|
---
|
|
language:
|
|
- en
|
|
tags:
|
|
- sentence-transformers
|
|
- cross-encoder
|
|
- text-classification
|
|
- generated_from_trainer
|
|
- dataset_size:5749
|
|
- loss:BinaryCrossEntropyLoss
|
|
base_model: distilbert/distilroberta-base
|
|
datasets:
|
|
- sentence-transformers/stsb
|
|
pipeline_tag: text-classification
|
|
library_name: sentence-transformers
|
|
metrics:
|
|
- pearson
|
|
- spearman
|
|
co2_eq_emissions:
|
|
emissions: 2.6550346776830636
|
|
energy_consumed: 0.006830514578476734
|
|
source: codecarbon
|
|
training_type: fine-tuning
|
|
on_cloud: false
|
|
cpu_model: 13th Gen Intel(R) Core(TM) i7-13700K
|
|
ram_total_size: 31.777088165283203
|
|
hours_used: 0.031
|
|
hardware_used: 1 x NVIDIA GeForce RTX 3090
|
|
model-index:
|
|
- name: CrossEncoder based on distilbert/distilroberta-base
|
|
results:
|
|
- task:
|
|
type: cross-encoder-correlation
|
|
name: Cross Encoder Correlation
|
|
dataset:
|
|
name: stsb validation
|
|
type: stsb-validation
|
|
metrics:
|
|
- type: pearson
|
|
value: 0.877295960646044
|
|
name: Pearson
|
|
- type: spearman
|
|
value: 0.8754151440157509
|
|
name: Spearman
|
|
- task:
|
|
type: cross-encoder-correlation
|
|
name: Cross Encoder Correlation
|
|
dataset:
|
|
name: stsb test
|
|
type: stsb-test
|
|
metrics:
|
|
- type: pearson
|
|
value: 0.8503341584157813
|
|
name: Pearson
|
|
- type: spearman
|
|
value: 0.8388642249054395
|
|
name: Spearman
|
|
---
|
|
|
|
# CrossEncoder based on distilbert/distilroberta-base
|
|
|
|
This is a [Cross Encoder](https://www.sbert.net/docs/cross_encoder/usage/usage.html) model finetuned from [distilbert/distilroberta-base](https://huggingface.co/distilbert/distilroberta-base) on the [stsb](https://huggingface.co/datasets/sentence-transformers/stsb) dataset using the [sentence-transformers](https://www.SBERT.net) library. It computes scores for pairs of texts, which can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more.
|
|
|
|
## Model Details
|
|
|
|
### Model Description
|
|
- **Model Type:** Cross Encoder
|
|
- **Base model:** [distilbert/distilroberta-base](https://huggingface.co/distilbert/distilroberta-base) <!-- at revision fb53ab8802853c8e4fbdbcd0529f21fc6f459b2b -->
|
|
- **Maximum Sequence Length:** 514 tokens
|
|
- **Training Dataset:**
|
|
- [stsb](https://huggingface.co/datasets/sentence-transformers/stsb)
|
|
- **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("tomaarsen/reranker-distilroberta-base-stsb")
|
|
# Get scores for pairs...
|
|
pairs = [
|
|
['A man with a hard hat is dancing.', 'A man wearing a hard hat is dancing.'],
|
|
['A young child is riding a horse.', 'A child is riding a horse.'],
|
|
['A man is feeding a mouse to a snake.', 'The man is feeding a mouse to the snake.'],
|
|
['A woman is playing the guitar.', 'A man is playing guitar.'],
|
|
['A woman is playing the flute.', 'A man is playing a flute.'],
|
|
]
|
|
scores = model.predict(pairs)
|
|
print(scores.shape)
|
|
# [5]
|
|
|
|
# ... or rank different texts based on similarity to a single text
|
|
ranks = model.rank(
|
|
'A man with a hard hat is dancing.',
|
|
[
|
|
'A man wearing a hard hat is dancing.',
|
|
'A child is riding a horse.',
|
|
'The man is feeding a mouse to the snake.',
|
|
'A man is playing guitar.',
|
|
'A man is playing a flute.',
|
|
]
|
|
)
