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--- |
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library_name: setfit |
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tags: |
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- setfit |
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- sentence-transformers |
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- text-classification |
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- generated_from_setfit_trainer |
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metrics: |
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- accuracy |
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- text: <s_cord-v2><s_menu><s_nm> UNDALCO INDUSTRIES LIIMITED</s_nm><s_discountprice> |
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-*OQU<sep/><s_nm> PYCHE DESIGNCE PURCHASE ORDER</s_nm><sep/><s_nm> WHOCO SUSHINGGA |
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POWER</s_nm><s_price> SUSHINGGANGHONGHONGHONG POWER</s_nm><s_price> SUSHINGGANGHONGHONG |
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POWER</s_nm><s_price> SUSHINGGANGGANGGANGGANGGANGGANGGANGGANGGA SUSHINGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGA |
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2</s_cnt><s_price> A</s_price><sep/><s_nm> BLOOM Combustion India Putu</s_nm><s_unitprice> |
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- text: <s_cord-v2><s_menu><s_nm> HINA DLCO INDUSTRIES LIMITED</s_nm><s_price> SUSHIZE</s_price><sep/><s_nm> |
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PONE CHOCO CHOCO CHOCO CHOCO CHOCO CHOCO CHOCO CHOCO CHOCO CHOCO CHOCO CHOCO CHOCO |
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pipeline_tag: text-classification |
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inference: true |
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base_model: BAAI/bge-small-en-v1.5 |
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model-index: |
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- name: SetFit with BAAI/bge-small-en-v1.5 |
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results: |
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- task: |
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type: text-classification |
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name: Text Classification |
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dataset: |
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name: Unknown |
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type: unknown |
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split: test |
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metrics: |
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- type: accuracy |
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value: 1.0 |
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name: Accuracy |
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--- |
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# SetFit with BAAI/bge-small-en-v1.5 |
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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. |
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The model has been trained using an efficient few-shot learning technique that involves: |
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1. Fine-tuning a [Sentence Transformer](https://www.sbert.net) with contrastive learning. |
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2. Training a classification head with features from the fine-tuned Sentence Transformer. |
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## Model Details |
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### Model Description |
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- **Model Type:** SetFit |
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- **Sentence Transformer body:** [BAAI/bge-small-en-v1.5](https://huggingface.co/BAAI/bge-small-en-v1.5) |
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- **Classification head:** a [LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) instance |
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- **Maximum Sequence Length:** 512 tokens |
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- **Number of Classes:** 3 classes |
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<!-- - **Training Dataset:** [Unknown](https://huggingface.co/datasets/unknown) --> |
