Add new SentenceTransformer model

1_Pooling/config.json

@@ -0,0 +1,10 @@
+{
+  "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
+}

README.md

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+---
+base_model: sentence-transformers/all-mpnet-base-v2
+datasets:
+- sentence-transformers/squad
+language:
+- en
+library_name: sentence-transformers
+pipeline_tag: sentence-similarity
+tags:
+- sentence-transformers
+- sentence-similarity
+- feature-extraction
+- generated_from_trainer
+- dataset_size:87599
+- loss:MultipleNegativesRankingLoss
+widget:
+- source_sentence: What prompted transportation improvements in Portugal in the 1970's?
+  sentences:
+  - Greenhouses convert solar light to heat, enabling year-round production and the
+    growth (in enclosed environments) of specialty crops and other plants not naturally
+    suited to the local climate. Primitive greenhouses were first used during Roman
+    times to produce cucumbers year-round for the Roman emperor Tiberius. The first
+    modern greenhouses were built in Europe in the 16th century to keep exotic plants
+    brought back from explorations abroad. Greenhouses remain an important part of
+    horticulture today, and plastic transparent materials have also been used to similar
+    effect in polytunnels and row covers.
+  - By the early 1970s Portugal's fast economic growth with increasing consumption
+    and purchase of new automobiles set the priority for improvements in transportation.
+    Again in the 1990s, after joining the European Economic Community, the country
+    built many new motorways. Today, the country has a 68,732 km (42,708 mi) road
+    network, of which almost 3,000 km (1,864 mi) are part of system of 44 motorways.
+    Opened in 1944, the first motorway (which linked Lisbon to the National Stadium)
+    was an innovative project that made Portugal among one of the first countries
+    in the world to establish a motorway (this roadway eventually became the Lisbon-Cascais
+    highway, or A5). But, although a few other tracts were created (around 1960 and
+    1970), it was only after the beginning of the 1980s that large-scale motorway
+    construction was implemented. In 1972, Brisa, the highway concessionaire, was
+    founded to handle the management of many of the regions motorways. On many highways,
+    toll needs to be paid, see Via Verde. Vasco da Gama bridge is the longest bridge
+    in Europe.
+  - Kanye West began his early production career in the mid-1990s, making beats primarily
+    for burgeoning local artists, eventually developing a style that involved speeding
+    up vocal samples from classic soul records. His first official production credits
+    came at the age of nineteen when he produced eight tracks on Down to Earth, the
+    1996 debut album of a Chicago rapper named Grav. For a time, West acted as a ghost
+    producer for Deric "D-Dot" Angelettie. Because of his association with D-Dot,
+    West wasn't able to release a solo album, so he formed and became a member and
+    producer of the Go-Getters, a late-1990s Chicago rap group composed of him, GLC,
+    Timmy G, Really Doe, and Arrowstar. His group was managed by John "Monopoly" Johnson,
+    Don Crowley, and Happy Lewis under the management firm Hustle Period. After attending
+    a series of promotional photo shoots and making some radio appearances, The Go-Getters
+    released their first and only studio album World Record Holders in 1999. The album
+    featured other Chicago-based rappers such as Rhymefest, Mikkey Halsted, Miss Criss,
+    and Shayla G. Meanwhile, the production was handled by West, Arrowstar, Boogz,
+    and Brian "All Day" Miller.
+- source_sentence: What did Virchow feel Darwin's conclusions lacked?
+  sentences:
+  - 'Similar organizations in other countries followed: The American Anthropological
+    Association in 1902, the Anthropological Society of Madrid (1865), the Anthropological
+    Society of Vienna (1870), the Italian Society of Anthropology and Ethnology (1871),
+    and many others subsequently. The majority of these were evolutionist. One notable
+    exception was the Berlin Society of Anthropology (1869) founded by Rudolph Virchow,
+    known for his vituperative attacks on the evolutionists. Not religious himself,
+    he insisted that Darwin''s conclusions lacked empirical foundation.'
+  - Russian Imperialism led to the Russian Empire's conquest of Central Asia during
+    the late 19th century's Imperial Era. Between 1864 and 1885 Russia gradually took
+    control of the entire territory of Russian Turkestan, the Tajikistan portion of
+    which had been controlled by the Emirate of Bukhara and Khanate of Kokand. Russia
