sentence-transformers safetensors xlm-roberta sentence-similarity feature-extraction generated_from_trainer dataset_size:16964 loss:TripletLoss arxiv:1908.10084 arxiv:1703.07737 base_model:sentence-transformers/paraphrase-multilingual-mpnet-base-v2 base_model:finetune:sentence-transformers/paraphrase-multilingual-mpnet-base-v2 autotrain_compatible text-embeddings-inference endpoints_compatible region:us
---
base_model: sentence-transformers/paraphrase-multilingual-mpnet-base-v2
library_name: sentence-transformers
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- feature-extraction
- generated_from_trainer
- dataset_size:16964
- loss:TripletLoss
widget:
- source_sentence: <s>पe र</s><s></s>
  sentences:
  - Individuals or entities that engage in unethical or illegal activities for personal
    gain, prioritizing profit or power over ethics. This includes corrupt politicians,
    business leaders, and officials.
  - Entities causing harm through ignorance, lack of skill, or incompetence. This
    includes people committing foolish acts or making poor decisions due to lack of
    understanding or expertise. Their actions, often unintentional, result in significant
    negative consequences.
  - Those involved in plots and secret plans, often working behind the scenes to undermine
    or deceive others. They engage in covert activities to achieve their goals.
- source_sentence: <s>the entity has been involved in several incidents and Events
    that demonstrate its Role in conflict initiation the russian plane Was carrying
    ukrainian prisoner When it crashed highlighting the ongoing tension between russia
    and ukraine thi incident is part of larger Context Where russia has been Accused
    of provoking Violence and unrest through its actiom</s><s></s><s>anger</s><s>disgust</s><s>fear</s>
  sentences:
  - 'People cast as victims due to circumstances beyond their control, specifically
    in two categories: (1) victims of physical harm, including natural disasters,
    acts of war, terrorism, mugging, physical assault, ... etc., and (2) victims of
    economic harm, such as sanctions, blockades, and boycotts. Their experiences evoke
    sympathy and calls for justice, focusing on either physical or economic suffering.'
  - Marginalized or overlooked groups who are often ignored by society and do not
    receive the attention or support they need. This includes refugees, who face systemic
    neglect and exclusion.
  - Heroes or guardians who protect values or communities, ensuring safety and upholding
    justice. They often take on roles such as law enforcement officers, soldiers,
    or community leaders
- source_sentence: <s>herir is the refined Context related to the entity russian russian
    diplomat have been Accused of being directly responsible hostile activitie Against
    poland and its allie they werir ordered to leave the country by november and are
    considered persona non gratar in poland thi move follow allegatiom that Russia
    was involved in plots and secret plans to undermine poland security With intelligence
    Suggesting that they werir Behind recent suspicious activitie the diplomat actions
    have been seen provocation and their presence in poland is longer tolerated</s><s></s><s>anger</s><s>disgust</s><s>fear</s>
  sentences:
  - Heroes or guardians who protect values or communities, ensuring safety and upholding
    justice. They often take on roles such as law enforcement officers, soldiers,
    or community leaders
  - Spies or double agents accused of espionage, gathering and transmitting sensitive
    information to a rival or enemy. They operate in secrecy and deception. This is
    mostly in politics, not in CC.
  - Terrorists, mercenaries, insurgents, fanatics, or extremists engaging in violence
    and terror to further ideological ends, often targeting civilians. They are viewed
    as significant threats to peace and security. This is mostly in politics, not
    in CC.
- source_sentence: <s>Immanuel Macron the president of france is involved in diplomatic
    effort to facilitate peace talks between ukraine and russia he has been scheduled
    to Meet With ukrainian president volodymyr zelenskyy after his Meeting With britain
    prime minister rishi sunak and nato jem Stoltenberg Where they discussed the potential
    Ceasefire and the lifting of western sanctiom on Russia thi indicate that Macron
    is Playing key role in mediating the conflict Which aligns with the definition
    of an individuals or groups initiating conflict he is involved in plots to initiate
    peace talks to end the ongoing War</s><s></s><s>anticipation</s><s>optimism</s>
  sentences:
  - Individuals portrayed as virtuous, righteous, or noble, who are seen as fair,
    just, and upholding high moral standards. They are often role models and figures
    of integrity.
  - Individuals portrayed as virtuous, righteous, or noble, who are seen as fair,
    just, and upholding high moral standards. They are often role models and figures
    of integrity.
  - Martyrs or saviors who sacrifice their well-being, or even their lives, for a
    greater good or cause. These individuals are often celebrated for their selflessness
    and dedication. This is mostly in politics, not in CC.
- source_sentence: <s>herir is the refined Context related to the entity russia after
    analyzing its actions and involvement in the Given Article rusia Violated international
    law by invading ukraine disregarding the principle of sovereignty and territorial
    integrity enshrined in the un charter thi aggression has led to prolonged conflict
    that cannot be resolved through negotiations or diplomacy Alone Russia actions
    have been characterized aggression Violence and exploitation by ukrainian president
    volodymyr zelensky Who has called global action to force russia to comply with
    the un charter thi context Aligns with the role definition of individuals or groups
    initiating conflict often seen the primaryr Cause of tension and discord</s><s></s><s>anger</s><s>disgust</s>
  sentences:
  - Entities from other nations or regions creating geopolitical tension and acting
    against the interests of another country. They are often depicted as threats to
    national security. This is mostly in politics, not in CC.
  - Entities who are considered unlikely to succeed due to their disadvantaged position
    but strive against greater forces and obstacles. Their stories often inspire others.
  - ': Individuals or groups initiating conflict, often seen as the primary cause
    of tension and discord. They may provoke violence or unrest.'
---

