sentence-transformers safetensors xlm-roberta sentence-similarity feature-extraction generated_from_trainer dataset_size:199321 loss:CachedInfonce custom_code arxiv:1908.10084 arxiv:2101.06983 autotrain_compatible text-embeddings-inference endpoints_compatible region:us
---
library_name: sentence-transformers
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- feature-extraction
- generated_from_trainer
- dataset_size:199321
- loss:CachedInfonce
widget:
- source_sentence: What organization is the person excited about donating to
  sentences:
  - The superiority of Balcomy, next to Crail, Fife, in 1394 was possessed by Nicholas
    de Hay, and on 15 January that year it passed to David Lindsay of Carnbie. indicating
    that George Lauder only held Balcomy by hereditary feu.
  - However, Robertson pulled out of the bout citing injury and was replaced by Tim
    Means. He lost the back and forth fight via submission in the third round. Sullivan
    was expected to face Marcio Alexandre Jr. on July 12, 2015, at The Ultimate Fighter
    21 Finale. However, Alexandre pulled out of the fight during the week leading
    up to the event citing a rib injury and was replaced by promotional newcomer Dominic
    Waters. Sullivan won the one-sided fight via unanimous decision. Sullivan faced
    Alexander Yakovlev at UFC on Fox 18 on January 30, 2016. He lost the fight via
    knockout in the first round.
  - I am super excited about donating to the ASPCA, I really wish I had the financial
    means to be part of their monthly donation club. In my last post I mentioned some
    charms I made for some friends, one a loyal customer at my shop.
- source_sentence: What are the four most famous wildlife sanctuaries in Rajasthan
  sentences:
  - There are two sets of mushroom dies in a set with several plants/fungi dies and
    I have been finding myself drawn to mushroom images lately so I tackled those!
    Each mushroom is 6 pieces!
  - Copernicia is a genus of palms native to South America and the Greater Antilles.
    Of the known species and nothospecies (hybrids), 22 of the 27 are endemic to Cuba.
    They are fan palms (Arecaceae tribe Corypheae), with the leaves with a bare petiole
    terminating in a rounded fan of numerous leaflets.
  - The four most famous and visited wildlife sanctuaries of Rajasthan are Ranthambore
    National Park, Desert National Park, Sariska Wildlife Sanctuary and Bharatpur
    Bird Sanctuary. These natural preserves are world renowned for their stable and
    growing tiger population, which, until recently, was dwindling alarmingly. The
    sanctuaries are thronged by various wildlife enthusiasts and photographers who
    want to catch this majestic animal in their cameras.
- source_sentence: What were the political ideologies of the individuals involved
    in the inoculation debate in Norfolk
  sentences:
  - Once we typed in the site information and pressed Enter, the page loaded and we
    were directed to confirm that we were at least 21 years of age. Now, we come to
    the ListCrawler homepage.
  - Interestingly, pro and anti-inoculation stances also seemed to be defined by political
    ideology. Dr. Archibald Campbell along with a group of Norfolk gentlemen decided
    to employ inoculator Dr. John Dalgleish to inoculate them and their families.
    Dr. Dalgleish published an article in the Virginia Gazette in support of inoculation,
    declaring smallpox an epidemic since ships coming from the West Indies constantly
    brought infected people to the area. The public of Norfolk blamed this epidemic
    on inoculation rather than the ships, and opposed inoculation altogether. Dr.
    Campbell was a Loyalist, and was the only Loyalist physician in Norfolk. While
    leaders of anti-inoculation groups, Maximillian Calvert and Paul Loyal, were Patriots,
    along with every other physician in Norfolk, who opposed inoculation as well.
  - "Incumbent Democratic Governor Pat Morris Neff won re-election to a second term,\
    \ defeating Republican candidate William Hawley Atwell in a landslide. Democratic\
    \ primary \n\nGovernor Neff won in the Democratic party against three different\
    \ challengers relatively comfortably, and narrowly avoided a runoff."
- source_sentence: What is the Brazyn Roller and what makes it effective
  sentences:
  - Rolling with the Brazyn Roller. This is a killer roller with great "knobs" to
    get a little bit deeper that you can also take with you.
  - (born July 26, 1974) is a Japanese musical lyricist and keyboardist under Giza
    Studio label. She is a former member of the Japanese pop band Garnet Crow, primarily
    as the lead songwriter and keyboardist.
  - Poux is a French surname.
- source_sentence: What items are present in the described setting along with the
    policy on pets
  sentences:
  - In 1839 Sergeant John Adams and Dr. John Conolly were impressed by the work of
    Hill, and introduced the method into their Hanwell Asylum, by then the largest
    in the country. Hill's system was adapted, since Conolly was unable to supervise
    each attendant as closely as Hill had done.
  - There is also a grandfather clock and two oriental lions on grey marbled pedestals.
    Pets are allowed (Charges may be applicable)
  - 'Investigators stated that Philoumenos appeared to have been trying to protect
    his face with his hands when a blow to his face or head severed one finger on
    each hand. Raby escaped the scene of the crime undetected. Raby was subsequently
    found to have acted alone, "without any connection to a religious or political
    entity." An investigation launched by the Israeli police initially failed to identify
    the killer. Raby was arrested on 17 November 1982 as he again attempted enter
    the Monastery at Jacob''s Well illicitly by climbing over a wall; he was carrying
    hand grenades. Raby supplied the police with accurate details of his earlier,
    previously unsolved, crimes. These were the murder of Philoumenos; a March 1979
    murder of a Jewish gynecologist in Tel-Aviv; the murder of the family of a woman
    in Lod, Israel in April 1979 who claimed to have clairvoyant powers; and an assault
    on a nun at the Jacob''s Well holy site in April 1982. The nun was seriously wounded
    in the attack. Both she and the gynecologist were attacked by axe, according to
    prosecutors. Raby, a newly religious Jew, was described as unwashed, dressed in
    worn-out clothing, and audibly muttered passages of scripture in a strange manner.
    Psychiatric evaluations found that he was mentally incompetent to stand trial;
    he was committed to a mental hospital; details of his subsequent whereabouts are
    restricted by privacy regulations. At a court hearing after his arrest, an Israeli
    prosecutor told the court that Raby was convinced that the monastery was the site
    of the ancient Jewish Temple, and that he made an attempt on the life of the nun
    "in response to a divine command." Erroneous accounts