+    was interested in gaining access to a supply of cotton and in the 1870s attempted
+    to switch cultivation in the region from grain to cotton (a strategy later copied
+    and expanded by the Soviets).[citation needed] By 1885 Tajikistan's territory
+    was either ruled by the Russian Empire or its vassal state, the Emirate of Bukhara,
+    nevertheless Tajiks felt little Russian influence.[citation needed]
+  - A solar balloon is a black balloon that is filled with ordinary air. As sunlight
+    shines on the balloon, the air inside is heated and expands causing an upward
+    buoyancy force, much like an artificially heated hot air balloon. Some solar balloons
+    are large enough for human flight, but usage is generally limited to the toy market
+    as the surface-area to payload-weight ratio is relatively high.
+- source_sentence: What is the object of study for linguistic anthropology?
+  sentences:
+  - Anthropology of development tends to view development from a critical perspective.
+    The kind of issues addressed and implications for the approach simply involve
+    pondering why, if a key development goal is to alleviate poverty, is poverty increasing?
+    Why is there such a gap between plans and outcomes? Why are those working in development
+    so willing to disregard history and the lessons it might offer? Why is development
+    so externally driven rather than having an internal basis? In short why does so
+    much planned development fail?
+  - The study of kinship and social organization is a central focus of sociocultural
+    anthropology, as kinship is a human universal. Sociocultural anthropology also
+    covers economic and political organization, law and conflict resolution, patterns
+    of consumption and exchange, material culture, technology, infrastructure, gender
+    relations, ethnicity, childrearing and socialization, religion, myth, symbols,
+    values, etiquette, worldview, sports, music, nutrition, recreation, games, food,
+    festivals, and language (which is also the object of study in linguistic anthropology).
+  - On 1 February 1908, the king Dom Carlos I of Portugal and his heir apparent, Prince
+    Royal Dom Luís Filipe, Duke of Braganza, were murdered in Lisbon. Under his rule,
+    Portugal had twice been declared bankrupt – on 14 June 1892, and again on 10 May
+    1902 – causing social turmoil, economic disturbances, protests, revolts and criticism
+    of the monarchy. Manuel II of Portugal became the new king, but was eventually
+    overthrown by the 5 October 1910 revolution, which abolished the regime and instated
+    republicanism in Portugal. Political instability and economic weaknesses were
+    fertile ground for chaos and unrest during the Portuguese First Republic. These
+    conditions would lead to the failed Monarchy of the North, 28 May 1926 coup d'état,
+    and the creation of the National Dictatorship (Ditadura Nacional).
+- source_sentence: What is the official name of Portugal?
+  sentences:
+  - 'Portugal (Portuguese: [puɾtuˈɣaɫ]), officially the Portuguese Republic (Portuguese:
+    República Portuguesa), is a country on the Iberian Peninsula, in Southwestern
+    Europe. It is the westernmost country of mainland Europe, being bordered by the
+    Atlantic Ocean to the west and south and by Spain to the north and east. The Portugal–Spain
+    border is 1,214 km (754 mi) long and considered the longest uninterrupted border
+    within the European Union. The republic also includes the Atlantic archipelagos
+    of the Azores and Madeira, both autonomous regions with their own regional governments.'
+  - The large magnitude of solar energy available makes it a highly appealing source
+    of electricity. The United Nations Development Programme in its 2000 World Energy
+    Assessment found that the annual potential of solar energy was 1,575–49,837 exajoules
+    (EJ). This is several times larger than the total world energy consumption, which
+    was 559.8 EJ in 2012.
+  - It was temporarily under the control of the Tibetan empire and Chinese from 650–680
+    and then under the control of the Umayyads in 710. The Samanid Empire, 819 to
+    999, restored Persian control of the region and enlarged the cities of Samarkand
+    and Bukhara (both cities are today part of Uzbekistan) which became the cultural
+    centers of Iran and the region was known as Khorasan. The Kara-Khanid Khanate
+    conquered Transoxania (which corresponds approximately with modern-day Uzbekistan,
+    Tajikistan, southern Kyrgyzstan and southwest Kazakhstan) and ruled between 999–1211.
+    Their arrival in Transoxania signaled a definitive shift from Iranian to Turkic
+    predominance in Central Asia, but gradually the Kara-khanids became assimilated
