sentence-transformers safetensors modernbert sentence-similarity feature-extraction generated_from_trainer dataset_size:1136292 loss:CachedMultipleNegativesRankingLoss dataset:YesaOuO/TEKGEN-CTSP arxiv:1908.10084 arxiv:2101.06983 base_model:answerdotai/ModernBERT-base base_model:finetune:answerdotai/ModernBERT-base model-index autotrain_compatible endpoints_compatible region:us
---
base_model: answerdotai/ModernBERT-base
datasets:
- YesaOuO/TEKGEN-CTSP
library_name: sentence-transformers
metrics:
- cosine_accuracy
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- feature-extraction
- generated_from_trainer
- dataset_size:1136292
- loss:CachedMultipleNegativesRankingLoss
widget:
- source_sentence: During the 1960s Willard Cochrane was U.S. Department of Agriculture's
    head agricultural economist under U.S. Secretary of Agriculture Orville Freeman.
  sentences:
  - Cosmic Smash publisher Sega, platform Dreamcast.
  - Willard Cochrane occupation Economist.
  - Willard Cochrane educated at Harvard University, educated at Montana State University,
    date of birth 15 May 1914.
- source_sentence: Four Moons stars Antonio Velázquez, Alejandro de la Madrid, César
    Ramos, Gustavo Egelhaaf, Alonso Echánove, Alejandro Belmonte, Karina Gidi and
    Juan Manuel Bernal.
  sentences:
  - Four Moons cast member Juan Manuel Bernal, cast member Antonio Velázquez, cast
    member Alejandro de la Madrid, RTC film rating C.
  - Leukotriene C4 synthase ortholog Ltc4s, ortholog Ltc4s, instance of Gene.
  - Four Moons publication date 27 April 2015.
- source_sentence: James B. Kirby (September 28, 1884 - June 9, 1971) was an American
    inventor and self-taught electrical engineer who focused Jim Kirby's career on
    "eliminating the drudgery of housework".
  sentences:
  - Jim Kirby sex or gender male.
  - Kimberlé Williams Crenshaw notable work Intersectionality, field of work Intersectionality.
  - Jim Kirby date of death 09 June 1971, occupation Inventor, date of birth 28 September
    1884.
- source_sentence: Isabel Montero de la Cámara began work in the Foreign Office on
    June 18, 1974. and was appointed ambassador on April 9, 1996.
  sentences:
  - Back in Baby 's Arms publication date 00  1969, instance of Album.
  - Isabel Montero de la Cámara occupation Diplomat, country of citizenship Costa
    Rica, date of birth 01 January 1942.
  - Isabel Montero de la Cámara position held Ambassador.
- source_sentence: In 1842 Alvars married the harpist Melanie Lewy, a member of a
    Vienna-based family of musicians with whom Alvars frequently performed.
  sentences:
  - Elias Parish Alvars place of birth Teignmouth.
  - Olivia of Palermo date of death 10 June 0463, sex or gender female, feast day
    June 10.
  - Elias Parish Alvars spouse Melanie Lewy, place of death Vienna.
model-index:
- name: SentenceTransformer based on answerdotai/ModernBERT-base
  results:
  - task:
      type: triplet
      name: Triplet
    dataset:
      name: YesaOuO/TEKGEN CTSP
      type: YesaOuO/TEKGEN-CTSP
    metrics:
    - type: cosine_accuracy
      value: 0.916620671749115
      name: Cosine Accuracy
---

# SentenceTransformer based on answerdotai/ModernBERT-base

This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on the [tekgen-ctsp](https://huggingface.co/datasets/YesaOuO/TEKGEN-CTSP) 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:** [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) <!-- at revision 8949b909ec900327062f0ebf497f51aef5e6f0c8 -->
- **Maximum Sequence Length:** 8192 tokens
- **Output Dimensionality:** 768 dimensions
- **Similarity Function:** Cosine Similarity
- **Training Dataset:**
    - [tekgen-ctsp](https://huggingface.co/datasets/YesaOuO/TEKGEN-CTSP)
<!-- - **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': 8192, 'do_lower_case': False}) with Transformer model: ModernBertModel 
  (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("YesaOuO/ModernBERT-base-CTSP")
# Run inference
sentences = [
    'In 1842 Alvars married the harpist Melanie Lewy, a member of a Vienna-based family of musicians with whom Alvars frequently performed.',
    'Elias Parish Alvars spouse Melanie Lewy, place of death Vienna.',
    'Elias Parish Alvars place of birth Teignmouth.',
]
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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## Evaluation

### Metrics

#### Triplet

* Dataset: `YesaOuO/TEKGEN-CTSP`
* Evaluated with [<code>TripletEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.TripletEvaluator)

| Metric              | Value      |
|:--------------------|:-----------|
| **cosine_accuracy** | **0.9166** |