    Initial accounts depicted the murder as an anti-Christian hate attack carried
    out by a group of Jewish settlers, the result being what Maariv described as "a
    wave of hatred" in Greece. Reports indicating that "radical Jews" had tortured
    Philoumenos and "cut off the fingers of his hand" before killing him had appeared
    in Greek newspapers. Maariv also quoted an official in the Greek Orthodox Patriarchate
    in Jerusalem asserting that "the murder was carried out by radical religious Jews"
    claiming that "the Well does not belong to Christians but to Jews". In a 2017
    article in the journal Israel Studies, researchers David Gurevich and Yisca Harani
    found that false accounts blaming the slaying on "settlers" and "Zionist extremists"
    persisted even after the arrest of the assailant and his confinement in a mental
    institution, and that there were "patterns of ritual murder accusation in the
    popular narrative." The same theme was echoed in parts of the Eastern Orthodox
    community and by some secular sources, including Blackwell''s Dictionary of Eastern
    Christianity, the Encyclopedia of the Israeli-Palestinian Conflict,  The Spectator
    and Times Literary Supplement, as well as Wikipedia. Gurevich and Harani contended
    that a 1989 account of the murder, published in Orthodox America, a publication
    of the Russian Orthodox Church Outside Russia, became the basis of an anti-Semitic
    ritual murder narrative, according to which a group of anti-Christianity Jews
    first harassed Philoumenos and destroyed Christian holy objects at the monastery,
    then murdered him. Veneration

    In 2009 the Greek Orthodox Patriarchate of Jerusalem recognised him as a holy
    martyr of the Eastern Orthodox Church, thirty years after his "martyrdom". The
    "careful" wording of the pronouncement of the Jerusalem Patriarchate that canonized
    Philoumenos makes no mention of murderer''s faith or ethnicity; he is described
    as a "vile man" a "heterodox fanatic visitor" and, inaccurately, as an individual
    who "with an axe, opened a deep cut across his forehead, cut off the fingers of
    his right hand, and upon escaping threw a grenade which ended the Father''s life."'
---