+    into the Perso-Arab Muslim culture of the region.
+- source_sentence: During what years did the formation of the First Portuguese Republic
+    take place?
+  sentences:
+  - Anthrozoology (also known as "human–animal studies") is the study of interaction
+    between living things. It is a burgeoning interdisciplinary field that overlaps
+    with a number of other disciplines, including anthropology, ethology, medicine,
+    psychology, veterinary medicine and zoology. A major focus of anthrozoologic research
+    is the quantifying of the positive effects of human-animal relationships on either
+    party and the study of their interactions. It includes scholars from a diverse
+    range of fields, including anthropology, sociology, biology, and philosophy.[n
+    7]
+  - Professional anthropological bodies often object to the use of anthropology for
+    the benefit of the state. Their codes of ethics or statements may proscribe anthropologists
+    from giving secret briefings. The Association of Social Anthropologists of the
+    UK and Commonwealth (ASA) has called certain scholarship ethically dangerous.
+    The AAA's current 'Statement of Professional Responsibility' clearly states that
+    "in relation with their own government and with host governments ... no secret
+    research, no secret reports or debriefings of any kind should be agreed to or
+    given."
+  - Many Portuguese holidays, festivals and traditions have a Christian origin or
+    connotation. Although relations between the Portuguese state and the Roman Catholic
+    Church were generally amiable and stable since the earliest years of the Portuguese
+    nation, their relative power fluctuated. In the 13th and 14th centuries, the church
+    enjoyed both riches and power stemming from its role in the reconquest, its close
+    identification with early Portuguese nationalism and the foundation of the Portuguese
+    educational system, including the first university. The growth of the Portuguese
+    overseas empire made its missionaries important agents of colonization, with important
+    roles in the education and evangelization of people from all the inhabited continents.
+    The growth of liberal and nascent republican movements during the eras leading
+    to the formation of the First Portuguese Republic (1910–26) changed the role and
+    importance of organized religion.
+---
+
+# 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) on the [squad](https://huggingface.co/datasets/sentence-transformers/squad) 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.
+
+## 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 f1b1b820e405bb8644f5e8d9a3b98f9c9e0a3c58 -->
+- **Maximum Sequence Length:** 384 tokens
+- **Output Dimensionality:** 768 tokens
+- **Similarity Function:** Cosine Similarity
+- **Training Dataset:**
+    - [squad](https://huggingface.co/datasets/sentence-transformers/squad)
+- **Language:** en
+<!-- - **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("lizchu414/mpnet-base-all-nli-squad")
+# Run inference
+sentences = [
+    'During what years did the formation of the First Portuguese Republic take place?',
+    'Many Portuguese holidays, festivals and traditions have a Christian origin or connotation. Although relations between the Portuguese state and the Roman Catholic Church were generally amiable and stable since the earliest years of the Portuguese nation, their relative power fluctuated. In the 13th and 14th centuries, the church enjoyed both riches and power stemming from its role in the reconquest, its close identification with early Portuguese nationalism and the foundation of the Portuguese educational system, including the first university. The growth of the Portuguese overseas empire made its missionaries important agents of colonization, with important roles in the education and evangelization of people from all the inhabited continents. The growth of liberal and nascent republican movements during the eras leading to the formation of the First Portuguese Republic (1910–26) changed the role and importance of organized religion.',
+    'Professional anthropological bodies often object to the use of anthropology for the benefit of the state. Their codes of ethics or statements may proscribe anthropologists from giving secret briefings. The Association of Social Anthropologists of the UK and Commonwealth (ASA) has called certain scholarship ethically dangerous. The AAA\'s current \'Statement of Professional Responsibility\' clearly states that "in relation with their own government and with host governments ... no secret research, no secret reports or debriefings of any kind should be agreed to or given."',
+]
+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.*
+-->
