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---
language:
- en
tags:
- sentence-transformers
- cross-encoder
- generated_from_trainer
- dataset_size:1990000
- loss:BinaryCrossEntropyLoss
base_model: answerdotai/ModernBERT-base
datasets:
- sentence-transformers/msmarco
pipeline_tag: text-ranking
library_name: sentence-transformers
metrics:
- map
- mrr@10
- ndcg@10
model-index:
- name: CrossEncoder based on answerdotai/ModernBERT-base
results:
- task:
type: cross-encoder-reranking
name: Cross Encoder Reranking
dataset:
name: NanoMSMARCO R100
type: NanoMSMARCO_R100
metrics:
- type: map
value: 0.6611
name: Map
- type: mrr@10
value: 0.6577
name: Mrr@10
- type: ndcg@10
value: 0.7254
name: Ndcg@10
- task:
type: cross-encoder-reranking
name: Cross Encoder Reranking
dataset:
name: NanoNFCorpus R100
type: NanoNFCorpus_R100
metrics:
- type: map
value: 0.3144
name: Map
- type: mrr@10
value: 0.5085
name: Mrr@10
- type: ndcg@10
value: 0.3421
name: Ndcg@10
- task:
type: cross-encoder-reranking
name: Cross Encoder Reranking
dataset:
name: NanoNQ R100
type: NanoNQ_R100
metrics:
- type: map
value: 0.6828
name: Map
- type: mrr@10
value: 0.7167
name: Mrr@10
- type: ndcg@10
value: 0.7314
name: Ndcg@10
- task:
type: cross-encoder-nano-beir
name: Cross Encoder Nano BEIR
dataset:
name: NanoBEIR R100 mean
type: NanoBEIR_R100_mean
metrics:
- type: map
value: 0.5527
name: Map
- type: mrr@10
value: 0.6276
name: Mrr@10
- type: ndcg@10
value: 0.5996
name: Ndcg@10
---
# CrossEncoder based on answerdotai/ModernBERT-base
This is a [Cross Encoder](https://www.sbert.net/docs/cross_encoder/usage/usage.html) model finetuned from [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on the [msmarco](https://huggingface.co/datasets/sentence-transformers/msmarco) dataset using the [sentence-transformers](https://www.SBERT.net) library. It computes scores for pairs of texts, which can be used for text reranking and semantic search.
## Model Details
### Model Description
- **Model Type:** Cross Encoder
- **Base model:** [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) <!-- at revision 8949b909ec900327062f0ebf497f51aef5e6f0c8 -->
- **Maximum Sequence Length:** 8192 tokens
- **Number of Output Labels:** 1 label
- **Training Dataset:**
- [msmarco](https://huggingface.co/datasets/sentence-transformers/msmarco)
- **Language:** en
<!-- - **License:** Unknown -->
### Model Sources
- **Documentation:** [Sentence Transformers Documentation](https://sbert.net)
- **Documentation:** [Cross Encoder Documentation](https://www.sbert.net/docs/cross_encoder/usage/usage.html)
- **Repository:** [Sentence Transformers on GitHub](https://github.com/UKPLab/sentence-transformers)
- **Hugging Face:** [Cross Encoders on Hugging Face](https://huggingface.co/models?library=sentence-transformers&other=cross-encoder)
## 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 CrossEncoder
# Download from the 🤗 Hub
model = CrossEncoder("skfrost19/reranker-ModernBERT-base-msmarco-bce-AdamW.Cosine-ep-1-3")
# Get scores for pairs of texts
pairs = [
['what symptoms might a patient with a tmd have', 'TMD sufferers have a long list of symptoms, including chronic pain (https://youtu.be/SvMaJb8o2RI), many of which are in common with Parkinsonâ\x80\x99s disease (PD) symptoms.'],
['what is a thermal protector', 'The word hero comes from the Greek á¼¥Ï\x81Ï\x89Ï\x82 (hÄ\x93rÅ\x8ds), hero, warrior, particularly one such as Heracles with divine ancestry or later given divine honors. literally protector or defender.'],
['how many copies of call of duty wwii sold', 'Call of Duty 3. Call of Duty 3 is a World War II first-person shooter and the third installment in the Call of Duty video game series. Released on November 7, 2006, the game was developed by Treyarch, and was the first major installment in the Call of Duty series not to be developed by Infinity Ward. It was also the first not to be released on the PC platform. It was released on the PlayStation 2, PlayStation 3, Wii, Xbox, and Xbox 360.'],
['what is the desired temperature for the fresh food compartment in a refrigerator', 'A refrigerator maintains a temperature a few degrees above the freezing point of water. Optimum temperature range for perishable food storage is 3 to 5 °C (37 to 41 °F).emperature settings for refrigerator and freezer compartments are often given arbitrary numbers by manufacturers (for example, 1 through 9, warmest to coldest), but generally 3 to 5 °C (37 to 41 °F) is ideal for the refrigerator compartment and â\x88\x9218 °C (0 °F) for the freezer.'],
