SentenceTransformer based on sentence-transformers/all-mpnet-base-v2
This is a sentence-transformers model finetuned from sentence-transformers/all-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/all-mpnet-base-v2
- Maximum Sequence Length: 384 tokens
- Output Dimensionality: 768 dimensions
- Similarity Function: Cosine Similarity
Model Sources
- Documentation: Sentence Transformers Documentation
- Repository: Sentence Transformers on GitHub
- Hugging Face: Sentence Transformers on Hugging Face
Full Model Architecture
SentenceTransformer(
(0): Transformer({'max_seq_length': 384, 'do_lower_case': False}) with Transformer model: MPNetModel
(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})
(2): Normalize()
)
Usage
Direct Usage (Sentence Transformers)
First install the Sentence Transformers library:
pip install -U sentence-transformers
Then you can load this model and run inference.
from sentence_transformers import SentenceTransformer
# Download from the 🤗 Hub
model = SentenceTransformer("mpnet-base-all-mqp-binary")
# Run inference
sentences = [
'My bm aren\'t solid but not quite loose. Looks more like for lack of better word "shredded" the why is this?',
'What causes stringy and shredded stools?',
'I have been taking treatment for anxiety and depression. I was given a new medication and have experienced heart flutters, can this medication cause it?',
]
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]
Evaluation
Metrics
Binary Classification
- Dataset:
all-mqp-test - Evaluated with BinaryClassificationEvaluator
| Metric | Value |
|---|---|
| cosine_accuracy | 0.8787 |
| cosine_accuracy_threshold | 0.7678 |
| cosine_f1 | 0.8796 |
| cosine_f1_threshold | 0.7446 |
| cosine_precision | 0.881 |
| cosine_recall | 0.8782 |
| cosine_ap | 0.9474 |
Training Details
Training Dataset
Unnamed Dataset
- Size: 2,437 training samples
- Columns: text1, text2, and label
- Approximate statistics based on the first 1000 samples:
text1 text2 label type string string int details min: 7 tokensmean: 26.53 tokensmax: 75 tokens min: 7 tokensmean: 28.18 tokensmax: 119 tokens 0: ~49.00%1: ~51.00% - Samples:
text1 text2 label I discovered I get this weakness in my hand whenever I try to snap my fingers, slight pain runs across elbow and wrist? When I try to snap my fingers there is weakness and pain across elbow and wrist? May I know what are the causes? 1 If a mother has celiac should the daughter be tested? What is Celiac disease? 0 Hi im 18 and I would like to know what I would use or take to get taller? Can growth hormone taken in minimal quantities increase height after 21 years in a male? 0 - Loss: ContrastiveLoss with these parameters:
{ "distance_metric": "SiameseDistanceMetric.COSINE_DISTANCE", "margin": 0.5, "size_average": true }
Evaluation Dataset
Unnamed Dataset
- Size: 610 evaluation samples
- Columns: text1, text2, and label
- Approximate statistics based on the first 610 samples:
text1 text2 label type string string int details min: 8 tokensmean: 27.56 tokensmax: 70 tokens min: 8 tokensmean: 27.88 tokensmax: 91 tokens 0: ~48.85%1: ~51.15% - Samples:
text1 text2 label Okay so i'm on bc and I have had sex (it hurts) i'm bleeding brown and my vagina hurts almost itchy but it hurts? I noticed a brown discharge and itching in my vaginal area to the point that it hurts. I am also on birth control and have sexual intercourse. What do you think is causing this? 1 I've had body aches, blocked stuffy nose, headaches, pressure in my face and throat tightness and it feels dry for 6 months is it a bad cold? For the last 6 months, I've noticed symptoms like body aches, stuffy nose, headaches, pressure sensation in the face, throat tightness and feels dry. Can a cold last this long or should I be looking for something else? 1 Is there any way to stop my period for a little while without a prescription? Are there any natural ways to stop my period without having to visit a local doctor? 1 - Loss: ContrastiveLoss with these parameters:
