--- library_name: setfit tags: - setfit - sentence-transformers - text-classification - generated_from_setfit_trainer metrics: - accuracy widget: - text: HNDALCO INDUSTRIES LIMITED HIRAKUD Rs.2.000,00 3 Rp.200,00 Rupes Two Lekh only of Payment Amount (R) Amount (R) Amount (R) 3 20,000 NRW PE leonas perHo Pey Otter No.652 DL20.1220 3 20,000 PE No 1912 Rp. 20,000 0 SUSHI Hkad Aud -Smi 0 MOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMOMO - text: RT @kanaka - text: MATERIAL RECEIPT REPORT Jと思い challan Pote MRR/Roceipt S/MB/SPR/1516/0720 3 -3 JOL ZMS -3 24/SEP-14 15/096 JAL BALAI GALAJI OKYGAN LTO PO Cate: 24/SEP-14 24/SEP-14 Valle S. Descriotion/ (Rs.) Value WLMJANQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQUQU - text: MATERIAL REGENT x 14,000 14,000 MARI/Requip Nc x 14,000 14,000 MARI/Requip CHOCOPICY MURRICapplaus &HACTA MURRICapplaus &HACTA Cosignment Nc 150,000 Rp. 0 PO Dlace 23.Jun-16 Rp. 0 Pollow 23.902 Pollow Late x 1 Vadomine & CENTRAL COALIFELDS LIMITED x WGWGWG SUNDA: Dlace 31-AUG-16 Rate. 20 ItemCodei Destroy - Value (Ks.) SLI. Destroycine Destroyce MOMO 0.00 x 1396.00 55.00 COAL FROM WHURRY @020.00 1 1376.00 15706.00 EAVACUTON FACTULITY 333.50 1.00 2319.00 1397.00 1 0 13.90 7.00 0 137813.00 336.00 336.002.018 9776 -Philage ) - text: HINDALCO INDUSTRIES LIMITED HIRAKUD WORKS PAYMENT ORDER Pauto HOTOL SHEELA TOWERS SAWABALPUR VucherNQUA Nc. H369 JANCE by Cash/Choque/D./Tangle summer of R&S.84同意 & HZQUAYE Rupes Eight thousand four hundred/Cory one only Rupes of Pavoment Dtalls of Pavoment Amount Sxpemie of fooding &lodging charges Cor Companywa quest Rs. P. Bll Bll B.4411 8,44 8,44 8,44 Bll Bll Bll Bll Bll Bll Bll BW 8,44 Redi Bll 8,44 by AWhoGised by Allowed by Aproved by 8,44 DAd D&G D&G HEGAL BWBWG (E)B) BW) Allow Account Rc. P. (B)B)B)B)B)B) Sundang Chicken Gholds JER JER Stella Bake of India Sambbur JERGE TWGMBLIGO TWICE TWICE TWICE TWICE TWICE TWINCHECKETCHECKED by SG Squequequequequente Squente Squente Squente Squente Squente Squente Squente Squente Squente Squente Stella Stella pipeline_tag: text-classification inference: true base_model: BAAI/bge-small-en-v1.5 model-index: - name: SetFit with BAAI/bge-small-en-v1.5 results: - task: type: text-classification name: Text Classification dataset: name: Unknown type: unknown split: test metrics: - type: accuracy value: 1.0 name: Accuracy --- # SetFit with BAAI/bge-small-en-v1.5 This is a [SetFit](https://github.com/huggingface/setfit) model that can be used for Text Classification. This SetFit model uses [BAAI/bge-small-en-v1.5](https://huggingface.co/BAAI/bge-small-en-v1.5) as the Sentence Transformer embedding model. A [LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) instance is used for classification. The model has been trained using an efficient few-shot learning technique that involves: 1. Fine-tuning a [Sentence Transformer](https://www.sbert.net) with contrastive learning. 2. Training a classification head with features from the fine-tuned Sentence Transformer. ## Model Details ### Model Description - **Model Type:** SetFit - **Sentence Transformer body:** [BAAI/bge-small-en-v1.5](https://huggingface.co/BAAI/bge-small-en-v1.5) - **Classification head:** a [LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) instance - **Maximum Sequence Length:** 512 tokens - **Number of Classes:** 4 classes ### Model Sources - **Repository:** [SetFit on GitHub](https://github.com/huggingface/setfit) - **Paper:** [Efficient