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## Training Details

### Training Dataset

#### tekgen-ctsp

* Dataset: [tekgen-ctsp](https://huggingface.co/datasets/YesaOuO/TEKGEN-CTSP) at [8d091eb](https://huggingface.co/datasets/YesaOuO/TEKGEN-CTSP/tree/8d091ebc57b429b55add63e77a0408fa8dc3732b)
* Size: 1,136,292 training samples
* Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
* Approximate statistics based on the first 1000 samples:
  |         | anchor                                                                              | positive                                                                          | negative                                                                          |
  |:--------|:------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|
  | type    | string                                                                              | string                                                                            | string                                                                            |
  | details | <ul><li>min: 11 tokens</li><li>mean: 38.01 tokens</li><li>max: 128 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 17.07 tokens</li><li>max: 47 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 17.02 tokens</li><li>max: 47 tokens</li></ul> |
* Samples:
  | anchor                                                                                                                      | positive                                                                                          | negative                                                                                  |
  |:----------------------------------------------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------------|
  | <code>1976 Swedish Grand Prix was the seventh round of the 1976 Formula One season and the ninth Swedish Grand Prix.</code> | <code>1976 Swedish Grand Prix point in time 13 June 1976, part of 1976 Formula One season.</code> | <code>1976 Swedish Grand Prix pole position Jody Scheckter, winner Jody Scheckter.</code> |
  | <code>1976 Swedish Grand Prix was the seventh round of the 1976 Formula One season and the ninth Swedish Grand Prix.</code> | <code>1976 Swedish Grand Prix point in time 13 June 1976, part of 1976 Formula One season.</code> | <code>1976 Swedish Grand Prix point in time 13 June 1976, country Sweden.</code>          |
  | <code>1976 Swedish Grand Prix was the seventh round of the 1976 Formula One season and the ninth Swedish Grand Prix.</code> | <code>1976 Swedish Grand Prix point in time 13 June 1976, part of 1976 Formula One season.</code> | <code>1976 Swedish Grand Prix point in time 13 June 1976.</code>                          |
* Loss: [<code>CachedMultipleNegativesRankingLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cachedmultiplenegativesrankingloss) with these parameters:
  ```json
  {
      "scale": 20.0,
      "similarity_fct": "cos_sim"
  }
  ```

### Evaluation Dataset

#### tekgen-ctsp

* Dataset: [tekgen-ctsp](https://huggingface.co/datasets/YesaOuO/TEKGEN-CTSP) at [8d091eb](https://huggingface.co/datasets/YesaOuO/TEKGEN-CTSP/tree/8d091ebc57b429b55add63e77a0408fa8dc3732b)
* Size: 10,866 evaluation samples
* Columns: <code>anchor</code>, <code>positive</code>, and <code>negative</code>
* Approximate statistics based on the first 1000 samples:
  |         | anchor                                                                              | positive                                                                          | negative                                                                          |
  |:--------|:------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|
  | type    | string                                                                              | string                                                                            | string                                                                            |
  | details | <ul><li>min: 13 tokens</li><li>mean: 40.18 tokens</li><li>max: 183 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 19.82 tokens</li><li>max: 62 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 19.82 tokens</li><li>max: 62 tokens</li></ul> |
* Samples:
  | anchor                                                                                                                                                                                                                         | positive                                                                                                                                | negative                                                                                                                                |
  |:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------------------------------------------------------------|
  | <code>Two men with prior criminal records, Dieter Degowski and Hans-Jürgen Rösner, went on the run for two days through Germany and the Netherlands.</code>                                                                    | <code>Gladbeck hostage crisis country Netherlands, country Germany, participant Hans-Jürgen Rösner, participant Dieter Degowski.</code> | <code>Gladbeck hostage crisis end time 18 August 1988, point in time 18 August 1988, country Germany, start time 16 August 1988.</code> |
  | <code>The Gladbeck hostage crisis (known in Germany as the Gladbeck hostage drama) was a hostage-taking crisis that happened in August 1988 after an armed bank raid in Gladbeck, North Rhine-Westphalia, West Germany.</code> | <code>Gladbeck hostage crisis end time 18 August 1988, point in time 18 August 1988, country Germany, start time 16 August 1988.</code> | <code>Gladbeck hostage crisis country Netherlands, country Germany, participant Hans-Jürgen Rösner, participant Dieter Degowski.</code> |
  | <code>The album was originally released only on cassette tape before later being made available for digital download on iTunes and similar digital media stores.</code>                                                        | <code>Vongole Fisarmonica instance of Album.</code>                                                                                     | <code>Vongole Fisarmonica performer Those Darn Accordions, publication date 01 January 1992, instance of Album.</code>                  |
* Loss: [<code>CachedMultipleNegativesRankingLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cachedmultiplenegativesrankingloss) with these parameters:
  ```json
  {
      "scale": 20.0,
      "similarity_fct": "cos_sim"
  }
  ```

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

- `per_device_train_batch_size`: 512
- `per_device_eval_batch_size`: 512
- `learning_rate`: 8e-05
- `num_train_epochs`: 1
- `warmup_ratio`: 0.05
- `bf16`: True
- `batch_sampler`: no_duplicates

#### 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`: 512
- `per_device_eval_batch_size`: 512
- `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`: 8e-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`: 0.05
- `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 | YesaOuO/TEKGEN-CTSP_cosine_accuracy |
|:------:|:----:|:-------------:|:-----------------------------------:|
| -1     | -1   | -             | 0.6585                              |
| 0.2252 | 500  | 0.6404        | -                                   |
| 0.4505 | 1000 | 0.212         | -                                   |
| 0.6757 | 1500 | 0.1764        | -                                   |
| 0.9009 | 2000 | 0.1562        | -                                   |
| -1     | -1   | -             | 0.9166                              |


### Framework Versions
- Python: 3.11.11
- Sentence Transformers: 3.4.1
- Transformers: 4.49.0
- PyTorch: 2.6.0+cu124
- Accelerate: 1.5.2
- Datasets: 3.3.2
- Tokenizers: 0.21.1

## 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",
}
```

#### CachedMultipleNegativesRankingLoss
```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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