{ "distance_metric": "SiameseDistanceMetric.COSINE_DISTANCE", "margin": 0.5, "size_average": true }
Training Hyperparameters
Non-Default Hyperparameters
eval_strategy: stepsper_device_train_batch_size: 16per_device_eval_batch_size: 16num_train_epochs: 1warmup_ratio: 0.1fp16: Truepush_to_hub: Truebatch_sampler: no_duplicates
All Hyperparameters
overwrite_output_dir: Falsedo_predict: Falseeval_strategy: stepsprediction_loss_only: Trueper_device_train_batch_size: 16per_device_eval_batch_size: 16per_gpu_train_batch_size: Noneper_gpu_eval_batch_size: Nonegradient_accumulation_steps: 1eval_accumulation_steps: Nonetorch_empty_cache_steps: Nonelearning_rate: 5e-05weight_decay: 0.0adam_beta1: 0.9adam_beta2: 0.999adam_epsilon: 1e-08max_grad_norm: 1.0num_train_epochs: 1max_steps: -1lr_scheduler_type: linearlr_scheduler_kwargs: {}warmup_ratio: 0.1warmup_steps: 0log_level: passivelog_level_replica: warninglog_on_each_node: Truelogging_nan_inf_filter: Truesave_safetensors: Truesave_on_each_node: Falsesave_only_model: Falserestore_callback_states_from_checkpoint: Falseno_cuda: Falseuse_cpu: Falseuse_mps_device: Falseseed: 42data_seed: Nonejit_mode_eval: Falseuse_ipex: Falsebf16: Falsefp16: Truefp16_opt_level: O1half_precision_backend: autobf16_full_eval: Falsefp16_full_eval: Falsetf32: Nonelocal_rank: 0ddp_backend: Nonetpu_num_cores: Nonetpu_metrics_debug: Falsedebug: []dataloader_drop_last: Falsedataloader_num_workers: 0dataloader_prefetch_factor: Nonepast_index: -1disable_tqdm: Falseremove_unused_columns: Truelabel_names: Noneload_best_model_at_end: Falseignore_data_skip: Falsefsdp: []fsdp_min_num_params: 0fsdp_config: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}fsdp_transformer_layer_cls_to_wrap: Noneaccelerator_config: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None}deepspeed: Nonelabel_smoothing_factor: 0.0optim: adamw_torchoptim_args: Noneadafactor: Falsegroup_by_length: Falselength_column_name: lengthddp_find_unused_parameters: Noneddp_bucket_cap_mb: Noneddp_broadcast_buffers: Falsedataloader_pin_memory: Truedataloader_persistent_workers: Falseskip_memory_metrics: Trueuse_legacy_prediction_loop: Falsepush_to_hub: Trueresume_from_checkpoint: Nonehub_model_id: Nonehub_strategy: every_savehub_private_repo: Nonehub_always_push: Falsegradient_checkpointing: Falsegradient_checkpointing_kwargs: Noneinclude_inputs_for_metrics: Falseinclude_for_metrics: []eval_do_concat_batches: Truefp16_backend: autopush_to_hub_model_id: Nonepush_to_hub_organization: Nonemp_parameters:auto_find_batch_size: Falsefull_determinism: Falsetorchdynamo: Noneray_scope: lastddp_timeout: 1800torch_compile: Falsetorch_compile_backend: Nonetorch_compile_mode: Nonedispatch_batches: Nonesplit_batches: Noneinclude_tokens_per_second: Falseinclude_num_input_tokens_seen: Falseneftune_noise_alpha: Noneoptim_target_modules: Nonebatch_eval_metrics: Falseeval_on_start: Falseuse_liger_kernel: Falseeval_use_gather_object: Falseaverage_tokens_across_devices: Falseprompts: Nonebatch_sampler: no_duplicatesmulti_dataset_batch_sampler: proportional
Training Logs
| Epoch | Step | Training Loss | Validation Loss | all-mqp-test_cosine_ap |
|---|---|---|---|---|
| 0.6536 | 100 | 0.0137 | 0.0135 | - |
| 1.0 | 153 | - | - | 0.9474 |
Framework Versions
- Python: 3.11.11
- Sentence Transformers: 3.3.1
- Transformers: 4.47.1
- PyTorch: 2.6.0+cu124
- Accelerate: 1.2.1
- Datasets: 3.2.0
- Tokenizers: 0.21.0
Citation
BibTeX
Sentence Transformers
@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",
}
ContrastiveLoss
@inproceedings{hadsell2006dimensionality,
author={Hadsell, R. and Chopra, S. and LeCun, Y.},
booktitle={2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06)},
title={Dimensionality Reduction by Learning an Invariant Mapping},
year={2006},
volume={2},
number={},
pages={1735-1742},
doi={10.1109/CVPR.2006.100}
}