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<!-- - **Language:** Unknown --> |
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<!-- - **License:** Unknown --> |
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### Model Sources |
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- **Repository:** [SetFit on GitHub](https://github.com/huggingface/setfit) |
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- **Paper:** [Efficient Few-Shot Learning Without Prompts](https://arxiv.org/abs/2209.11055) |
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- **Blogpost:** [SetFit: Efficient Few-Shot Learning Without Prompts](https://huggingface.co/blog/setfit) |
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### Model Labels |
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| Label | Examples | |
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|:------|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------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| 2 | <ul><li>'<s_cord-v2><s_menu><s_nm> M/S. JOSEPH SUNA</s_nm><s_num> DATABI<sep/><s_nm> Tankipaa.MIRAKU SAMBALPUR.768Q16</s_nm><s_num> DMB Nb N.9861345883<sep/><s_nm> Deals Which :Altypes of ChickenGNALOR REGUMING)</s_nm><s_num> DISALI<sep/><s_nm> WINNALIZED</s_nm><s_num> CHOCO SUSPECIALIZE</s_nm><s_num> TWICENCHE<sep/><s_nm> SHRANGKANG POWER</s_nm><s_num> LATHOCO TWICENKO:</s_nm><s_num> JERYUNG CHOCO TWICENKO:</s_nm><s_num> JERYUNG HZYGANGKAN<sep/><s_nm> DIFF-SAWALAPUKU SAMBALPUR.76801GHOLIZEG DATE</s_nm><s_num> DATE</s_nm><s_num> DATE:</s_nm><s_num> 01/01/01/01/01/01/01/01/01/01/01/01/01/01/01/01/01<sep/><s_nm> PAN No.:</s_nm><s_num> PPODATE</s_nm><s_num> 01/01/01/01/01/01/01/01/01/01/01<sep/><s_nm> DATE OPSE<sep/><s_nm> HANDUPPOWER</s_nm><s_num> 30.12221</s_num><s_price> 1,945.00</s_price><sep/><s_nm> SUSPENGGANGURG.GUSTAGUR GUSTAGANGKANGURGUSTAGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTGUTG'</li><li>'<s_cord-v2><s_menu><s_nm> GST INVOLICE</s_nm><s_price> ORIGINAL FOR KEGINGLI</s_nm><s_price> WOUCE BREGRAMING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPINGLIPPING SUSHIPPING SUSHIPPINGLIPPING SUSHIPPING SUSHIPPINGLIPPING SUSHIPPINGLIPPING SUSHIPPINGLIPPING SUSHIPPINGLIPPING SUSHIPPINGLIPPING SUSHIPPINGLIPPING SUSHIPPINGLIPPING SUSHIPPINGLIPPING SUSHIPPINGLIPPING SUSHIPPINGLIPPING SUSHIPPINGLIPPING SUSHIPPINGLIPPING SUSHIPPINGLIPPING SUSHIPPINGLIPPING SUSHIPPINGLIPPING SUSHIPPINGLIPPING SUSHIPPINGLIPPING SUSHIPPINGLIPPING SUSHIPPING SUSHIPPINGLIPPING SUSHIPPING SUSHIPPINGLIPPING SUSHIPPING SUSHIPPINGLIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHIPPING SUSHI'</li><li>'<s_cord-v2><s_menu><s_nm> TAX INVOICE</s_nm><s_price> ORIGINAL FOR AQUALIZE</s_nm><s_price> SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO SUSHIKO '</li></ul> | |
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| 1 | <ul><li>'<s_cord-v2><s_menu><s_nm> UNDALCO INDUSTRIES LTB.</s_nm><s_unitprice> HIRAKUD POWER</s_nm><sep/><s_nm> ASH WPTCH BRIOGE</s_nm><s_unitprice> TIMOL CATE BRIOUS DATE</s_nm><s_unitprice> SUSCEE</s_nm><s_unitprice> SUSCE</s_unitprice><s_cnt> 1</s_cnt><s_price> SUSCE</s_price><sep/><s_nm> MSCED</s_nm><s_unitprice> SUSCEE</s_nm><s_unitprice> SUSCE</s_unitprice><s_cnt> 1</s_cnt><s_price> SUSCE</s_price><sep/><s_nm> MICHI CHOCO KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KESE KE'</li><li>'<s_cord-v2><s_menu><s_nm> UNDALCO INDUSTRIES LTB.</s_nm><s_unitprice> HIR A KD POWER</s_nm></s_sub><sep/><s_nm> ASH WEICH BRIOGE</s_nm><s_unitprice> 16.36.36m2</s_unitprice><s_cnt> AGE IMPL CAST SUSIC :RING LETS SUSIC SUSIC SUSIC SUSIC SUSIC SUSIC SUSCCE</s_nm></s_sub><sep/><s_nm> MSCHO</s_nm><s_unitprice> 13.45</s_unitprice><s_cnt> 1.36.36</s_cnt><s_price> 6.36</s_price><sep/><s_nm> SUSPICY TEMPLE</s_nm><s_unitprice> 14.50.13.502</s_unitprice><s_cnt> 1.00</s_cnt><s_price> 0.00</s_price><sep/><s_nm> BREAT TRIPSE TO WBLE</s_nm><s_unitprice> 13.35.5cs</s_unitprice><s_cnt> 1.00.00</s_cnt><s_price> 0.00</s_price><sep/><s_nm> BREATTY TRIPSE</s_nm><s_unitprice> 13.50</s_unitprice><s_cnt> 1.00.00.00.00</s_cnt><s_price> 0.00</s_price><sep/><s_nm> BREATTY TRIPSE</s_nm><s_unitprice> 13.50.50</s_unitprice><s_cnt> 1.00.00.00</s_cnt><s_price> 0.00</s_price><sep/><s_nm> BREATTY TRIPSE</s_nm><s_unitprice> 13.50.50</s_unitprice><s_cnt> 1.00.00.00</s_cnt><s_price> 0.00</s_price><sep/><s_nm> BREATTY TRIPSE</s_nm><s_unitprice> 13.50.50</s_unitprice><s_cnt> 1.00.00</s_cnt><s_price> 0.00</s_price><sep/><s_nm> BREYA TEMPLE</s_nm><s_unitprice> 13.50</s_unitprice><s_cnt> 1.00.00</s_cnt><s_price> 