+
+<!--
+## 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
+
+#### squad
+
+* Dataset: [squad](https://huggingface.co/datasets/sentence-transformers/squad) at [d84c8c2](https://huggingface.co/datasets/sentence-transformers/squad/tree/d84c8c2ef64693264c890bb242d2e73fc0a46c40)
+* Size: 87,599 training samples
+* Columns: <code>question</code> and <code>answer</code>
+* Approximate statistics based on the first 1000 samples:
+  |         | question                                                                          | answer                                                                              |
+  |:--------|:----------------------------------------------------------------------------------|:------------------------------------------------------------------------------------|
+  | type    | string                                                                            | string                                                                              |
+  | details | <ul><li>min: 6 tokens</li><li>mean: 14.46 tokens</li><li>max: 31 tokens</li></ul> | <ul><li>min: 34 tokens</li><li>mean: 187.2 tokens</li><li>max: 384 tokens</li></ul> |
+* Samples:
+  | question                                                                                  | answer                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               |
+  |:------------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+  | <code>To whom did the Virgin Mary allegedly appear in 1858 in Lourdes France?</code>      | <code>Architecturally, the school has a Catholic character. Atop the Main Building's gold dome is a golden statue of the Virgin Mary. Immediately in front of the Main Building and facing it, is a copper statue of Christ with arms upraised with the legend "Venite Ad Me Omnes". Next to the Main Building is the Basilica of the Sacred Heart. Immediately behind the basilica is the Grotto, a Marian place of prayer and reflection. It is a replica of the grotto at Lourdes, France where the Virgin Mary reputedly appeared to Saint Bernadette Soubirous in 1858. At the end of the main drive (and in a direct line that connects through 3 statues and the Gold Dome), is a simple, modern stone statue of Mary.</code> |
+  | <code>What is in front of the Notre Dame Main Building?</code>                            | <code>Architecturally, the school has a Catholic character. Atop the Main Building's gold dome is a golden statue of the Virgin Mary. Immediately in front of the Main Building and facing it, is a copper statue of Christ with arms upraised with the legend "Venite Ad Me Omnes". Next to the Main Building is the Basilica of the Sacred Heart. Immediately behind the basilica is the Grotto, a Marian place of prayer and reflection. It is a replica of the grotto at Lourdes, France where the Virgin Mary reputedly appeared to Saint Bernadette Soubirous in 1858. At the end of the main drive (and in a direct line that connects through 3 statues and the Gold Dome), is a simple, modern stone statue of Mary.</code> |
+  | <code>The Basilica of the Sacred heart at Notre Dame is beside to which structure?</code> | <code>Architecturally, the school has a Catholic character. Atop the Main Building's gold dome is a golden statue of the Virgin Mary. Immediately in front of the Main Building and facing it, is a copper statue of Christ with arms upraised with the legend "Venite Ad Me Omnes". Next to the Main Building is the Basilica of the Sacred Heart. Immediately behind the basilica is the Grotto, a Marian place of prayer and reflection. It is a replica of the grotto at Lourdes, France where the Virgin Mary reputedly appeared to Saint Bernadette Soubirous in 1858. At the end of the main drive (and in a direct line that connects through 3 statues and the Gold Dome), is a simple, modern stone statue of Mary.</code> |
+* Loss: [<code>MultipleNegativesRankingLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#multiplenegativesrankingloss) with these parameters:
+  ```json
+  {
+      "scale": 20.0,
+      "similarity_fct": "cos_sim"
+  }
+  ```
+
+### Evaluation Dataset
+
+#### squad
+
+* Dataset: [squad](https://huggingface.co/datasets/sentence-transformers/squad) at [d84c8c2](https://huggingface.co/datasets/sentence-transformers/squad/tree/d84c8c2ef64693264c890bb242d2e73fc0a46c40)
+* Size: 87,599 evaluation samples
+* Columns: <code>question</code> and <code>answer</code>
+* Approximate statistics based on the first 1000 samples:
+  |         | question                                                                          | answer                                                                               |
+  |:--------|:----------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|