Few-Shot Learning Without Prompts](https://arxiv.org/abs/2209.11055) - **Blogpost:** [SetFit: Efficient Few-Shot Learning Without Prompts](https://huggingface.co/blog/setfit) ### Model Labels | Label | Examples | 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' MATBRIOL BRECEIPT REPORT Y INvoice No 1 S/MR/SPR/2122/1803 Invoice Date 1 S/MR/Acecipit Date: 02-AUG-21 1 02-AUG-21 Consimment No 261 x5 1 S/P/SPR/2122/0389 Consimment Date: 16-JUL-21 1 PO N. S/P/SPR/2122/0389 POWERGAN (INDIA) 1 22-MAY-21 Value / 17582 175820.00'
' MATERIAL RECEIPT REPORT @018-4636 3 S/MR/SPR/1516 Chaillam Nc @1-FEB-2016 2 06-FEB-16 Consiminent Nc @0-FRB216 2J S/PO/SPR/1516/1502 Consiminent Dece @0-KEB PO Nc S/PO/SPR/1516/1502 PO DATE: 27-JAN-16 Vendor NAME : KONARK ELEKTRONIX @quantity Value S. Descrigi n/ Received Rejuce Delivered Retur Rate/Unit (Rs.) 30000 1 VET @14.5% B341.50 SICHENG MAKE HEC FUSE. 100 @040 1 1209.52 Amp.S.TYPE -3NAP B300-YYE @14 1 1209.52 DELIVERY DATE @179.00 2 SUSPOEPICYE @17.00 1 1209.52 P BIST. QTY/CC @07.M @079 80.000 2 9551.02 SIEMONG MAKE BIMETAL THERMAL @0.000 2 VET @14.5% 3591.20 BELLARLAD JUSBO2-KE -S @14.5% 3 520.72 -FBB-16 @14.502 3 52.072 P07-EL @17.0 1 52.072 P07-EL @11.92 2 411.92 13662.94 411.92 13662.94 1972517'
' MATERIAL RECKIPT BEPORT 1 00148/2122 1 S/MB/SPR/2122/1850 Invoice Date MRR/Aceipt Date: 04-AUG-21 AUG 2021 11 04-AUG-21 Consimment Nc Duce: PO N: S/PO/SPR/2122/0844 DATED PO DATE: 10-JUL-21 10-40 V.H. POLYMERS 1 1788 1 10-40 ITEM / SLI. -Quantity SLI. - Decoripi toxicallow/ Succi Delivered Retur Rate/Unit SKEET NONMETALIC TYPE SGPATCH BOX SATCH 0.00 1 ISI Taxe188 34138.00 JULILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILI'

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' MCLIPLE Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie Cookie 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' Original Box Buvez/ Duplicate Box Investice @MCL 3 93,000 suppliece MCL suppliece MADEMIZED CHOCO SPICK VICE. THOUS NICE.COMPANY SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICY CHOCO SPICYCE CHOCO SPICYCE CHOCO SPICYCE CHOCO SPICYCE CHOCO SPICYCE CHOCO SPICYCE CHOCO SUSPICYCOCOCOCOCOCOCO SUSPICYCOCOCOCOCOCOCO SUSPICYCOCOCOCOCOCO SUSPICYCOCOCOCOCO SUSPICYCOCOCOCOCO SUSPICYCOCOCOCO SUSPICYCOCOCOCO SUSPICYCOCOCOCO SUSPICYCOCOCO SUSPICYCOCOCO SUSPICYCOCOCO SUSPICYCOCOCO SUSPICYCOCOCO SUSPICYCOCOCO SUSPICY'
' (COUR) 93103AH52 MCLIPPIC Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level Level'

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' HNDALCO INDUSTRIES LIMITED HIRAKUD PAYMENT ORDER SAWALEWARI PHARMACENTRALS 1 Payto SAMALESWANGAUPUR 1 - BADYANATH CHOWK SAMBALPUR 1 -210% Emplo.SCode N.Gang HIRAKUD CaghCheuud D.I/Transfer The sun of (R.163,701.72) 163556 1 A.P.V.N.NallullahG3 Rupes ONE LKING SIXY THRKEWENT HUNDRED ONE AND SEYWNYYAISE ONLY Details of Pavment of Ayment Dellate Amount CAST OF UNAVAILABLE MEDICINCES PURGHASE FROM OUTSIDE 1 Ra.194,83.00 FOR OUR EMPLOYEE FROM D.11.08: 2021 20.08-2011 1 - INVOLICE NO-0121 RATE & DISCOUNT 16% ON WASHUUM RETAIL PRICE Rs. 1 (311.28) 13.000 AQ. Aproved by 1 Avo Avo Avo Avo Avo Avo Avo Avo Avonut Deploy Happ Happ. FEM Happ. FEM Happ. Sambalur Cluse Ucsa Amount 2.04ML Rs. 1 1,94,836.00 SKE Bunk of India Bun @Minitie @Mikc discoun R. (31.18.26) 1 Rs. (311.26) 1635.00 (318) 1635.00 1635.6 by Cheese Account Cheese Cheese Cheese Cheese Cheese Cheese Cheese Cheese Cheese Cheese Cheese Cheese Cheese Cheese Cheese Cheese Cheese Cheese Cheese Cheese Cheese Cheese Cheese Cheese Cheese Cheese Cheese Cheese Cheese Cheese Sque Sgnature Sgnature Strate 7de Sgnature 7deQKQKQE 1 (8,8701) 6,87012'