# SentenceTransformer based on sentence-transformers/paraphrase-multilingual-mpnet-base-v2

This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [sentence-transformers/paraphrase-multilingual-mpnet-base-v2](https://huggingface.co/sentence-transformers/paraphrase-multilingual-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/paraphrase-multilingual-mpnet-base-v2](https://huggingface.co/sentence-transformers/paraphrase-multilingual-mpnet-base-v2) <!-- at revision 75c57757a97f90ad739aca51fa8bfea0e485a7f2 -->
- **Maximum Sequence Length:** 512 tokens
- **Output Dimensionality:** 768 dimensions
- **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': 512, 'do_lower_case': False}) with Transformer model: XLMRobertaModel 
  (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})
)
```

## 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 = [
    '<s>herir is the refined Context related to the entity russia after analyzing its actions and involvement in the Given Article rusia Violated international law by invading ukraine disregarding the principle of sovereignty and territorial integrity enshrined in the un charter thi aggression has led to prolonged conflict that cannot be resolved through negotiations or diplomacy Alone Russia actions have been characterized aggression Violence and exploitation by ukrainian president volodymyr zelensky Who has called global action to force russia to comply with the un charter thi context Aligns with the role definition of individuals or groups initiating conflict often seen the primaryr Cause of tension and discord</s><s></s><s>anger</s><s>disgust</s>',
    'Entities from other nations or regions creating geopolitical tension and acting against the interests of another country. They are often depicted as threats to national security. This is mostly in politics, not in CC.',
    ': Individuals or groups initiating conflict, often seen as the primary cause of tension and discord. They may provoke violence or unrest.',
]
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]
```

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## Training Details

### Training Dataset

#### Unnamed Dataset


* Size: 16,964 training samples
* Columns: <code>sentence_0</code>, <code>sentence_1</code>, and <code>sentence_2</code>
* Approximate statistics based on the first 1000 samples:
  |         | sentence_0                                                                          | sentence_1                                                                         | sentence_2                                                                         |
  |:--------|:------------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|
  | type    | string                                                                              | string                                                                             | string                                                                             |
  | details | <ul><li>min: 6 tokens</li><li>mean: 104.84 tokens</li><li>max: 327 tokens</li></ul> | <ul><li>min: 31 tokens</li><li>mean: 49.21 tokens</li><li>max: 97 tokens</li></ul> | <ul><li>min: 31 tokens</li><li>mean: 47.28 tokens</li><li>max: 97 tokens</li></ul> |
* Samples:
  | sentence_0                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                 | sentence_1                                                                                                                                                                                                                             | sentence_2                                                                                                                                                                                                                                                               |
  |:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
  | <code><s>the entity has been involved in various actions and Events that align With the role of tyrants and corrupt officials who abuse their power ruling unjustly and oppressing those under their control specifically russia Military intervention in ukraine its annexation of crimea and its support separatist groups in eastern ukraine demonstrate patternr of Authoritarian Rule and exploitation additionally russia actions have been characterized by lack of transparency and accountability with allegations of human rights abuses and Suppression of dissenting voice thi behavior is consistent with the role of tyrants and corrupt officials who abuse their power to Maintain control and Suppress opposition</s><s></s><s>anger</s><s>disgust</s><s>fear</s></code>                  | <code>Heroes or guardians who protect values or communities, ensuring safety and upholding justice. They often take on roles such as law enforcement officers, soldiers, or community leaders</code>                                   | <code>Martyrs or saviors who sacrifice their well-being, or even their lives, for a greater good or cause. These individuals are often celebrated for their selflessness and dedication. This is mostly in politics, not in CC.</code>                                   |
  | <code><s>herir is the refined Context related to the entity context indicate that ukraine defense has been Supported by india in manner that has been ongoing over year thi support has been provided despitir russia opposition and it is alleged that Weapons have been sent to ukraine through european route Which has raised concerns About india compliance With international Laws regulating arms export</s><s></s><s>anticipation</s><s>fear</s></code>                                                                                                                                                                                                                                                                                                                                           | <code>Entities who are considered unlikely to succeed due to their disadvantaged position but strive against greater forces and obstacles. Their stories often inspire others.</code>                                                  | <code>Rebels, revolutionaries, or freedom fighters who challenge the status quo and fight for significant change or liberation from oppression. They are often seen as champions of justice and freedom.</code>                                                          |
  | <code><s>russia president putinr issued Warning that the red line must not be crossed referring to potential further Military action in Ukraine he Emphasized that any escalation Would have severir Consequences and stressed the need restraint on All side his Statement Came after Meeting With top security officials Where they Discussed strategies countering nato expansion into eastern europe and defending russian interest putinr also emphasized the importance of maintaining strategic stability in the region particularly given the recent buildup of Military force Along The border With ukraine he warned that any attempt to encroach on Russia sovereignty or territorial integrity Would be met With swift and decisive action</s><s></s><s>anticipation</s><s>optimism</s></code> | <code>Entities from other nations or regions creating geopolitical tension and acting against the interests of another country. They are often depicted as threats to national security. This is mostly in politics, not in CC.</code> | <code>Individuals accused of hostility or discrimination against specific groups. This includes entities committing acts falling under racism, sexism, homophobia, Antisemitism, Islamophobia, or any kind of hate speech. This is mostly in politics, not in CC.</code> |
* Loss: [<code>TripletLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#tripletloss) with these parameters:
  ```json
  {
      "distance_metric": "TripletDistanceMetric.EUCLIDEAN",
      "triplet_margin": 5
  }
  ```

