--- tags: - sentence-transformers - sentence-similarity - feature-extraction - generated_from_trainer - dataset_size:65360 - loss:ContrastiveLoss base_model: BSC-LT/mRoBERTa widget: - source_sentence: El agua se volvió turbia desde que uso el ozono. ¿A qué se debe? sentences: - >- 27 de septiembre de 2009 27 de septiembre de 2009Tegucigalpa, Honduras — En un comunicado del gobierno de facto hondureño, encabezado por Roberto Micheletti, se ha decretado un ultimatum de 10 días para que la embajada de Brasil defina el estatus del depuesto presidente Manuel Zelaya, quien permanece en la sede diplomática desde el lunes pasado. En el texto del comunicado se afirma: "ningún país puede tolerar que una embajada extranjera sea utilizada como base de mando para generar violencia y romper la tranquilidad, como el señor Zelaya lo ha estado haciendo desde su ingreso al territorio nacional", agregando: "nos veremos obligados a tomar medidas adicionales conforme al derecho internacional". - >- La nubosidad es una señal de que el ozono está haciendo su trabajo. Continúe ejecutando el filtro y desaparecerá en un par de días. La nubosidad también puede indicar un problema en el filtro. Verifique el filtro por daños y operación apropiada. Retrolavado si es necesario. - >- El filòsof i periodista Jordi Graupera ha guanyat la votació de Primàries Catalunya a Barcelona, amb 7.715 vots. El segon candidat més votat ha estat Adrià Alsina, ex-membre del secretariat de l'ANC, amb 1.933 vots. La votació va començar divendres a les 20.00 i s'ha acabat avui a les 20.00. - source_sentence: >- What is a term being used for organizations that are for the citizens, by the citizens? sentences: - >- The term "civil society organization" (CSO) has been used by a growing number of organizations, such as the Center for the Study of Global Governance. The term "citizen sector organization" (CSO) has also been advocated to describe the sector – as one of citizens, for citizens – by organizations such as Ashoka: Innovators for the Public. A more broadly applicable term, "Social Benefit Organization" (SBO) has been advocated for by organizations such as MiniDonations. - >- The number e is a famous irrational number and is one of the most important numbers in mathematics. e is the base of the Natural Logarithms. - >- In 1885, British claims to a West African sphere of influence received recognition from other European nations at the Berlin Conference. The following year, it chartered the Royal Niger Company under the leadership of Sir George Taubman Goldie. - source_sentence: ¿Cuándo se llevó a cabo la adquisición? sentences: - >- La operadora de telefonía móvil de Sao Paulo, Telesp Celular, controlada por Portugal Telecom, adquirió el control de la empresa brasileña Ceterp Celular, perteneciente al grupo español Telefónica, se informó hoy. En un aviso publicitario publicado hoy en la prensa local, Telefónica indica que la operación se hizo efectiva ayer, Martes, por un valor de 148,5 millones de reales (75,5 millones de dólares). La empresa vendida formaba parte de las Centrales Telefónicas de Ribeirao Preto (Ceterp), una pequeña compañía comprada en diciembre del año pasado por Telefónica en subasta pública. - >- Los ecologistas denuncian ante el TSJC la concesión por la Agència Catalana del' Aigua de caudales de la depuradora de Les Fonts para el futuro campo de Torrebonica. Adenc, que ya denunció el uso del agua, cree que han existido irregularidades en la concesión. - >- The word Anglican originates in ecclesia anglicana, a medieval Latin phrase dating to at least 1246 that means the English Church. There is no single "Anglican Church" with universal juridical authority, since each national or regional church has full autonomy. As the name suggests, the communion is an association of churches in full communion with the Archbishop of Canterbury. - source_sentence: >- What was introduced that made using Mac OS alternative operating systems easier? sentences: - >- and then to hand over control to a Mac OS-based bootloader application. Used even by Apple for A/UX and MkLinux, this technique is no longer necessary since the introduction of Open Firmware-based PCI Macs, though it was formerly used for convenience on many Old World ROM systems due to bugs in the firmware implementation.