' HNDALCO INDUSTRIES LIMITED HIRAKUD PAYMENT ORDER PAYO DR. SUBATA CHARTERJEE Cash Vi.N. HP.Nov./S.Code No. 2274 Rp. V.Nchovequen D/Transfertie sum of Rs.3,500.00 Rp.3,500.00 Rupess THREE THOUSAND FIVE HUNDRED ONLY DATE DATE DATE DATE DAYOUN Amount DAYON BKPENSES ON AMBULANCE TO TAKE FOR M R. K. BEHERA A A A Akka 3.00.00 Rp.3,500.00 EMP.N.O. 030 DEPT.MECHANICAL MANT HIRAKUD TOUTIKA MEDICAL BSR OT OT OTOLizace LIF DESEBLIC COMPANY 13 LIT DILLI DIRLEBEL BILL NO.45636.8 DRYER SKENGAL DVRER DVRER DVR DVR DVR DVR SPICY DVR DVR DVR SPICY DVR DVR DVR DVR DVR DVR DVR DVR DVR DVR DVR DVR DVR DVR D DVR D D 3.00.00.00 BK.00.00 BK.00 BK.00.00 BK.00 BK.00 BK.00 BK.00.00 BK.00 BK.00 BK.00M DVR DVR DQUA ML Rs..500.00 ML BK.500.00 Rs..500.00.500.00) Sque Squente JG.50.50.00 Rp. 3,500.00'
' HNDALCO INDUSTRIES LIMITED HIRAKUD PAYMENT ORDER THE NEW INDIA ASSURANTE CO.LTD. Stie.B Caoh V.N.I D.Affensietie sun of N144 44,073.00 1.00 1.00 3035.0018 Rupess Pory Four Thousang Seventey Three Only DATE Distus of Payment Amount Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow Allow A'

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| ## Evaluation ### Metrics | Label | Accuracy | |:--------|:---------| | **all** | 1.0 | ## Uses ### Direct Use for Inference First install the SetFit library: ```bash pip install setfit ``` Then you can load this model and run inference. ```python from setfit import SetFitModel # Download from the 🤗 Hub model = SetFitModel.from_pretrained("Gopal2002/setfit_zeon_3456") # Run inference preds = model(" RT @kanaka") ``` ## Training Details ### Training Set Metrics | Training set | Min | Median | Max | |:-------------|:----|:---------|:----| | Word count | 2 | 123.7582 | 762 | | Label | Training Sample Count | |:------|:----------------------| | 3 | 16 | | 4 | 24 | | 5 | 22 | | 6 | 29 | ### Training Hyperparameters - batch_size: (32, 32) - num_epochs: (2, 2) - max_steps: -1 - sampling_strategy: oversampling - body_learning_rate: (2e-05, 1e-05) - head_learning_rate: 0.01 - loss: CosineSimilarityLoss - distance_metric: cosine_distance - margin: 0.25 - end_to_end: False - use_amp: False - warmup_proportion: 0.1 - seed: 42 - eval_max_steps: -1 - load_best_model_at_end: False ### Training Results | Epoch | Step | Training Loss | Validation Loss | |:------:|:----:|:-------------:|:---------------:| | 0.0052 | 1 | 0.2983 | - | | 0.2604 | 50 | 0.1069 | - | | 0.5208 | 100 | 0.0221 | - | | 0.7812 | 150 | 0.0063 | - | | 1.0417 | 200 | 0.0039 | - | | 1.3021 | 250 | 0.0029 | - | | 1.5625 | 300 | 0.003 | - | | 1.8229 | 350 | 0.0027 | - | ### Framework Versions - Python: 3.10.12 - SetFit: 1.0.2 - Sentence Transformers: 2.2.2 - Transformers: 4.35.2 - PyTorch: 2.1.0+cu121 - Datasets: 2.16.1 - Tokenizers: 0.15.0 ## Citation ### BibTeX ```bibtex @article{https://doi.org/10.48550/arxiv.2209.11055, doi = {10.48550/ARXIV.2209.11055}, url = {https://arxiv.org/abs/2209.11055}, author = {Tunstall, Lewis and Reimers, Nils and Jo, Unso Eun Seo and Bates, Luke and Korat, Daniel and Wasserblat, Moshe and Pereg, Oren}, keywords = {Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences}, title = {Efficient Few-Shot Learning Without Prompts}, publisher = {arXiv}, year = {2022}, copyright = {Creative Commons Attribution 4.0 International} } ```