### Training Hyperparameters
#### Non-Default Hyperparameters

- `num_train_epochs`: 6
- `multi_dataset_batch_sampler`: round_robin

#### All Hyperparameters
<details><summary>Click to expand</summary>

- `overwrite_output_dir`: False
- `do_predict`: False
- `eval_strategy`: no
- `prediction_loss_only`: True
- `per_device_train_batch_size`: 8
- `per_device_eval_batch_size`: 8
- `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
- `num_train_epochs`: 6
- `max_steps`: -1
- `lr_scheduler_type`: linear
- `lr_scheduler_kwargs`: {}
- `warmup_ratio`: 0.0
- `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`: False
- `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`: None
- `hub_always_push`: False
- `gradient_checkpointing`: False
- `gradient_checkpointing_kwargs`: None
- `include_inputs_for_metrics`: False
- `include_for_metrics`: []
- `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
- `average_tokens_across_devices`: False
- `prompts`: None
- `batch_sampler`: batch_sampler
- `multi_dataset_batch_sampler`: round_robin

</details>

### Training Logs
| Epoch  | Step  | Training Loss |
|:------:|:-----:|:-------------:|
| 0.2357 | 500   | 4.5473        |
| 0.4715 | 1000  | 2.5359        |
| 0.7072 | 1500  | 2.2468        |
| 0.9430 | 2000  | 1.9783        |
| 1.1787 | 2500  | 1.8315        |
| 1.4144 | 3000  | 1.8298        |
| 1.6502 | 3500  | 1.682         |
| 1.8859 | 4000  | 1.5649        |
| 2.1216 | 4500  | 1.5579        |
| 2.3574 | 5000  | 1.4128        |
| 2.5931 | 5500  | 1.2549        |
| 2.8289 | 6000  | 1.181         |
| 3.0646 | 6500  | 1.0095        |
| 3.3003 | 7000  | 0.9564        |
| 3.5361 | 7500  | 0.9461        |
| 3.7718 | 8000  | 0.8855        |
| 4.0075 | 8500  | 0.8634        |
| 4.2433 | 9000  | 0.6998        |
| 4.4790 | 9500  | 0.7194        |
| 4.7148 | 10000 | 0.7614        |
| 4.9505 | 10500 | 0.6216        |
| 5.1862 | 11000 | 0.5405        |
| 5.4220 | 11500 | 0.4347        |
| 5.6577 | 12000 | 0.3897        |
| 5.8934 | 12500 | 0.3221        |


### Framework Versions
- Python: 3.9.20
- Sentence Transformers: 3.3.1
- Transformers: 4.48.0
- PyTorch: 2.5.1+cu121
- Accelerate: 1.2.1
- Datasets: 3.2.0
- Tokenizers: 0.21.0

## 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",
}
```

#### TripletLoss
```bibtex
@misc{hermans2017defense,
    title={In Defense of the Triplet Loss for Person Re-Identification},
    author={Alexander Hermans and Lucas Beyer and Bastian Leibe},
    year={2017},
    eprint={1703.07737},
    archivePrefix={arXiv},
    primaryClass={cs.CV}
}
```

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