| | --- |
| | tags: |
| | - sentence-transformers |
| | - sentence-similarity |
| | - feature-extraction |
| | - generated_from_trainer |
| | - dataset_size:2437 |
| | - loss:ContrastiveLoss |
| | base_model: sentence-transformers/all-mpnet-base-v2 |
| | widget: |
| | - source_sentence: I am having troubles and confusing moments with my body and I am |
| | scared I may be pregnant by my research online and I really want some advice ? |
| | sentences: |
| | - 'Does Acyclovir cause ulcers when it is prescribed for genital herpes? ' |
| | - The confusing symptoms and online research points towards me being pregnant. Can |
| | I get a professional advice? |
| | - Do bariatric surgeries like gastric sleeve or Roux-en-Y surgery actually work |
| | in the long term? |
| | - source_sentence: It started with a headache the next day came dizziness when I move |
| | my eyes, soreness behind my eyes, 102 fever, slight cough. Help! |
| | sentences: |
| | - I had a headache and this was followe by dizziness on moving the eyes, soreness |
| | behind my eyes, high grade fever (102) and slight cough. Can you help me? |
| | - What are the signs of ovulation? |
| | - Why does it hurt when I shave my face? Can I do something else for it besides |
| | shaving in the direction of the hair growth? |
| | - source_sentence: How low can hemoglobin go before you need a transfusion? |
| | sentences: |
| | - 'I heard banana is rich in potassium. I am having diarrhea and can I take banana. ' |
| | - At what Hemoglobin levels, is a blood transfusion recommended? |
| | - What are the symptoms of eye cancer? |
| | - source_sentence: I'm 5 weeks pregnant and this morning had brownish spotting, my |
| | gyn said this is normal and ita was due to implantation, should I be worried? |
| | sentences: |
| | - I have abdominal cramps, spotting, nause and fatigue. I am on oral contraceptive |
| | pills. I take them regularly. My pregnancy test is negative. I dont believe it |
| | is implantation as I am not pregnant. Could it be withdrawal bleeding or do I |
| | have an STD? |
| | - 'What''s best for a 1 year old, breast milk or bottle milk? ' |
| | - I am 40, and I've had a breast lump in my right breast for about 4 years now. |
| | Could it be cancer? |
| | - source_sentence: My bm aren't solid but not quite loose. Looks more like for lack |
| | of better word "shredded" the why is this? |
| | sentences: |
| | - 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? |
| | - You might think I'm a bit paranoid but could you please help me with the five |
| | most common emergency surgeries in american teen girls? |
| | - What causes stringy and shredded stools? |
| | pipeline_tag: sentence-similarity |
| | library_name: sentence-transformers |
| | metrics: |
| | - cosine_accuracy |
| | - cosine_accuracy_threshold |
| | - cosine_f1 |
| | - cosine_f1_threshold |
| | - cosine_precision |
| | - cosine_recall |
| | - cosine_ap |
| | model-index: |
| | - name: SentenceTransformer based on sentence-transformers/all-mpnet-base-v2 |
| | results: |
| | - task: |
| | type: binary-classification |
| | name: Binary Classification |
| | dataset: |
| | name: all mqp test |
| | type: all-mqp-test |
| | metrics: |
| | - type: cosine_accuracy |
| | value: 0.8786885245901639 |
| | name: Cosine Accuracy |
| | - type: cosine_accuracy_threshold |
| | value: 0.7678120136260986 |
| | name: Cosine Accuracy Threshold |
| | - type: cosine_f1 |
| | value: 0.8796147672552167 |
| | name: Cosine F1 |
| | - type: cosine_f1_threshold |
| | value: 0.7446306943893433 |
| | name: Cosine F1 Threshold |
| | - type: cosine_precision |
| | value: 0.8810289389067524 |
| | name: Cosine Precision |
| | - type: cosine_recall |
| | value: 0.8782051282051282 |
| | name: Cosine Recall |
| | - type: cosine_ap |
| | value: 0.9474266832530879 |
| | name: Cosine Ap |
| | --- |
| | |
| | # SentenceTransformer based on sentence-transformers/all-mpnet-base-v2 |
| |
|
| | This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [sentence-transformers/all-mpnet-base-v2](https://huggingface.co/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](https://huggingface.co/sentence-transformers/all-mpnet-base-v2) <!-- at revision 9a3225965996d404b775526de6dbfe85d3368642 --> |
| | - **Maximum Sequence Length:** 384 tokens |
| | - **Output Dimensionality:** 768 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( |
| | (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: |
| |
|
| | ```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("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] |
| | ``` |
| |
|
| | <!-- |
| | ### 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 |
| |
|
| | #### Binary Classification |
| |
|
| | * Dataset: `all-mqp-test` |
| | * Evaluated with [<code>BinaryClassificationEvaluator</code>](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.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** | |