|
|
# [{'corpus_id': ..., 'score': ...}, {'corpus_id': ..., 'score': ...}, ...]
|
|
```
|
|
|
|
<!--
|
|
### 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.*
|
|
-->
|
|
|
|
## Evaluation
|
|
|
|
### Metrics
|
|
|
|
#### Cross Encoder Correlation
|
|
|
|
* Datasets: `stsb-validation` and `stsb-test`
|
|
* Evaluated with [<code>CECorrelationEvaluator</code>](https://sbert.net/docs/package_reference/cross_encoder/evaluation.html#sentence_transformers.cross_encoder.evaluation.CECorrelationEvaluator)
|
|
|
|
| Metric | stsb-validation | stsb-test |
|
|
|:-------------|:----------------|:-----------|
|
|
| pearson | 0.8773 | 0.8503 |
|
|
| **spearman** | **0.8754** | **0.8389** |
|
|
|
|
<!--
|
|
## 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
|
|
|
|
#### stsb
|
|
|
|
* Dataset: [stsb](https://huggingface.co/datasets/sentence-transformers/stsb) at [ab7a5ac](https://huggingface.co/datasets/sentence-transformers/stsb/tree/ab7a5ac0e35aa22088bdcf23e7fd99b220e53308)
|
|
* Size: 5,749 training samples
|
|
* Columns: <code>sentence1</code>, <code>sentence2</code>, and <code>score</code>
|
|
* Approximate statistics based on the first 1000 samples:
|
|
| | sentence1 | sentence2 | score |
|
|
|:--------|:------------------------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------------------|:---------------------------------------------------------------|
|
|
| type | string | string | float |
|
|
| details | <ul><li>min: 16 characters</li><li>mean: 31.92 characters</li><li>max: 113 characters</li></ul> | <ul><li>min: 16 characters</li><li>mean: 31.51 characters</li><li>max: 94 characters</li></ul> | <ul><li>min: 0.0</li><li>mean: 0.45</li><li>max: 1.0</li></ul> |
|
|
* Samples:
|
|
| sentence1 | sentence2 | score |
|
|
|:-----------------------------------------------------------|:----------------------------------------------------------------------|:------------------|
|
|
| <code>A plane is taking off.</code> | <code>An air plane is taking off.</code> | <code>1.0</code> |
|
|
| <code>A man is playing a large flute.</code> | <code>A man is playing a flute.</code> | <code>0.76</code> |
|
|
| <code>A man is spreading shreded cheese on a pizza.</code> | <code>A man is spreading shredded cheese on an uncooked pizza.</code> | <code>0.76</code> |
|
|
* Loss: [<code>BinaryCrossEntropyLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#binarycrossentropyloss)
|
|
|
|
### Evaluation Dataset
|
|
|
|
#### stsb
|
|
|
|
* Dataset: [stsb](https://huggingface.co/datasets/sentence-transformers/stsb) at [ab7a5ac](https://huggingface.co/datasets/sentence-transformers/stsb/tree/ab7a5ac0e35aa22088bdcf23e7fd99b220e53308)
|
|
* Size: 1,500 evaluation samples
|
|
* Columns: <code>sentence1</code>, <code>sentence2</code>, and <code>score</code>
|
|
* Approximate statistics based on the first 1000 samples:
|
|
| | sentence1 | sentence2 | score |
|
|
|:--------|:------------------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------------------|:---------------------------------------------------------------|
|
|
| type | string | string | float |
|
|
| details | <ul><li>min: 12 characters</li><li>mean: 57.37 characters</li><li>max: 144 characters</li></ul> | <ul><li>min: 17 characters</li><li>mean: 56.84 characters</li><li>max: 141 characters</li></ul> | <ul><li>min: 0.0</li><li>mean: 0.42</li><li>max: 1.0</li></ul> |
|
|
* Samples:
|
|
| sentence1 | sentence2 | score |
|
|
|:--------------------------------------------------|:------------------------------------------------------|:------------------|
|
|
| <code>A man with a hard hat is dancing.</code> | <code>A man wearing a hard hat is dancing.</code> | <code>1.0</code> |
|
|
| <code>A young child is riding a horse.</code> | <code>A child is riding a horse.</code> | <code>0.95</code> |
|
|
| <code>A man is feeding a mouse to a snake.</code> | <code>The man is feeding a mouse to the snake.</code> | <code>1.0</code> |
|
|
* Loss: [<code>BinaryCrossEntropyLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#binarycrossentropyloss)
|
|
|
|
### Training Hyperparameters
|
|
#### Non-Default Hyperparameters
|
|
|
|
- `eval_strategy`: steps
|
|
- `per_device_train_batch_size`: 64
|
|
- `per_device_eval_batch_size`: 64
|
|
- `num_train_epochs`: 4
|
|
- `warmup_ratio`: 0.1
|
|
- `bf16`: True
|
|
|
|
#### 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`: 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`: 5e-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`: 4
|
|
- `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`: batch_sampler
|
|
- `multi_dataset_batch_sampler`: proportional
|
|
|
|
</details>
|
|
|
|
### Training Logs
|
|
| Epoch | Step | Training Loss | Validation Loss | stsb-validation_spearman | stsb-test_spearman |
|
|
|:------:|:----:|:-------------:|:---------------:|:------------------------:|:------------------:|
|
|
| -1 | -1 | - | - | -0.0150 | - |
|
|
| 0.2222 | 20 | 0.6905 | - | - | - |
|
|
| 0.4444 | 40 | 0.6548 | - | - | - |
|
|
| 0.6667 | 60 | 0.5906 | - | - | - |
|
|
| 0.8889 | 80 | 0.5631 | 0.5475 | 0.8589 | - |
|
|
| 1.1111 | 100 | 0.5517 | - | - | - |
|
|
| 1.3333 | 120 | 0.5473 | - | - | - |
|
|
| 1.5556 | 140 | 0.5454 | - | - | - |
|
|
| 1.7778 | 160 | 0.5402 | 0.5346 | 0.8760 | - |
|
|
| 2.0 | 180 | 0.542 | - | - | - |
|
|
| 2.2222 | 200 | 0.5229 | - | - | - |
|
|
| 2.4444 | 220 | 0.524 | - | - | - |
|
|
| 2.6667 | 240 | 0.5286 | 0.5373 | 0.8744 | - |
|
|
| 2.8889 | 260 | 0.5236 | - | - | - |
|
|
| 3.1111 | 280 | 0.5269 | - | - | - |
|
|
| 3.3333 | 300 | 0.5209 | - | - | - |
|
|
| 3.5556 | 320 | 0.5115 | 0.5409 | 0.8754 | - |
|
|
| 3.7778 | 340 | 0.5149 | - | - | - |
|
|
| 4.0 | 360 | 0.5084 | - | - | - |
|
|
| -1 | -1 | - | - | - | 0.8389 |
|
|
|
|
|
|
### Environmental Impact
|
|
Carbon emissions were measured using [CodeCarbon](https://github.com/mlco2/codecarbon).
|
|
- **Energy Consumed**: 0.007 kWh
|
|
- **Carbon Emitted**: 0.003 kg of CO2
|
|
- **Hours Used**: 0.031 hours
|
|
|
|
### Training Hardware
|
|
- **On Cloud**: No
|
|
- **GPU Model**: 1 x NVIDIA GeForce RTX 3090
|
|
- **CPU Model**: 13th Gen Intel(R) Core(TM) i7-13700K
|
|
- **RAM Size**: 31.78 GB
|
|
|
|
### Framework Versions
|
|
- Python: 3.11.6
|
|
- Sentence Transformers: 3.5.0.dev0
|
|
- Transformers: 4.49.0.dev0
|
|
- PyTorch: 2.5.0+cu121
|
|
- Accelerate: 1.3.0
|
|
- Datasets: 2.20.0
|
|
- 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",
|
|
}
|
|
```
|
|
|
|
<!--
|
|
## Glossary
|
|
|
|
*Clearly define terms in order to be accessible across audiences.*
|
|
-->
|
|
|
|
<!--
|
|
## Model Card Authors
|
|
|
|
*Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.*
|
|
-->
|
|
|
|
<!--
|
|
## Model Card Contact
|
|
|
|
*Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.*
|
|
--> |