[citation needed] Now, Mac hardware boots directly from Open Firmware in most PowerPC-based Macs or EFI in all Intel-based Macs. - >- During the Napoleonic Wars in the late 18th century and early 19th century, Napoleon annexed territory formerly controlled by the Habsburgs and Savoys. In 1798 he established the Helvetic Republic in Switzerland; two years later he led an army across the St. Bernard pass and conquered almost all of the Alpine regions. - >- La visita coincideix amb un període de vaga a França per la reforma de les pensions que també afecta el col·lectiu que exerceix al Principat. La visita de Jean–Michel Blanquer a Andorra ha arrencat a primera hora amb una reunió amb el cap de govern, Xavier Espot. No se'n sap el contingut, però de segur que han parlat del reforç de la presència francesa a Andorra mitjançant el sistema educatiu. - source_sentence: Of pregnant women, how many are believed to be infected with HIV? sentences: - >- In 2004, the Swaziland government acknowledged for the first time that it suffered an AIDS crisis, with 38.8% of tested pregnant women infected with HIV (see AIDS in Africa). The then Prime Minister Themba Dlamini declared a humanitarian crisis due to the combined effect of drought, land degradation, increased poverty, and HIV/AIDS. - >- James Liebman, a professor of law at Columbia Law School, stated in 1996 that his study found that when habeas corpus petitions in death penalty cases were traced from conviction to completion of the case that there was "a 40 percent success rate in all capital cases from 1978 to 1995." Similarly, a study by Ronald Tabak in a law review article puts the success rate in habeas corpus cases involving death row inmates even higher, finding that between "1976 and 1991, approximately 47 percent of the habeas petitions filed by death row inmates were granted." - >- Si t'allotges a Casa da Pendôa tens aquestes possibilitats d'aparcament (sota disponibilitat):Pàrquing interior de pagament,Pàrquing exterior de pagament datasets: - langtech-innovation/trilingual_query_relevance 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 - cosine_mcc model-index: - name: SentenceTransformer based on BSC-LT/mRoBERTa results: - task: type: binary-classification name: Binary Classification dataset: name: trilingual query relevance dev type: trilingual_query_relevance_dev metrics: - type: cosine_accuracy value: 0.9214229867083659 name: Cosine Accuracy - type: cosine_accuracy_threshold value: 0.7342114448547363 name: Cosine Accuracy Threshold - type: cosine_f1 value: 0.9215354586857515 name: Cosine F1 - type: cosine_f1_threshold value: 0.7342114448547363 name: Cosine F1 Threshold - type: cosine_precision value: 0.9202182952182952 name: Cosine Precision - type: cosine_recall value: 0.9228563982277821 name: Cosine Recall - type: cosine_ap value: 0.9762691065142695 name: Cosine Ap - type: cosine_mcc value: 0.8428494369763666 name: Cosine Mcc license: apache-2.0 language: - ca - es - en --- # SentenceTransformer based on BSC-LT/mRoBERTa This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [BSC-LT/mRoBERTa](https://huggingface.co/BSC-LT/mRoBERTa) on the [trilingual_query_relevance](https://huggingface.co/datasets/crodri/trilingual_query_relevance) 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:** [BSC-LT/mRoBERTa](https://huggingface.co/BSC-LT/mRoBERTa) - **Maximum Sequence Length:** 512 tokens - **Output Dimensionality:** 768 dimensions - **Similarity Function:** Cosine Similarity - **Training Dataset:** - [trilingual_query_relevance](https://huggingface.co/datasets/crodri/trilingual_query_relevance) ### 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': 512, 'do_lower_case': False}) with Transformer model: RobertaModel (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("langtech-innovation/mRoBERTA_retrieval") # Run inference query ="Com ha dit Juncker que havia sigut Georgieva com a vicepresidenta?" sentences = ["La vicepresidenta de la Comissió Europea i responsable de Pressupostos i Recursos Humans, Kristalina Georgieva, ha presentat aquest divendres la seva dimissió i deixarà el càrrec a finals d'any per treballar al Banc Mundial. El president de la CE, Jean-Claude Juncker, ha anunciat en un comunicat que el comissari alemany Günther H. Oettinger assumirà la carpeta de Georgieva, a qui ha definit com una 'excel·lent vicepresidenta'. Amb la vacant de Georgieva, s'iniciarà el procés per nomenar un nou comissari búlgar, que haurà de ser avalat pel Parlament Europeu.",\ "El infierno del Atlético en Segunda División es especialmente duro para Kiko, precisamente el jugador que prestó su imagen a la campaña publicitaria con la que el club madrileño buscó el respaldo de su afición. El más carismático jugador rojiblanco hasta hace unos meses fue objeto el sábado por la noche de un intento de agresión a la salida del estadio, después de la humillante derrota ante el Murcia. Un grupo de los más radicales miembros del Frente Atlético le acusó de ser el principal responsable del descenso y le reprochó con suma dureza no colaborar económicamente con la peña para sufragar sus desplazamientos.",\ "Tras el infructuoso intento de realizar la marcha del domingo, los organizadores lanzaron un comunicado diciendo que 'no estamos asustados, estamos aquí, no cambiaremos (...) Ustedes están asustados, cambiarán y se acostumbrarán'. El İstanbul Onur Yürüyüşü, nombre local de la marcha del orgullo gay, fue organizado por primera vez en 2003, atrayendo según los reportes, entre decenas de miles y cien mil personas en 2014, año en que se celebró el último desfile y se toparía con una serie de bloqueos en los tres años siguientes. El año pasado, a los organizadores no se les brindó permiso para hacer la marcha tras los ataques militares que enfrentó Estambul, y