['what is gsm alarm system', 'Iâ\x80\x99m sure you would have these questions in your mind when you heard GSM alarm system at the first time. GSM alarm system is an alarm system that operating through GSM (global system for mobile communications) network; not requiring a telephone line.urthermore, in the case of burglar entering the premises and cutting the telephone line, the GSM alarm would not be affected and still work as it does not require the use of a fixed phone line. So this security alarm is ideal for the place where no fixed phone line or hard to get one.'],
]
scores = model.predict(pairs)
print(scores.shape)
# (5,)
# Or rank different texts based on similarity to a single text
ranks = model.rank(
'what symptoms might a patient with a tmd have',
[
'TMD sufferers have a long list of symptoms, including chronic pain (https://youtu.be/SvMaJb8o2RI), many of which are in common with Parkinsonâ\x80\x99s disease (PD) symptoms.',
'The word hero comes from the Greek á¼¥Ï\x81Ï\x89Ï\x82 (hÄ\x93rÅ\x8ds), hero, warrior, particularly one such as Heracles with divine ancestry or later given divine honors. literally protector or defender.',
'Call of Duty 3. Call of Duty 3 is a World War II first-person shooter and the third installment in the Call of Duty video game series. Released on November 7, 2006, the game was developed by Treyarch, and was the first major installment in the Call of Duty series not to be developed by Infinity Ward. It was also the first not to be released on the PC platform. It was released on the PlayStation 2, PlayStation 3, Wii, Xbox, and Xbox 360.',
'A refrigerator maintains a temperature a few degrees above the freezing point of water. Optimum temperature range for perishable food storage is 3 to 5 °C (37 to 41 °F).emperature settings for refrigerator and freezer compartments are often given arbitrary numbers by manufacturers (for example, 1 through 9, warmest to coldest), but generally 3 to 5 °C (37 to 41 °F) is ideal for the refrigerator compartment and â\x88\x9218 °C (0 °F) for the freezer.',
'Iâ\x80\x99m sure you would have these questions in your mind when you heard GSM alarm system at the first time. GSM alarm system is an alarm system that operating through GSM (global system for mobile communications) network; not requiring a telephone line.urthermore, in the case of burglar entering the premises and cutting the telephone line, the GSM alarm would not be affected and still work as it does not require the use of a fixed phone line. So this security alarm is ideal for the place where no fixed phone line or hard to get one.',
]
)
# [{'corpus_id': ..., 'score': ...}, {'corpus_id': ..., 'score': ...}, ...]
```
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<details><summary>Click to see the direct usage in Transformers</summary>
</details>
-->
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### Downstream Usage (Sentence Transformers)
You can finetune this model on your own dataset.
<details><summary>Click to expand</summary>
</details>
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## Evaluation
### Metrics
#### Cross Encoder Reranking
* Datasets: `NanoMSMARCO_R100`, `NanoNFCorpus_R100` and `NanoNQ_R100`
* Evaluated with [<code>CrossEncoderRerankingEvaluator</code>](https://sbert.net/docs/package_reference/cross_encoder/evaluation.html#sentence_transformers.cross_encoder.evaluation.CrossEncoderRerankingEvaluator) with these parameters:
```json
{
"at_k": 10,
"always_rerank_positives": true
}
```
| Metric | NanoMSMARCO_R100 | NanoNFCorpus_R100 | NanoNQ_R100 |
|:------------|:---------------------|:---------------------|:---------------------|
| map | 0.6611 (+0.1715) | 0.3144 (+0.0534) | 0.6828 (+0.2632) |
| mrr@10 | 0.6577 (+0.1802) | 0.5085 (+0.0087) | 0.7167 (+0.2900) |
| **ndcg@10** | **0.7254 (+0.1850)** | **0.3421 (+0.0171)** | **0.7314 (+0.2308)** |
#### Cross Encoder Nano BEIR
* Dataset: `NanoBEIR_R100_mean`
* Evaluated with [<code>CrossEncoderNanoBEIREvaluator</code>](https://sbert.net/docs/package_reference/cross_encoder/evaluation.html#sentence_transformers.cross_encoder.evaluation.CrossEncoderNanoBEIREvaluator) with these parameters:
```json
{
"dataset_names": [
"msmarco",
"nfcorpus",
"nq"
],
"rerank_k": 100,
"at_k": 10,
"always_rerank_positives": true
}
```
| Metric | Value |
|:------------|:---------------------|
| map | 0.5527 (+0.1627) |
| mrr@10 | 0.6276 (+0.1596) |
| **ndcg@10** | **0.5996 (+0.1443)** |
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## Training Details
### Training Dataset
#### msmarco
* Dataset: [msmarco](https://huggingface.co/datasets/sentence-transformers/msmarco) at [9e329ed](https://huggingface.co/datasets/sentence-transformers/msmarco/tree/9e329ed2e649c9d37b0d91dd6b764ff6fe671d83)
* Size: 1,990,000 training samples
* Columns: <code>query</code>, <code>passage</code>, and <code>score</code>
* Approximate statistics based on the first 1000 samples:
| | query | passage | score |
|:--------|:------------------------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------------------|:---------------------------------------------------------------|
| type | string | string | float |
| details | <ul><li>min: 11 characters</li><li>mean: 34.61 characters</li><li>max: 124 characters</li></ul> | <ul><li>min: 82 characters</li><li>mean: 357.43 characters</li><li>max: 1034 characters</li></ul> | <ul><li>min: 0.0</li><li>mean: 0.49</li><li>max: 1.0</li></ul> |
* Samples:
| query | passage | score |
|:---------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-----------------|
| <code>what causes your tailbone to hurt</code> | <code>A coccyx injury results in pain and discomfort in the tailbone area (the condition is called coccydynia). These injuries may result in a bruise, dislocation, or fracture (break) of the coccyx. Although they may be slow to heal, the majority of coccyx injuries can be managed with cautious treatment.ost tailbone injuries are caused by trauma to the coccyx area. 1 A fall onto the tailbone in the seated position, usually against a hard surface, is the most common cause of coccyx injuries. 2 A direct blow to the tailbone, such as those that occur during contact sports, can injure the coccyx.</code> | <code>1.0</code> |
| <code>what muscles do trunk lateral flexion</code> | <code>Itâs the same with the External Obliques, but unlike the External Obliques, they are not visible when fully developed. Action: 1 Supports abdominal wall, assists forced respiration, aids raising intra-abdominal pressure and, with muscles of other side, abducts and rotates trunk. 2 Contraction of one side alone laterally bends the trunk to that side and rotates the trunk to the other side.</code> | <code>0.0</code> |
| <code>brake horsepower definition</code> | <code>When the brake lights will not come on, the first thing to check is the third-brake light. If it too is not working, the brake-light switch, a bad fuse or an unplugged harness is likely.ull up on the brake pedal and if the lights go out, switch mis-alignment or pedal position error is the likely cause. The final possibility is a wire shorted to power. Unplug the brake-light switch and if the lights stay on, a short circuit is the case.</code> | <code>0.0</code> |
* Loss: [<code>BinaryCrossEntropyLoss</code>](https://sbert.net/docs/package_reference/cross_encoder/losses.html#binarycrossentropyloss) with these parameters:
```json
{
"activation_fn": "torch.nn.modules.linear.Identity",
"pos_weight": null
}
```
### Evaluation Dataset
#### msmarco
* Dataset: [msmarco](https://huggingface.co/datasets/sentence-transformers/msmarco) at [9e329ed](https://huggingface.co/datasets/sentence-transformers/msmarco/tree/9e329ed2e649c9d37b0d91dd6b764ff6fe671d83)
* Size: 10,000 evaluation samples
* Columns: <code>query</code>, <code>passage</code>, and <code>score</code>
* Approximate statistics based on the first 1000 samples:
| | query | passage | score |
|:--------|:-----------------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------------------|:--------------------------------------------------------------|
| type | string | string | float |
| details | <ul><li>min: 9 characters</li><li>mean: 33.72 characters</li><li>max: 193 characters</li></ul> | <ul><li>min: 55 characters</li><li>mean: 353.35 characters</li><li>max: 895 characters</li></ul> | <ul><li>min: 0.0</li><li>mean: 0.5</li><li>max: 1.0</li></ul> |
* Samples:
| query | passage | score |