# SentenceTransformer

This is a [sentence-transformers](https://www.SBERT.net) model trained. It maps sentences & paragraphs to a 1024-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:** [Unknown](https://huggingface.co/unknown) -->
- **Maximum Sequence Length:** 8192 tokens
- **Output Dimensionality:** 1024 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(
  (transformer): Transformer(
    (auto_model): XLMRobertaLoRA(
      (roberta): XLMRobertaModel(
        (embeddings): XLMRobertaEmbeddings(
          (word_embeddings): ParametrizedEmbedding(
            250002, 1024, padding_idx=1
            (parametrizations): ModuleDict(
              (weight): ParametrizationList(
                (0): LoRAParametrization()
              )
            )
          )
          (token_type_embeddings): ParametrizedEmbedding(
            1, 1024
            (parametrizations): ModuleDict(
              (weight): ParametrizationList(
                (0): LoRAParametrization()
              )
            )
          )
        )
        (emb_drop): Dropout(p=0.1, inplace=False)
        (emb_ln): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)
        (encoder): XLMRobertaEncoder(
          (layers): ModuleList(
            (0-23): 24 x Block(
              (mixer): MHA(
                (rotary_emb): RotaryEmbedding()
                (Wqkv): ParametrizedLinearResidual(
                  in_features=1024, out_features=3072, bias=True
                  (parametrizations): ModuleDict(
                    (weight): ParametrizationList(
                      (0): LoRAParametrization()
                    )
                  )
                )
                (inner_attn): FlashSelfAttention(
                  (drop): Dropout(p=0.1, inplace=False)
                )
                (inner_cross_attn): FlashCrossAttention(
                  (drop): Dropout(p=0.1, inplace=False)
                )
                (out_proj): ParametrizedLinear(
                  in_features=1024, out_features=1024, bias=True
                  (parametrizations): ModuleDict(
                    (weight): ParametrizationList(
                      (0): LoRAParametrization()
                    )
                  )
                )
              )
              (dropout1): Dropout(p=0.1, inplace=False)
              (drop_path1): StochasticDepth(p=0.0, mode=row)
              (norm1): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)
              (mlp): Mlp(
                (fc1): ParametrizedLinear(
                  in_features=1024, out_features=4096, bias=True
                  (parametrizations): ModuleDict(
                    (weight): ParametrizationList(
                      (0): LoRAParametrization()
                    )
                  )
                )
                (fc2): ParametrizedLinear(
                  in_features=4096, out_features=1024, bias=True
                  (parametrizations): ModuleDict(
                    (weight): ParametrizationList(
                      (0): LoRAParametrization()
                    )
                  )
                )
              )
              (dropout2): Dropout(p=0.1, inplace=False)
              (drop_path2): StochasticDepth(p=0.0, mode=row)
              (norm2): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)
            )
          )
        )
        (pooler): XLMRobertaPooler(
          (dense): ParametrizedLinear(
            in_features=1024, out_features=1024, bias=True
            (parametrizations): ModuleDict(
              (weight): ParametrizationList(
                (0): LoRAParametrization()
              )
            )
          )
          (activation): Tanh()
        )
      )
    )
  )
  (pooler): Pooling({'word_embedding_dimension': 1024, '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})
  (normalizer): 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("Jrinky/final_stage1")
# Run inference
sentences = [
    'What items are present in the described setting along with the policy on pets',
    'There is also a grandfather clock and two oriental lions on grey marbled pedestals. Pets are allowed (Charges may be applicable)',
    'Investigators stated that Philoumenos appeared to have been trying to protect his face with his hands when a blow to his face or head severed one finger on each hand. Raby escaped the scene of the crime undetected. Raby was subsequently found to have acted alone, "without any connection to a religious or political entity." An investigation launched by the Israeli police initially failed to identify the killer. Raby was arrested on 17 November 1982 as he again attempted enter the Monastery at Jacob\'s Well illicitly by climbing over a wall; he was carrying hand grenades. Raby supplied the police with accurate details of his earlier, previously unsolved, crimes. These were the murder of Philoumenos; a March 1979 murder of a Jewish gynecologist in Tel-Aviv; the murder of the family of a woman in Lod, Israel in April 1979 who claimed to have clairvoyant powers; and an assault on a nun at the Jacob\'s Well holy site in April 1982. The nun was seriously wounded in the attack. Both she and the gynecologist were attacked by axe, according to prosecutors. Raby, a newly religious Jew, was described as unwashed, dressed in worn-out clothing, and audibly muttered passages of scripture in a strange manner. Psychiatric evaluations found that he was mentally incompetent to stand trial; he was committed to a mental hospital; details of his subsequent whereabouts are restricted by privacy regulations. At a court hearing after his arrest, an Israeli prosecutor told the court that Raby was convinced that the monastery was the site of the ancient Jewish Temple, and that he made an attempt on the life of the nun "in response to a divine command." Erroneous accounts\nInitial accounts depicted the murder as an anti-Christian hate attack carried out by a group of Jewish settlers, the result being what Maariv described as "a wave of hatred" in Greece. Reports indicating that "radical Jews" had tortured Philoumenos and "cut off the fingers of his hand" before killing him had appeared in Greek newspapers. Maariv also quoted an official in the Greek Orthodox Patriarchate in Jerusalem asserting that "the murder was carried out by radical religious Jews" claiming that "the Well does not belong to Christians but to Jews". In a 2017 article in the journal Israel Studies, researchers David Gurevich and Yisca Harani found that false accounts blaming the slaying on "settlers" and "Zionist extremists" persisted even after the arrest of the assailant and his confinement in a mental institution, and that there were "patterns of ritual murder accusation in the popular narrative." The same theme was echoed in parts of the Eastern Orthodox community and by some secular sources, including Blackwell\'s Dictionary of Eastern Christianity, the Encyclopedia of the Israeli-Palestinian Conflict,  The Spectator and Times Literary Supplement, as well as Wikipedia. Gurevich and Harani contended that a 1989 account of the murder, published in Orthodox America, a publication of the Russian Orthodox Church Outside Russia, became the basis of an anti-Semitic ritual murder narrative, according to which a group of anti-Christianity Jews first harassed Philoumenos and destroyed Christian holy objects at the monastery, then murdered him. Veneration\nIn 2009 the Greek Orthodox Patriarchate of Jerusalem recognised him as a holy martyr of the Eastern Orthodox Church, thirty years after his "martyrdom". The "careful" wording of the pronouncement of the Jerusalem Patriarchate that canonized Philoumenos makes no mention of murderer\'s faith or ethnicity; he is described as a "vile man" a "heterodox fanatic visitor" and, inaccurately, as an individual who "with an axe, opened a deep cut across his forehead, cut off the fingers of his right hand, and upon escaping threw a grenade which ended the Father\'s life."',
]
embeddings = model.encode(sentences)
print(embeddings.shape)
# [3, 1024]

