be achieved at the moon mars and beyond '
sentences:
- 'this is an introduction to the study of the solar system with emphasis on the
latest spacecraft results the subject covers basic principles rather than detailed
mathematical and physical models topics include an overview of the solar system planetary
orbits rings planetary formation meteorites asteroids comets planetary surfaces
and cratering planetary interiors planetary atmospheres and life in the solar
system '
- 'in this course describes the largescale circulation systems of the tropical atmosphere
are used to infer the nalyses the dynamics of such systems the course includes
phase equilibria of homogeneous and heterogeneous systems and thermodynamic modeling
of nonideal crystalline solutions it also surveys the processes that lead to
the formation of metamorphic and igneous rocks in the major tectonic environments
in the earths crust and mantle '
- this introductory course presents a basic study in oceanography and the utilization
of seismic waves for the study of ocean it introduces techniques necessary for
understanding of elastic wave propagation in layered media
- source_sentence: introduction to the physics of atmospheric radiation remote sensing
and convection including use of computer codes risotopic contents occurrence
in modern organisms and environments diagenetic pathways analytical techniques physics
of dry and moist convection including moist thermodynamics radiativeconvective
equilibrium solution of inverse problems in remote sensing of atmospheric temperature
and composition students taking the graduate version complete additional assignments
sentences:
- the aim of this course is to introduce the principles of geostatistics and to
demonstrate its application to various aspects of earth sciences the specific
content of the course depends each year on the interests of the students in the
class in some cases the class interests are towards the spatial sampling for statistical
analysis and we concentrate on sample augmentation in other cases the interests
have been more toward engineering applications of kinematic positioning with gps
in which case the concentration is on positioning with slightly less accuracy
but being able to do so for a moving object in all cases we concentrate on the
fundamental issues so that students should gain an understanding of the basic
limitations of the system and how to extend its application to areas not yet fully
explored
- 'this is an introduction to the principles of thermodynamics including use of
computer codes subjects covered include physical conditions of formation and
modification of igneous and metamorphic rocks including emission and scattering
spectroscopy mie theory and numerical solutions we examine the solution of inverse
problems in remote sensing of atmospheric temperature and composition '
- 'this course presents the phenomena theory and modeling of turbulence in the earths
oceans and atmosphere the scope ranges from centimeter to planetary scale motions the
regimes of turbulence include homogeneous isotropic threedimensional turbulence convection quasigeostrophic
turbulence shallow water turbulence baroclinic turbulence and macroturbulence
in the ocean and atmosphere '
- source_sentence: 'introduction on the interactive earth system biology in geologic
environmental and climate change throughout earths history introduces the concept
of life as a geological agent and examines the interaction between biology and
the earth system during the roughly 4 billion years since life first appeared
topics include the origin of the solar system and the early earth atmosphere the
origin and evolution of life and its influence on climate up through and including
the modern age and the problem of global warming the global carbon cycle and
astrobiology '
sentences:
- this course introduces the parallel evolution of life and the environment life
processes are influenced by chemical and physical processes in the atmosphere
hydrosphere cryosphere and the solid earth in turn life can influence chemical
and physical processes on our planet this course explores the concept of life
as a geological agent and examines the interaction between biology and the earth
system during the roughly 4 billion years since life first appeared
- this undergraduate class is designed to introduce students to the physics that
govern the earthquakes the focus of the course is on the processes that control
the earthquake intensity of the planet the course demonstrates underlying mechanisms
through computare simulations and modeling of atmospheric and oceanic data
- 'the electron microprobe provides a complete micrometerscale emission of electromagnetic
radiation by atoms 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 sensors and digital imagery 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 '
- source_sentence: classical mechanics in a computational framework lagrangian formulation action
variational principles and hamiltons principle conserved quantities hamiltonian
formulation surfaces of section chaos and liouvilles theorem poincaré integral
invariants poincarébirkhoff and kam theorems invariant curves and cantori nonlinear
resonances resonance overlap and transition to chaos symplectic integration adiabatic