|:-----------------------------------------------------------|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-----------------|
| <code>what symptoms might a patient with a tmd have</code> | <code>TMD sufferers have a long list of symptoms, including chronic pain (https://youtu.be/SvMaJb8o2RI), many of which are in common with Parkinsonâs disease (PD) symptoms.</code> | <code>1.0</code> |
| <code>what is a thermal protector</code> | <code>The word hero comes from the Greek á¼¥ÏÏÏ (hÄrÅs), hero, warrior, particularly one such as Heracles with divine ancestry or later given divine honors. literally protector or defender.</code> | <code>0.0</code> |
| <code>how many copies of call of duty wwii sold</code> | <code>Call of Duty 3. Call of Duty 3 is a World War II first-person shooter and the third installment in the Call of Duty video game series. Released on November 7, 2006, the game was developed by Treyarch, and was the first major installment in the Call of Duty series not to be developed by Infinity Ward. It was also the first not to be released on the PC platform. It was released on the PlayStation 2, PlayStation 3, Wii, Xbox, and Xbox 360.</code> | <code>0.0</code> |
* Loss: [<code>BinaryCrossEntropyLoss</code>](https://sbert.net/docs/package_reference/cross_encoder/losses.html#binarycrossentropyloss) with these parameters:
```json
{
"activation_fn": "torch.nn.modules.linear.Identity",
"pos_weight": null
}
```
### Training Hyperparameters
#### Non-Default Hyperparameters
- `eval_strategy`: epoch
- `per_device_train_batch_size`: 64
- `per_device_eval_batch_size`: 64
- `learning_rate`: 2e-05
- `warmup_ratio`: 0.1
- `seed`: 12
- `bf16`: True
- `dataloader_num_workers`: 4
- `load_best_model_at_end`: True
- `resume_from_checkpoint`: True
#### All Hyperparameters
<details><summary>Click to expand</summary>
- `overwrite_output_dir`: False
- `do_predict`: False
- `eval_strategy`: epoch
- `prediction_loss_only`: True
- `per_device_train_batch_size`: 64
- `per_device_eval_batch_size`: 64
- `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`: 3
- `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`: 12
- `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`: 2
- `ddp_backend`: None
- `tpu_num_cores`: None
- `tpu_metrics_debug`: False
- `debug`: []
- `dataloader_drop_last`: True
- `dataloader_num_workers`: 4
- `dataloader_prefetch_factor`: None
- `past_index`: -1
- `disable_tqdm`: False
- `remove_unused_columns`: True
- `label_names`: None
- `load_best_model_at_end`: True
- `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}
- `tp_size`: 0
- `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`: True
- `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`: proportional
</details>
### Training Logs
| Epoch | Step | Training Loss | Validation Loss | NanoMSMARCO_R100_ndcg@10 | NanoNFCorpus_R100_ndcg@10 | NanoNQ_R100_ndcg@10 | NanoBEIR_R100_mean_ndcg@10 |
|:-------:|:---------:|:-------------:|:---------------:|:------------------------:|:-------------------------:|:--------------------:|:--------------------------:|
| -1 | -1 | - | - | 0.0186 (-0.5218) | 0.2929 (-0.0321) | 0.0429 (-0.4577) | 0.1182 (-0.3372) |
| 0.0001 | 1 | 0.7403 | - | - | - | - | - |
| 0.3860 | 4000 | 0.201 | - | - | - | - | - |
| 0.7719 | 8000 | 0.1544 | - | - | - | - | - |
| 1.0 | 10364 | - | 0.1478 | 0.7029 (+0.1625) | 0.3798 (+0.0548) | 0.7394 (+0.2388) | 0.6074 (+0.1520) |
| 1.1579 | 12000 | 0.1364 | - | - | - | - | - |
| 1.5438 | 16000 | 0.1227 | - | - | - | - | - |
| 1.9298 | 20000 | 0.1173 | - | - | - | - | - |
| **2.0** | **20728** | **-** | **0.1297** | **0.7089 (+0.1685)** | **0.3785 (+0.0535)** | **0.7382 (+0.2375)** | **0.6085 (+0.1532)** |
| 2.3157 | 24000 | 0.1014 | - | - | - | - | - |
| 2.7017 | 28000 | 0.0969 | - | - | - | - | - |
| 3.0 | 31092 | - | 0.1195 | 0.6846 (+0.1442) | 0.3906 (+0.0655) | 0.7433 (+0.2426) | 0.6062 (+0.1508) |
| -1 | -1 | - | - | 0.7254 (+0.1850) | 0.3421 (+0.0171) | 0.7314 (+0.2308) | 0.5996 (+0.1443) |
* The bold row denotes the saved checkpoint.
### Framework Versions
- Python: 3.11.5
- Sentence Transformers: 4.0.1
- Transformers: 4.50.3
- PyTorch: 2.6.0+cu124
- Accelerate: 1.6.0
- Datasets: 3.5.0
- 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",
}
```
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