SentenceTransformer based on microsoft/mpnet-base

Model Details

Model Description

• Model Type: Sentence Transformer
• Base model: microsoft/mpnet-base
• Maximum Sequence Length: 512 tokens
• Output Dimensionality: 768 dimensions
• Similarity Function: Cosine Similarity
• Training Dataset:
  • json

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': 512, 'do_lower_case': False, 'architecture': 'PeftModelForFeatureExtraction'})
  (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)

Evaluation

Metrics

Triplet

• Datasets: antibiotics_test and mpnet-base-smartbots/iter2
• Evaluated with TripletEvaluator

Training Details

Training Dataset

json

• Dataset: json
• Size: 80 training samples
• Columns: anchor, positive, and negative
• Approximate statistics based on the first 80 samples:

  	anchor	positive	negative
  type	string	string	string
  details	min: 9 tokens mean: 16.14 tokens max: 33 tokens	min: 48 tokens mean: 125.65 tokens max: 218 tokens	min: 48 tokens mean: 122.97 tokens max: 211 tokens

• Samples:

  anchor	positive	negative
  Which two macrolide antibiotics are frequently detected in surface water samples?	seems to undertake a similar fate in the environment.[object Object]Nevertheless, due to stronger adsorption, with higher emergence in sediment, its occurrence in the surface water is lower[object Object][71]. The use of tetracyclines, mainly as medicated premix and oral solution for food-producing animals [72], and the very[object Object]low bioavailability (e.g. in pig feed) [43] contribute to increasing its release into the environment. Regarding macrolides,[object Object]erythromycin and clarithromycin exhibit a remarkable frequency of detection in surface water samples. The most	Nonetheless, besides the sorption capacity, these antibiotics have high solubility in water. Crucial routes for these[object Object]substances into the environment are manure from animal production and sewage sludge from wastewater treatment[object Object]plant (WWTP) used as fertilisers. Therefore, these substances have been evidenced in topsoil samples [68]. These[object Object]quinolones and other antibiotics, for instance, norfloxacin and tetracycline, have been identified in groundwater samples[object Object]despite being influenced by sorption processes. They were not readily degraded; instead, the input into groundwater
  What antimicrobial drugs were identified in the survey besides macrolides?	is one of the most frequently pharmaceutical in representative rivers [74,75]. The three macrolides identified in our[object Object]detection survey are included since 2018 in the first 'watch list' [76].[object Object]Another group of antimicrobial drugs identified in our survey were sulfamethoxazole/trimethoprim and sulfamethazine.[object Object]Sulfamethoxazole/trimethoprim are often used combined since the effectiveness of sulfonamides is enhanced. In the[object Object]present study, the detection of both substances was comparable; however, trimethoprim was detected in groundwater.	upstream samples obtained in rural locations was demonstrated and could be attributed to a low efficiency in the urban[object Object]wastewater treatment plants or due to agricultural pressure.[object Object]The higher frequency of detection for most substances was observed in the Ave river and Ria Formosa, confirming that[object Object]several effluents impact these water bodies from urban wastewater treatment plants and livestock production.[object Object]Pharmacokinetic characteristics may represent key features in understanding antibiotics occurrence [62]. Most antibiotics
  How long was the observational period of the antibiotic survey in Portugal?	of antibiotics and their metabolites in surface- groundwater. It seeks to reflect the current demographic, spatial, drug[object Object]consumption, and drug profile on an observational period of 3 years in Portugal. The greatest challenge of this survey[object Object]data will be to promote the ecopharmacovigilance framework development shortly to implement measures for avoiding[object Object]misuse/overuse of antibiotics and slow down emission and antibiotic resistance.[object Object]2. Results[object Object]2.1. Frequency of Detections:[object Object]Antibiotics/Enzyme-Inhibitors and Abacavir[object Object]in Surface-Groundwater	despite being influenced by sorption processes. They were not readily degraded; instead, the input into groundwater[object Object]could be due to livestock farming pressure, namely by spreading manure in the soil or the possible sewage sludge[object Object]application in the area. High clay and low sand content in soils can decrease the mobility of pharmaceuticals, which is[object Object]attributed to clay intense exchange capacity. Thus, soil properties (e.g. particle composition) are a significant, influential

• Loss: MultipleNegativesRankingLoss with these parameters:
  json

  1{ 2 "scale": 20.0, 3 "similarity_fct": "cos_sim" 4}

Evaluation Dataset

json

• Dataset: json
• Size: 20 evaluation samples
• Columns: anchor, positive, and negative
• Approximate statistics based on the first 20 samples:

  	anchor	positive	negative
  type	string	string	string
  details	min: 11 tokens mean: 16.4 tokens max: 25 tokens	min: 76 tokens mean: 113.65 tokens max: 148 tokens	min: 89 tokens mean: 118.8 tokens max: 162 tokens