| | |
| | <!-- |
| | ## 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: 2,437 training samples |
| | * Columns: <code>text1</code>, <code>text2</code>, and <code>label</code> |
| | * Approximate statistics based on the first 1000 samples: |
| | | | text1 | text2 | label | |
| | |:--------|:----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:------------------------------------------------| |
| | | type | string | string | int | |
| | | details | <ul><li>min: 7 tokens</li><li>mean: 26.53 tokens</li><li>max: 75 tokens</li></ul> | <ul><li>min: 7 tokens</li><li>mean: 28.18 tokens</li><li>max: 119 tokens</li></ul> | <ul><li>0: ~49.00%</li><li>1: ~51.00%</li></ul> | |
| | * Samples: |
| | | text1 | text2 | label | |
| | |:-------------------------------------------------------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------------------------------------------------|:---------------| |
| | | <code>I discovered I get this weakness in my hand whenever I try to snap my fingers, slight pain runs across elbow and wrist?</code> | <code>When I try to snap my fingers there is weakness and pain across elbow and wrist? May I know what are the causes?</code> | <code>1</code> | |
| | | <code>If a mother has celiac should the daughter be tested?</code> | <code>What is Celiac disease?</code> | <code>0</code> | |
| | | <code>Hi im 18 and I would like to know what I would use or take to get taller?</code> | <code>Can growth hormone taken in minimal quantities increase height after 21 years in a male?</code> | <code>0</code> | |
| | * Loss: [<code>ContrastiveLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#contrastiveloss) with these parameters: |
| | ```json |
| | { |
| | "distance_metric": "SiameseDistanceMetric.COSINE_DISTANCE", |
| | "margin": 0.5, |
| | "size_average": true |
| | } |
| | ``` |
| | |
| | ### Evaluation Dataset |
| | |
| | #### Unnamed Dataset |
| | |
| | |
| | * Size: 610 evaluation samples |
| | * Columns: <code>text1</code>, <code>text2</code>, and <code>label</code> |
| | * Approximate statistics based on the first 610 samples: |
| | | | text1 | text2 | label | |
| | |:--------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:------------------------------------------------| |
| | | type | string | string | int | |
| | | details | <ul><li>min: 8 tokens</li><li>mean: 27.56 tokens</li><li>max: 70 tokens</li></ul> | <ul><li>min: 8 tokens</li><li>mean: 27.88 tokens</li><li>max: 91 tokens</li></ul> | <ul><li>0: ~48.85%</li><li>1: ~51.15%</li></ul> | |
| | * Samples: |
| | | text1 | text2 | label | |
| | |:-----------------------------------------------------------------------------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------| |
| | | <code>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?</code> | <code>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?</code> | <code>1</code> | |
| | | <code>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?</code> | <code>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?</code> | <code>1</code> | |
| | | <code>Is there any way to stop my period for a little while without a prescription?</code> | <code>Are there any natural ways to stop my period without having to visit a local doctor?</code> | <code>1</code> | |
| | * Loss: [<code>ContrastiveLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#contrastiveloss) with these parameters: |
| | ```json |
| | { |
| | "distance_metric": "SiameseDistanceMetric.COSINE_DISTANCE", |
| | "margin": 0.5, |
| | "size_average": true |
| | } |
| | ``` |
| | |
| | ### Training Hyperparameters |
| | #### Non-Default Hyperparameters |
| | |
| | - `eval_strategy`: steps |
| | - `per_device_train_batch_size`: 16 |
| | - `per_device_eval_batch_size`: 16 |
| | - `num_train_epochs`: 1 |
| | - `warmup_ratio`: 0.1 |
| | - `fp16`: True |
| | - `push_to_hub`: 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`: 16 |
| | - `per_device_eval_batch_size`: 16 |
| | - `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`: 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`: False |
| | - `fp16`: True |
| | - `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`: True |
| | - `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 | 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 |
| | ```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", |
| | } |
| | ``` |
| | |
| | #### ContrastiveLoss |
| | ```bibtex |
| | @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} |
| | } |
| | ``` |
| | |
| | <!-- |
| | ## 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.* |
| | --> |
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| | ## Model Card Contact |
| | |
| | *Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.* |
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