invariants applications to simple physical systems and solar system dynamics extensive
use of computation to capture methods for simulation and for symbolic analysis programming
experience required level of difficulty
sentences:
- 'we will study the fundamental principles of classical mechanics with a modern
emphasis on the qualitative structure of phase space we will use computational
ideas to formulate the principles of mechanics precisely expression in a computational
framework encourages clear thinking and active exploration we will consider the
following topics lagrangian formulation action variational principles and equations
of motion hamiltons principle conserved quantities rigid bodies and tops hamiltonian
formulation and canonical equations surfaces of section chaos canonical transformations
and generating functions liouvilles theorem and poincaré integral invariants poincarébirkhoff
and kam theorems invariant curves and cantori nonlinear resonances resonance
overlap and transition to chaos properties of chaotic motion ideas will be illustrated
and supported with physical examples we will make extensive use of computing
to capture methods for simulation and for symbolic analysis '
- '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 '
- this course introduces the parallel evolution of life and the environment life
processes are influenced by volcano magnitude in the atmosphere hydrosphere cryosphere
and the solid earth in turn life can influence volcano occurrences on our planet
this course explores the concept of volcano predictions and examines the interaction
between biology and the earth system during the roughly 4 billion years since
life first appeared
- source_sentence: 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
sentences:
- '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 '
- this introductory course presents a basic study in seismology and the utilization
of seismic waves for the study of earths interior it introduces techniques necessary
for understanding of elastic wave propagation in layered media
- 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
model-index:
- name: SentenceTransformer based on sentence-transformers/all-mpnet-base-v2
results:
- task:
type: semantic-similarity
name: Semantic Similarity
dataset:
name: fair oer dev
type: fair-oer-dev
metrics:
- type: pearson_cosine
value: 0.6766633081596867
name: Pearson Cosine
- type: spearman_cosine
value: 0.7004537271955967
name: Spearman Cosine
- type: pearson_manhattan
value: 0.6766701961023414
name: Pearson Manhattan
- type: spearman_manhattan
value: 0.7118775018619872
name: Spearman Manhattan
- type: pearson_euclidean
value: 0.6774930713812672
name: Pearson Euclidean
- type: spearman_euclidean
value: 0.7004537271955967
name: Spearman Euclidean
- type: pearson_dot
value: 0.6766633663251878
name: Pearson Dot
- type: spearman_dot
value: 0.7004537271955967
name: Spearman Dot
- type: pearson_max
value: 0.6774930713812672
name: Pearson Max
- type: spearman_max
value: 0.7118775018619872
name: Spearman Max
- task:
type: semantic-similarity
name: Semantic Similarity
dataset:
name: fair oer test
type: fair-oer-test
metrics:
- type: pearson_cosine
value: 0.7409764421917553
name: Pearson Cosine
- type: spearman_cosine
value: 0.7473025735565767
name: Spearman Cosine
- type: pearson_manhattan
value: 0.7363301285462346
name: Pearson Manhattan
- type: spearman_manhattan
value: 0.7390870824057955
name: Spearman Manhattan
- type: pearson_euclidean
value: 0.7413213451539604
name: Pearson Euclidean
- type: spearman_euclidean
value: 0.7473025735565767
name: Spearman Euclidean
- type: pearson_dot
value: 0.7409764734754448
name: Pearson Dot
- type: spearman_dot
value: 0.7473025735565767
name: Spearman Dot
- type: pearson_max
value: 0.7413213451539604
name: Pearson Max
- type: spearman_max
value: 0.7473025735565767
name: Spearman Max
---
# SentenceTransformer based on sentence-transformers/all-mpnet-base-v2
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.
## Model Details
### Model Description
- **Model Type:** Sentence Transformer
- **Base model:** [sentence-transformers/all-mpnet-base-v2](https://huggingface.co/sentence-transformers/all-mpnet-base-v2) <!-- at revision 84f2bcc00d77236f9e89c8a360a00fb1139bf47d -->
- **Maximum Sequence Length:** 384 tokens
- **Output Dimensionality:** 768 tokens
- **Similarity Function:** Cosine Similarity
<!-- - **Training Dataset:** Unknown -->
<!-- - **Language:** Unknown -->
<!-- - **License:** Unknown -->
### Model Sources
- **Documentation:** [Sentence Transformers Documentation](https://sbert.net)
- **Repository:** [Sentence Transformers on GitHub](https://github.com/UKPLab/sentence-transformers)
- **Hugging Face:** [Sentence Transformers on Hugging Face](https://huggingface.co/models?library=sentence-transformers)
### Full Model Architecture
```
SentenceTransformer(
(0): Transformer({'max_seq_length': 384, 'do_lower_case': False}) with Transformer model: MPNetModel
(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})
(2): Normalize()
)
```
## Usage
### Direct Usage (Sentence Transformers)
First install the Sentence Transformers library:
```bash
pip install -U sentence-transformers
```
Then you can load this model and run inference.