• Samples:

  anchor	positive	negative
  What percentage of unchanged excretion did the most significant number of detected substances show?	coefficients were not available for lincomycin, clavulanic acid and cilastatin.[object Object]Physicochemical properties of detected pharmaceuticals.[object Object]1 Data retrieved from [16]; 2 Data retrieved from [17]; 3 Data retrieved from [18]; 4 Data retrieved from [19]; 5[object Object]Data retrieved from [20];[object Object]6 Data retrieved from [21]; 7 Data retrieved from [22]; 8 Data retrieved from [23]; 9 Data retrieved from [24]; 10[object Object]Data retrieved from [25];[object Object]NA-not available.[object Object]The most significant number of detected substances showed a percentage of unchanged excretion higher than 40%.	1. Introduction[object Object]Antibiotics are a critical component of human and veterinary modern medicine, developed to produce desirable or[object Object]beneficial effects on infections induced by pathogens. Like most pharmaceuticals, antibiotics tend to be small organic[object Object]polar compounds, generally ionisable, ordinarily subject to a metabolism or biotransformation process by the organism to[object Object]be eliminated more efficiently [1,2]. The excretion of these compounds and their metabolites occurs mainly through urine,
  How many kilograms of abacavir were detected in Portugal in 2017?	Regarding the different regions, it has been concluded that North and West/Tejo were the regions with the higher[object Object]consuming values. Both regions presented a significant value (33%) for the abacavir. For the detected antiviral abacavir,[object Object]an amount of 1458 kg has been observed.[object Object]Regarding antibiotics used in veterinary medicine, the regional amount was not available. Likewise, due to the reported[object Object]missing quantity for sulfamethazine, the sulfonamides group has been matched.[object Object]Consumption (Kg) of the detected pharmaceuticals in Portugal (2017).	43%[object Object](3/7), enrofloxacin, norfloxacin, trimethoprim, lincomycin (29% (2/7), abacavir and tetracycline[object Object]14% (1/7). The enzyme inhibitors, namely clavulanic acid and cilastatin, were detected once in an urban region located[object Object]well. This catchment point showed the most significant[object Object]number of pharmaceuticals. West/Tejo and Centre were the regions with the most considerable number of substances in[object Object]groundwater, accounting for 43%. All groundwater[object Object]samples were contaminated by at least one antibiotic. Supplemental Tables S2 and S4 contain a detailed description of[object Object]the
  What must marketing authorisation procedures for medicines include since 2006?	substances in passive samplers [7]. Since 2006, marketing authorisation procedures for both human and veterinary[object Object]medicines must include an environmental risk assessment that comprises a prospective exposure assessment,[object Object]underestimating the possible impact and the occurrence of antibiotics after years of consumption. Ultimately, the potential[object Object]risk may not be correctly anticipated. It becomes urgent to generate new data, mainly to refine exposure assessments.[object Object]As much as the specificities of each member state should be considered this issue has become one of the European	clarithromycin/erythromycin, tetracycline, sulfamethoxazole, and abacavir. In groundwater, enrofloxacin/ciprofloxacin,[object Object]norfloxacin, trimethoprim, lincomycin, abacavir and tetracycline were recovered. Metabolites were not detected in water[object Object]bodies. Noticeable was the detection of enzyme inhibitors, tazobactam and cilastatin, which are both for exclusive[object Object]hospital use. The North region and Algarve (South) were the areas with the most significant frequency of substances in[object Object]surface water. The relatively higher detection of substances downstream of the effluent discharge points compared with a

• Loss: MultipleNegativesRankingLoss with these parameters:
  json

  1{ 2 "scale": 20.0, 3 "similarity_fct": "cos_sim" 4}

Training Hyperparameters

Non-Default Hyperparameters

• eval_strategy: steps
• per_device_train_batch_size: 10
• per_device_eval_batch_size: 10
• num_train_epochs: 1
• warmup_ratio: 0.1
• fp16: True
• batch_sampler: no_duplicates

All Hyperparameters

Training Logs

Framework Versions

• Python: 3.11.11
• Sentence Transformers: 5.0.0
• Transformers: 4.51.3
• PyTorch: 2.6.0+cu124
• Accelerate: 1.5.2
• Datasets: 3.6.0
• Tokenizers: 0.21.1

Citation

BibTeX

Sentence Transformers

MultipleNegativesRankingLoss