# 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

#### Unnamed Dataset

* Size: 199,321 training samples
* Columns: <code>anchor</code> and <code>positive</code>
* Approximate statistics based on the first 1000 samples:
  |         | anchor                                                                            | positive                                                                             |
  |:--------|:----------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|
  | type    | string                                                                            | string                                                                               |
  | details | <ul><li>min: 7 tokens</li><li>mean: 17.09 tokens</li><li>max: 46 tokens</li></ul> | <ul><li>min: 8 tokens</li><li>mean: 109.45 tokens</li><li>max: 1835 tokens</li></ul> |
* Samples:
  | anchor                                                                                                                       | positive                                                                                                                                                                                                                                                            |
  |:-----------------------------------------------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
  | <code>Where is Nagpada located</code>                                                                                        | <code>Nagpada is a neighbourhood in South Mumbai.</code>                                                                                                                                                                                                            |
  | <code>What types of players are associated with Folkestone F.C., Midland Football League, and English Football League</code> | <code>players<br>Folkestone F.C. players<br>Midland Football League players<br>English Football League players</code>                                                                                                                                               |
  | <code>What is Anthony Elujoba known for in the field of Pharmacognosy</code>                                                 | <code>Anthony Elujoba (born 1948) is a Nigerian professor of  Pharmacognosy, fondly referred to as the "village chemist" because of his involvement in research into medicinal plants. He was acting vice chancellor of Obafemi Awolowo University, Nigeria.</code> |
* Loss: <code>cachedselfloss.CachedInfonce</code> with these parameters:
  ```json
  {
      "scale": 20.0,
      "similarity_fct": "cos_sim"
  }
  ```