```python
from sentence_transformers import SentenceTransformer
# Download from the 🤗 Hub
model = SentenceTransformer("sentence_transformers_model_id")
# Run inference
sentences = [
'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',
'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',
'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 ',
]
embeddings = model.encode(sentences)
print(embeddings.shape)
# [3, 768]
# Get the similarity scores for the embeddings
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [3, 3]
```
<!--
### Direct Usage (Transformers)
<details><summary>Click to see the direct usage in Transformers</summary>
</details>
-->
<!--
### Downstream Usage (Sentence Transformers)
You can finetune this model on your own dataset.
<details><summary>Click to expand</summary>
</details>
-->
<!--
### Out-of-Scope Use
*List how the model may foreseeably be misused and address what users ought not to do with the model.*
-->
## Evaluation
### Metrics
#### Semantic Similarity
* Dataset: `fair-oer-dev`
* Evaluated with [<code>EmbeddingSimilarityEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.EmbeddingSimilarityEvaluator)
| Metric | Value |
|:--------------------|:-----------|
| pearson_cosine | 0.6767 |
| **spearman_cosine** | **0.7005** |
| pearson_manhattan | 0.6767 |
| spearman_manhattan | 0.7119 |
| pearson_euclidean | 0.6775 |
| spearman_euclidean | 0.7005 |
| pearson_dot | 0.6767 |
| spearman_dot | 0.7005 |
| pearson_max | 0.6775 |
| spearman_max | 0.7119 |
#### Semantic Similarity
* Dataset: `fair-oer-test`
* Evaluated with [<code>EmbeddingSimilarityEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.EmbeddingSimilarityEvaluator)
| Metric | Value |
|:--------------------|:-----------|
| pearson_cosine | 0.741 |
| **spearman_cosine** | **0.7473** |
| pearson_manhattan | 0.7363 |
| spearman_manhattan | 0.7391 |
| pearson_euclidean | 0.7413 |
| spearman_euclidean | 0.7473 |
| pearson_dot | 0.741 |
| spearman_dot | 0.7473 |
| pearson_max | 0.7413 |
| spearman_max | 0.7473 |
<!--
## Bias, Risks and Limitations
*What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.*
-->
<!--
### Recommendations
*What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*
-->
## Training Details
### Training Dataset
#### Unnamed Dataset
* Size: 129 training samples
* Columns: <code>description-mit</code>, <code>description-ocw</code>, and <code>label</code>
* Approximate statistics based on the first 1000 samples:
| | description-mit | description-ocw | label |
|:--------|:-------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:-----------------------------------------------------------------|
| type | string | string | float |
| 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> |
* Samples:
| description-mit | description-ocw | label |
|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-------------------------------|
| <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> |
| <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> |
| <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> |
* Loss: [<code>CoSENTLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cosentloss) with these parameters:
```json
{
"scale": 20.0,
"similarity_fct": "pairwise_cos_sim"
}
```
### Evaluation Dataset
#### Unnamed Dataset
* Size: 43 evaluation samples
* Columns: <code>description-mit</code>, <code>description-ocw</code>, and <code>label</code>
* Approximate statistics based on the first 1000 samples:
| | description-mit | description-ocw | label |
|:--------|:------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|:-----------------------------------------------------------------|
| type | string | string | float |
| 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> |
* Samples:
| description-mit | description-ocw | label |
|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:--------------------------------|
| <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> |
| <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> |
| <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> |
* Loss: [<code>CoSENTLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cosentloss) with these parameters:
```json
{
"scale": 20.0,
"similarity_fct": "pairwise_cos_sim"
}
```
### Training Hyperparameters
#### Non-Default Hyperparameters
- `eval_strategy`: epoch
- `per_device_train_batch_size`: 256
- `per_device_eval_batch_size`: 256
- `num_train_epochs`: 107
- `warmup_ratio`: 0.1
- `fp16`: True
#### All Hyperparameters
<details><summary>Click to expand</summary>
- `overwrite_output_dir`: False
- `do_predict`: False
- `eval_strategy`: epoch
- `prediction_loss_only`: True
- `per_device_train_batch_size`: 256
- `per_device_eval_batch_size`: 256
- `per_gpu_train_batch_size`: None
- `per_gpu_eval_batch_size`: None
- `gradient_accumulation_steps`: 1
- `eval_accumulation_steps`: None
- `torch_empty_cache_steps`: None
- `learning_rate`: 5e-05
- `weight_decay`: 0.0
- `adam_beta1`: 0.9
- `adam_beta2`: 0.999
- `adam_epsilon`: 1e-08
- `max_grad_norm`: 1.0
- `num_train_epochs`: 107
- `max_steps`: -1
- `lr_scheduler_type`: linear
- `lr_scheduler_kwargs`: {}
- `warmup_ratio`: 0.1
- `warmup_steps`: 0
- `log_level`: passive
- `log_level_replica`: warning
- `log_on_each_node`: True
- `logging_nan_inf_filter`: True
- `save_safetensors`: True
- `save_on_each_node`: False
- `save_only_model`: False
- `restore_callback_states_from_checkpoint`: False
- `no_cuda`: False
- `use_cpu`: False
- `use_mps_device`: False
- `seed`: 42
- `data_seed`: None
- `jit_mode_eval`: False
- `use_ipex`: False
- `bf16`: False
- `fp16`: True
- `fp16_opt_level`: O1
- `half_precision_backend`: auto
- `bf16_full_eval`: False
- `fp16_full_eval`: False
- `tf32`: None
- `local_rank`: 0
- `ddp_backend`: None
- `tpu_num_cores`: None
- `tpu_metrics_debug`: False
- `debug`: []
- `dataloader_drop_last`: False
- `dataloader_num_workers`: 0
- `dataloader_prefetch_factor`: None
- `past_index`: -1
- `disable_tqdm`: False
- `remove_unused_columns`: True
- `label_names`: None
- `load_best_model_at_end`: False
- `ignore_data_skip`: False
- `fsdp`: []
- `fsdp_min_num_params`: 0
- `fsdp_config`: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}
- `fsdp_transformer_layer_cls_to_wrap`: None
- `accelerator_config`: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None}
- `deepspeed`: None