en 2015 la marcha fue detenida cuando iba a comenzar, y la policía empleó chorros de agua y gas lacrimógeno para dispersar a los manifestantes."] embeddings_sentences = model.encode(sentences) embeddings_query = model.encode(query) # Get the similarity scores for the embeddings similarities = model.similarity(embeddings_sentences, embeddings_query) similarities tensor([[0.9194], [0.5663], [0.4800]]) ``` ## Evaluation ### Metrics #### Binary Classification * Dataset: `trilingual_query_relevance_dev` * Evaluated with [BinaryClassificationEvaluator](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.BinaryClassificationEvaluator) | Metric | Value | |:--------------------------|:-----------| | cosine_accuracy | 0.9214 | | cosine_accuracy_threshold | 0.7342 | | cosine_f1 | 0.9215 | | cosine_f1_threshold | 0.7342 | | cosine_precision | 0.9202 | | cosine_recall | 0.9229 | | **cosine_ap** | **0.9763** | | cosine_mcc | 0.8428 | ## Training Details ### Training Dataset * Dataset: [trilingual_query_relevance](https://huggingface.co/datasets/langtech-innovation/trilingual_query_relevance) at [32b70c9](https://huggingface.co/datasets/langtech-innovation/trilingual_query_relevance/tree/32b70c97d9bdaee980d2781718425d89fe1f350f) * Size: 61,231 training samples * Columns: sentence1, sentence2, and label * Approximate statistics based on the first 1000 samples: | | sentence1 | sentence2 | label | |:--------|:----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------| | type | string | string | int | | details | | | | * Samples: | sentence1 | sentence2 | label | |:------------------------------------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------| | Olvidé que tenía un bono e hice una nueva reserva. ¿Se puede aplicar mi bono y obtener un reembolso? | No, no puede aplicar el bono a una reserva que ya se ha pagado. | 1 | | De quina època és típic el clarobscur naturalista en l'obra de Velázquez? | La llum principal, com es dedueix per les ombres que s'aprecien, ve de davant de l'escena. En aquest quadre, ja s'observa l'inici de l'abandonament del clarobscur naturalista de la seva època sevillana. Els focus de llum que més destaquen formen una composició entre la corona d'Apol·lo, la llum de les flames del foc i els reflexos de l'armadura. | 1 | | How Much is The Distance from Nathia Gali to Murree? | The distance from Nathia Gali to Murree is approximately 35 kilometers. | 1 | * Loss: [ContrastiveLoss](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 #### trilingual_query_relevance * Dataset: [trilingual_query_relevance](https://huggingface.co/datasets/langtech-innovation/trilingual_query_relevance) at [32b70c9](https://huggingface.co/datasets/langtech-innovation/trilingual_query_relevance/tree/32b70c97d9bdaee980d2781718425d89fe1f350f) * Size: 15,348 evaluation samples * Columns: sentence1, sentence2, and label * Approximate statistics based on the first 1000 samples: | | sentence1 | sentence2 | label | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:-----------------------------| | type | string | string | int | | details | | | | * Samples: | sentence1 | sentence2 | label | |:----------------------------------------------------|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------| | ¿Cómo se cancela Diri? | Diri no es un servicio que requiere de un contrato forzoso, así que para cancelarlo solo se debe dejar de pagar. Al dejar de usar la línea por un tiempo de 12 meses, el servicio pasará a inactivo de forma automática. | 1 | | How did whitehead define "experience"? | He also argued that the most basic elements of reality can all be regarded as experiential, indeed that everything is constituted by its experience. He used the term "experience" very broadly, so that even inanimate processes such as electron collisions are said to manifest some degree of experience. In this, he went against Descartes' separation of two different kinds of real existence, either exclusively material or else exclusively mental. | 1 | | ¿Cómo te llaman? | Y tú con tus caras y tus nombres, nos dejaste tutearte. Fran, Bebeto, Aldana, Nando, Djukic, Mauro Silva... | 1 | * Loss: [ContrastiveLoss](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`: 2 - `per_device_eval_batch_size`: 2 - `num_train_epochs`: 4 - `warmup_ratio`: 0.1 - `fp16`: True - `load_best_model_at_end`: True - `gradient_checkpointing`: True #### All Hyperparameters
Click to expand - `overwrite_output_dir`: False - `do_predict`: False - `eval_strategy`: steps - `prediction_loss_only`: True - `per_device_train_batch_size`: 2 - `per_device_eval_batch_size`: 2 - `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`: 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`: 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} - `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`: True - `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
### Framework Versions - Python: 3.10.16 - Sentence Transformers: 3.4.1 - Transformers: 4.49.0 - PyTorch: 2.5.1+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} } ```