+  | type    | string                                                                            | string                                                                               |
+  | details | <ul><li>min: 7 tokens</li><li>mean: 13.84 tokens</li><li>max: 31 tokens</li></ul> | <ul><li>min: 28 tokens</li><li>mean: 151.09 tokens</li><li>max: 368 tokens</li></ul> |
+* Samples:
+  | question                                                     | answer                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                       |
+  |:-------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+  | <code>What is one purpose of a greenhouse?</code>            | <code>Greenhouses convert solar light to heat, enabling year-round production and the growth (in enclosed environments) of specialty crops and other plants not naturally suited to the local climate. Primitive greenhouses were first used during Roman times to produce cucumbers year-round for the Roman emperor Tiberius. The first modern greenhouses were built in Europe in the 16th century to keep exotic plants brought back from explorations abroad. Greenhouses remain an important part of horticulture today, and plastic transparent materials have also been used to similar effect in polytunnels and row covers.</code> |
+  | <code>What was one of the first uses of a greenhouse?</code> | <code>Greenhouses convert solar light to heat, enabling year-round production and the growth (in enclosed environments) of specialty crops and other plants not naturally suited to the local climate. Primitive greenhouses were first used during Roman times to produce cucumbers year-round for the Roman emperor Tiberius. The first modern greenhouses were built in Europe in the 16th century to keep exotic plants brought back from explorations abroad. Greenhouses remain an important part of horticulture today, and plastic transparent materials have also been used to similar effect in polytunnels and row covers.</code> |
+  | <code>Where were the first modern greenhouses built?</code>  | <code>Greenhouses convert solar light to heat, enabling year-round production and the growth (in enclosed environments) of specialty crops and other plants not naturally suited to the local climate. Primitive greenhouses were first used during Roman times to produce cucumbers year-round for the Roman emperor Tiberius. The first modern greenhouses were built in Europe in the 16th century to keep exotic plants brought back from explorations abroad. Greenhouses remain an important part of horticulture today, and plastic transparent materials have also been used to similar effect in polytunnels and row covers.</code> |
+* Loss: [<code>MultipleNegativesRankingLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#multiplenegativesrankingloss) with these parameters:
+  ```json
+  {
+      "scale": 20.0,
+      "similarity_fct": "cos_sim"
+  }
+  ```
+
+### Training Hyperparameters
+#### Non-Default Hyperparameters
+
+- `eval_strategy`: steps
+- `per_device_train_batch_size`: 16
+- `per_device_eval_batch_size`: 16
+- `learning_rate`: 2e-05
+- `num_train_epochs`: 1
+- `warmup_ratio`: 0.1
+- `fp16`: True
+- `batch_sampler`: no_duplicates
+
+#### All Hyperparameters
+<details><summary>Click to expand</summary>
+
+- `overwrite_output_dir`: False
+- `do_predict`: False
+- `eval_strategy`: steps
+- `prediction_loss_only`: True
+- `per_device_train_batch_size`: 16
+- `per_device_eval_batch_size`: 16
+- `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`: 2e-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`: 1
+- `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
+- `use_liger_kernel`: False
+- `eval_use_gather_object`: False
+- `batch_sampler`: no_duplicates
+- `multi_dataset_batch_sampler`: proportional
+
+</details>
+
+### Framework Versions
+- Python: 3.12.7
+- Sentence Transformers: 3.2.0
+- Transformers: 4.45.2
+- PyTorch: 2.2.2+cu121
+- Accelerate: 1.0.1
+- Datasets: 3.0.1
+- Tokenizers: 0.20.1
+
+## 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",
+}
+```
+
+#### MultipleNegativesRankingLoss
+```bibtex
+@misc{henderson2017efficient,
+    title={Efficient Natural Language Response Suggestion for Smart Reply},
+    author={Matthew Henderson and Rami Al-Rfou and Brian Strope and Yun-hsuan Sung and Laszlo Lukacs and Ruiqi Guo and Sanjiv Kumar and Balint Miklos and Ray Kurzweil},
+    year={2017},
+    eprint={1705.00652},
+    archivePrefix={arXiv},
+    primaryClass={cs.CL}
+}
+```
+
+<!--
+## Glossary
+
+*Clearly define terms in order to be accessible across audiences.*
+-->
+
+<!--
+## Model Card Authors
+
+*Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.*
+-->
+
+<!--
+## Model Card Contact
+
+*Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.*
+-->