- `label_smoothing_factor`: 0.0
- `optim`: adamw_torch
- `optim_args`: None
- `adafactor`: False
- `group_by_length`: False
- `length_column_name`: length
- `ddp_find_unused_parameters`: None
- `ddp_bucket_cap_mb`: None
- `ddp_broadcast_buffers`: False
- `dataloader_pin_memory`: True
- `dataloader_persistent_workers`: False
- `skip_memory_metrics`: True
- `use_legacy_prediction_loop`: False
- `push_to_hub`: False
- `resume_from_checkpoint`: None
- `hub_model_id`: None
- `hub_strategy`: every_save
- `hub_private_repo`: False
- `hub_always_push`: False
- `gradient_checkpointing`: False
- `gradient_checkpointing_kwargs`: None
- `include_inputs_for_metrics`: False
- `eval_do_concat_batches`: True
- `fp16_backend`: auto
- `push_to_hub_model_id`: None
- `push_to_hub_organization`: None
- `mp_parameters`:
- `auto_find_batch_size`: False
- `full_determinism`: False
- `torchdynamo`: None
- `ray_scope`: last
- `ddp_timeout`: 1800
- `torch_compile`: False
- `torch_compile_backend`: None
- `torch_compile_mode`: None
- `dispatch_batches`: None
- `split_batches`: None
- `include_tokens_per_second`: False
- `include_num_input_tokens_seen`: False
- `neftune_noise_alpha`: None
- `optim_target_modules`: None
- `batch_eval_metrics`: False
- `eval_on_start`: False
- `eval_use_gather_object`: False
- `batch_sampler`: batch_sampler
- `multi_dataset_batch_sampler`: proportional
</details>
### Training Logs
<details><summary>Click to expand</summary>
| Epoch | Step | loss | fair-oer-dev_spearman_cosine | fair-oer-test_spearman_cosine |
|:-----:|:----:|:-------:|:----------------------------:|:-----------------------------:|
| 1.0 | 1 | 9.7759 | 0.6292 | - |
| 2.0 | 2 | 9.6581 | 0.6341 | - |
| 3.0 | 3 | 9.4181 | 0.6271 | - |
| 4.0 | 4 | 9.0745 | 0.6420 | - |
| 5.0 | 5 | 8.6646 | 0.6524 | - |
| 6.0 | 6 | 8.2165 | 0.6679 | - |
| 7.0 | 7 | 7.8114 | 0.6680 | - |
| 8.0 | 8 | 7.5601 | 0.6633 | - |
| 9.0 | 9 | 7.3990 | 0.6423 | - |
| 10.0 | 10 | 7.2400 | 0.6330 | - |
| 11.0 | 11 | 7.1190 | 0.6068 | - |
| 12.0 | 12 | 7.0208 | 0.5861 | - |
| 13.0 | 13 | 6.9463 | 0.6038 | - |
| 14.0 | 14 | 6.8670 | 0.6043 | - |
| 15.0 | 15 | 6.7977 | 0.5943 | - |
| 16.0 | 16 | 6.7435 | 0.6127 | - |
| 17.0 | 17 | 6.7221 | 0.6160 | - |
| 18.0 | 18 | 6.7073 | 0.6420 | - |
| 19.0 | 19 | 6.7120 | 0.6702 | - |
| 20.0 | 20 | 6.7506 | 0.6674 | - |
| 21.0 | 21 | 6.7998 | 0.6736 | - |
| 22.0 | 22 | 6.9053 | 0.6776 | - |
| 23.0 | 23 | 7.0869 | 0.6684 | - |
| 24.0 | 24 | 7.3077 | 0.6663 | - |
| 25.0 | 25 | 7.5744 | 0.6385 | - |
| 26.0 | 26 | 7.8442 | 0.6467 | - |
| 27.0 | 27 | 8.0424 | 0.6428 | - |
| 28.0 | 28 | 8.1636 | 0.6482 | - |
| 29.0 | 29 | 8.2419 | 0.6555 | - |
| 30.0 | 30 | 8.2826 | 0.6661 | - |
| 31.0 | 31 | 8.3410 | 0.6719 | - |
| 32.0 | 32 | 8.3956 | 0.6678 | - |
| 33.0 | 33 | 8.4566 | 0.6667 | - |
| 34.0 | 34 | 8.4874 | 0.6653 | - |
| 35.0 | 35 | 8.4888 | 0.6727 | - |
| 36.0 | 36 | 8.4657 | 0.6617 | - |
| 37.0 | 37 | 8.4654 | 0.6733 | - |
| 38.0 | 38 | 8.4697 | 0.6830 | - |
| 39.0 | 39 | 8.4993 | 0.6788 | - |
| 40.0 | 40 | 8.5351 | 0.6775 | - |
| 41.0 | 41 | 8.5518 | 0.6907 | - |
| 42.0 | 42 | 8.5360 | 0.6983 | - |
| 43.0 | 43 | 8.5675 | 0.7085 | - |
| 44.0 | 44 | 8.5537 | 0.7194 | - |