### Evaluation Dataset

#### Unnamed Dataset

* Size: 4,068 evaluation samples
* Columns: <code>anchor</code> and <code>positive</code>
* Approximate statistics based on the first 1000 samples:
  |         | anchor                                                                            | positive                                                                             |
  |:--------|:----------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|
  | type    | string                                                                            | string                                                                               |
  | details | <ul><li>min: 6 tokens</li><li>mean: 17.26 tokens</li><li>max: 40 tokens</li></ul> | <ul><li>min: 6 tokens</li><li>mean: 108.28 tokens</li><li>max: 2233 tokens</li></ul> |
* Samples:
  | anchor                                                                                 | positive                                                                                                                                                                                                                                                                                                                                    |
  |:---------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
  | <code>What metaphor is being used to describe collaboration in the text segment</code> | <code>Like two oxen in a field, tied shoulder to shoulder. With Jesus doing all of the heavy lifting.</code>                                                                                                                                                                                                                                |
  | <code>What titles did McGurk win while playing as a schoolboy and a student</code>     | <code>He won consecutive MacRory Cup titles lining out as a schoolboy with St Patrick's College, Maghera before winning a Sigerson Cup title as a student at Queen's University Belfast. McGurk progressed onto the Lavey senior teams in both codes and was corner-forward on the team that won the All-Ireland SCFC title in 1991.</code> |
  | <code>What are the borders of the Trinity-Bellwoods neighborhood in Toronto</code>     | <code>Trinity-Bellwoods is an inner city neighbourhood in Toronto, Ontario, Canada. It is bounded on the east by Bathurst Street, on the north by College Street, on the south by Queen Street West, and by Dovercourt Road on the west.</code>                                                                                             |
* Loss: <code>cachedselfloss.CachedInfonce</code> with these parameters:
  ```json
  {
      "scale": 20.0,
      "similarity_fct": "cos_sim"
  }
  ```

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

- `eval_strategy`: steps
- `per_device_train_batch_size`: 2000
- `per_device_eval_batch_size`: 2000
- `learning_rate`: 2e-05
- `num_train_epochs`: 1
- `warmup_ratio`: 0.1
- `bf16`: 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`: 2000
- `per_device_eval_batch_size`: 2000
- `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`: True
- `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`: no_duplicates
- `multi_dataset_batch_sampler`: proportional

</details>

### Training Logs
| Epoch | Step | Training Loss | Validation Loss |
|:-----:|:----:|:-------------:|:---------------:|
| 0.1   | 10   | 0.3939        | 0.4079          |
| 0.2   | 20   | 0.4225        | 0.3920          |
| 0.3   | 30   | 0.4067        | 0.3819          |
| 0.4   | 40   | 0.3918        | 0.3760          |
| 0.5   | 50   | 0.4631        | 0.3719          |
| 0.6   | 60   | 0.3806        | 0.3686          |
| 0.7   | 70   | 0.3971        | 0.3663          |
| 0.8   | 80   | 0.3788        | 0.3655          |
| 0.9   | 90   | 0.3852        | 0.3649          |
| 1.0   | 100  | 0.3881        | 0.3648          |


### Framework Versions
- Python: 3.11.8
- Sentence Transformers: 3.4.1
- Transformers: 4.49.0
- PyTorch: 2.4.0+cu121
- Accelerate: 1.4.0
- Datasets: 3.3.2
- 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",
}
```

#### CachedInfonce
```bibtex
@misc{gao2021scaling,
    title={Scaling Deep Contrastive Learning Batch Size under Memory Limited Setup},
    author={Luyu Gao and Yunyi Zhang and Jiawei Han and Jamie Callan},
    year={2021},
    eprint={2101.06983},
    archivePrefix={arXiv},
    primaryClass={cs.LG}
}
```

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