config.json

@@ -0,0 +1,24 @@
+{
+  "_name_or_path": "sentence-transformers/all-mpnet-base-v2",
+  "architectures": [
+    "MPNetModel"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "eos_token_id": 2,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 514,
+  "model_type": "mpnet",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 1,
+  "relative_attention_num_buckets": 32,
+  "torch_dtype": "float32",
+  "transformers_version": "4.45.2",
+  "vocab_size": 30527
+}

config_sentence_transformers.json

@@ -0,0 +1,10 @@
+{
+  "__version__": {
+    "sentence_transformers": "3.2.0",
+    "transformers": "4.45.2",
+    "pytorch": "2.2.2+cu121"
+  },
+  "prompts": {},
+  "default_prompt_name": null,
+  "similarity_fn_name": null
+}

model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6273560d2f240fe54342345f87d3616643ebe00f9d11f68ed9affb0c83dbe883
+size 437967672

modules.json

@@ -0,0 +1,20 @@
+[
+  {
+    "idx": 0,
+    "name": "0",
+    "path": "",
+    "type": "sentence_transformers.models.Transformer"
+  },
+  {
+    "idx": 1,
+    "name": "1",
+    "path": "1_Pooling",
+    "type": "sentence_transformers.models.Pooling"
+  },
+  {
+    "idx": 2,
+    "name": "2",
+    "path": "2_Normalize",
+    "type": "sentence_transformers.models.Normalize"
+  }
+]

sentence_bert_config.json

@@ -0,0 +1,4 @@
+{
+  "max_seq_length": 384,
+  "do_lower_case": false
+}

special_tokens_map.json

@@ -0,0 +1,51 @@
+{
+  "bos_token": {
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "cls_token": {
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "mask_token": {
+    "content": "<mask>",
+    "lstrip": true,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "<pad>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "sep_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "[UNK]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer_config.json

@@ -0,0 +1,72 @@
+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "<s>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "1": {
+      "content": "<pad>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "2": {
+      "content": "</s>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "3": {
+      "content": "<unk>",
+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "104": {
+      "content": "[UNK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "30526": {
+      "content": "<mask>",
+      "lstrip": true,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "bos_token": "<s>",
+  "clean_up_tokenization_spaces": false,
+  "cls_token": "<s>",
+  "do_lower_case": true,
+  "eos_token": "</s>",
+  "mask_token": "<mask>",
+  "max_length": 128,
+  "model_max_length": 384,
+  "pad_to_multiple_of": null,
+  "pad_token": "<pad>",
+  "pad_token_type_id": 0,
+  "padding_side": "right",
+  "sep_token": "</s>",
+  "stride": 0,
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "MPNetTokenizer",
+  "truncation_side": "right",
+  "truncation_strategy": "longest_first",
+  "unk_token": "[UNK]"
+}