| 45.0 | 45 | 8.5644 | 0.7187 | - |
| 46.0 | 46 | 8.6108 | 0.7181 | - |
| 47.0 | 47 | 8.6788 | 0.6951 | - |
| 48.0 | 48 | 8.7507 | 0.6833 | - |
| 49.0 | 49 | 8.8212 | 0.6667 | - |
| 50.0 | 50 | 8.8551 | 0.6639 | - |
| 51.0 | 51 | 8.8956 | 0.6649 | - |
| 52.0 | 52 | 8.9308 | 0.6818 | - |
| 53.0 | 53 | 8.9567 | 0.6888 | - |
| 54.0 | 54 | 9.0068 | 0.6854 | - |
| 55.0 | 55 | 9.0578 | 0.6905 | - |
| 56.0 | 56 | 9.1408 | 0.6831 | - |
| 57.0 | 57 | 9.2814 | 0.6954 | - |
| 58.0 | 58 | 9.4346 | 0.6988 | - |
| 59.0 | 59 | 9.5225 | 0.6913 | - |
| 60.0 | 60 | 9.6025 | 0.6883 | - |
| 61.0 | 61 | 9.7100 | 0.6832 | - |
| 62.0 | 62 | 9.8010 | 0.6810 | - |
| 63.0 | 63 | 9.8612 | 0.6851 | - |
| 64.0 | 64 | 9.9173 | 0.6817 | - |
| 65.0 | 65 | 9.9991 | 0.6784 | - |
| 66.0 | 66 | 10.1267 | 0.6738 | - |
| 67.0 | 67 | 10.2853 | 0.6740 | - |
| 68.0 | 68 | 10.4325 | 0.6806 | - |
| 69.0 | 69 | 10.5536 | 0.6760 | - |
| 70.0 | 70 | 10.6870 | 0.6732 | - |
| 71.0 | 71 | 10.7818 | 0.6726 | - |
| 72.0 | 72 | 10.8700 | 0.6755 | - |
| 73.0 | 73 | 10.9502 | 0.6771 | - |
| 74.0 | 74 | 11.0337 | 0.6783 | - |
| 75.0 | 75 | 11.0625 | 0.6857 | - |
| 76.0 | 76 | 11.0907 | 0.6844 | - |
| 77.0 | 77 | 11.1157 | 0.6844 | - |
| 78.0 | 78 | 11.1711 | 0.6844 | - |
| 79.0 | 79 | 11.2116 | 0.6846 | - |
| 80.0 | 80 | 11.2587 | 0.6849 | - |
| 81.0 | 81 | 11.3408 | 0.6801 | - |
| 82.0 | 82 | 11.3927 | 0.6782 | - |
| 83.0 | 83 | 11.4829 | 0.6779 | - |
| 84.0 | 84 | 11.5753 | 0.6811 | - |
| 85.0 | 85 | 11.6758 | 0.6821 | - |
| 86.0 | 86 | 11.7435 | 0.6851 | - |
| 87.0 | 87 | 11.8001 | 0.6920 | - |
| 88.0 | 88 | 11.8933 | 0.6953 | - |
| 89.0 | 89 | 11.9564 | 0.6966 | - |
| 90.0 | 90 | 12.0058 | 0.6985 | - |
| 91.0 | 91 | 12.0442 | 0.7018 | - |
| 92.0 | 92 | 12.0632 | 0.7032 | - |
| 93.0 | 93 | 12.1156 | 0.7024 | - |
| 94.0 | 94 | 12.1354 | 0.7005 | - |
| 95.0 | 95 | 12.1454 | 0.7027 | - |
| 96.0 | 96 | 12.1282 | 0.6999 | - |
| 97.0 | 97 | 12.1065 | 0.6999 | - |
| 98.0 | 98 | 12.0973 | 0.7039 | - |
| 99.0 | 99 | 12.0881 | 0.7051 | - |
| 100.0 | 100 | 12.0714 | 0.7051 | - |
| 101.0 | 101 | 12.0595 | 0.7051 | - |
| 102.0 | 102 | 12.0560 | 0.7038 | - |
| 103.0 | 103 | 12.0585 | 0.7038 | - |
| 104.0 | 104 | 12.0569 | 0.7038 | - |
| 105.0 | 105 | 12.0600 | 0.7038 | - |
| 106.0 | 106 | 12.0623 | 0.7005 | - |
| 107.0 | 107 | 12.0643 | 0.7005 | 0.7473 |
</details>
### Framework Versions
- Python: 3.11.9
- Sentence Transformers: 3.0.1
- Transformers: 4.44.2
- PyTorch: 2.4.1+cu118
- Accelerate: 0.30.0
- Datasets: 2.21.0
- Tokenizers: 0.19.1
## Citation
### BibTeX
#### Sentence Transformers
```bibtex
@inproceedings{reimers-2019-sentence-bert,
title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
author = "Reimers, Nils and Gurevych, Iryna",
booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
month = "11",
year = "2019",
publisher = "Association for Computational Linguistics",
url = "https://arxiv.org/abs/1908.10084",
}
```
#### CoSENTLoss
```bibtex
@online{kexuefm-8847,
title={CoSENT: A more efficient sentence vector scheme than Sentence-BERT},
author={Su Jianlin},
year={2022},
month={Jan},
url={https://kexue.fm/archives/8847},
}
```
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