0.00</s_price><sep/><s_nm> BREYA TEMPLE ITEMBLE<s_cnt> 1.00</s_cnt><s_price> 0.00</s_price><sep/><s_nm> BREYANG TEMPLE ITEMBLE<s_cnt> 1.00.00</s_cnt><s_price> 0.00</s_price><sep/><s_nm> BREYANG TEMPLE ITEMBLE<s_cnt> 1.00</s_cnt><s_price> 0.00</s_price><sep/><s_nm> BREATTYPE 3.00.00</s_cnt><s_price> 0.00</s_price><sep/><s_nm> BREATSUPER</s_nm><s_unitprice> 13.35.5cs</s_unitprice><s_cnt> 1.00</s_cnt><s_price> 5.940</s_price><sep/><s_nm> 0.00</s_price><sep/><s_nm> BRETYPETROPICPICPICPICYE</s_nm><s_unitprice> 13.50</s_cnt><s_price> 0.00</s_price><sep/><s_nm> BREATTYPE 3.00.00</s_cnt><s_price> 0.00</s_price><sep/><s_nm> BREATPICYEPIC ITEMBLE<s_cnt> 1.00</s_cnt><s_price> 0.00</s_price><sep/><s_nm> BREATSUPER</s_nm><s_unitprice> 13.50</s_cnt><s_price> 5.940.00</s_price></s_menu><s_sub_total><s_subtotal_price> 0.00</s_subtotal_price><s_tax_price> 13.50</s_tax_price></s_sub_total><s_total><s_total_price> 31.00</s_cnt><s_price> BK.00</s_total_price></s_total>'</li><li>'<s_cord-v2><s_menu><s_nm> ORI ZHDLE TOMI O JAPAN SUSHIKA JERYA CHARGE</s_nm><s_unitprice> @SAKASAKASAKA SPICKING SUSHI JER</s_nm><s_unitprice> @SAKASAKASAKASAKASAKA SPICKING SUSHI JER</s_nm><s_unitprice> @SAKASAKASAKASAKASAKA SPICKING SUSHI JER</s_nm><s_unitprice> @SAKASAKASAKASAKASAKASAKASAKASAKASAKASAKASAKASAKASAKASAKASAKASAKASAKASAKASAKASAKASAKASAKASAKASAKASAKASAKASAKASAKASAKASAKASAKASAKASAKASAKASAKASAKASAKASAKASAKASAKASAKASAKASAKASAKASAKAStakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakattakat'</li></ul> | |
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| 0 | <ul><li>'<s_cord-v2><s_menu><s_nm> HANDALCO 이미지ES LIMITED</s_nm><s_price> SUNDAYGHOCO SUSHIZEH CINCEHANGKAGHOCO SUSHIZEHANGKAGHOUSHIZEHANGKAGHOUSHIZEHANGKAGHOUSHIZEHANGKAGHOUSHIZEHANGKAGHOUSHIZEHANGKANG PURCHASE ORDER</s_nm><sep/><s_nm> WANTE CHOCO CAKE CONSULATANCE PYI LOTHO NUMPIC UPICK CHOCO CHOCO CHOCOCO SUSHIZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHER</s_nm><s_discountprice>Nt.Minitie HGHOCEHINE</s_nm><s_discountprice>N.Minitie HGUMAGHO</s_nm><s_discountprice>N</s_nm><s_discountprice>N.Minitie HUMAGHO</s_nm><s_discountprice>N</s_nm><s_discountprice>N</s_discountprice><s_price> 436.0</s_price><sep/><s_nm> OxMini WHEN HUMAGHUNG</s_nm><s_discountprice> SUSHIZEHITEGHOUSHILIZEHENCE COTTING THOGEHGHOCO SUSHIZEHITEGHTGHOLIZEHGHOLIZEHGHOLIZEHGHOLIZEHGPICYGLIZEHGHTG SOUTING SUSHIZEHITEGHTGHOLIZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEHZEH'</li><li>'<s_cord-v2><s_menu><s_nm> WINGllaco Industries Limited</s_nm><s_unitprice> LIKING PICCE CHOCOLOGY VICE</s_nm><s_unitprice> LIKING SUSHIBILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILILI'</li><li>'<s_cord-v2><s_menu><s_nm> HINDALCO INDUSTRIES LIMITED</s_nm><s_price> GSTING&NAACHI201</s_price><sep/><s_nm> WBABUPOWER HEROGUSTAMPURGANGKANCE CHOCOLOGALINGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGANGGA'</li></ul> 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## Evaluation |
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### Metrics |
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| Label | Accuracy | |
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|:--------|:---------| |
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| **all** | 1.0 | |
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## Uses |
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### Direct Use for Inference |
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First install the SetFit library: |
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```bash |
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pip install setfit |
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``` |
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Then you can load this model and run inference. |
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```python |
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from setfit import SetFitModel |
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# Download from the 🤗 Hub |
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model = SetFitModel.from_pretrained("Gopal2002/setfit_zeon") |
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# Run inference |
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preds = model("<s_cord-v2><s_menu><s_nm> HINALCO INDUSTRIES LTB. HIRAKUR</s_nm><s_unitprice> 1344</s_unitprice><s_cnt> 1</s_cnt><s_price> 4,436</s_price><sep/><s_nm> ASTRICA BRIOC</s_nm><s_unitprice> 12.082</s_unitprice><s_cnt> 1</s_cnt><s_discountprice> 12.027</s_discountprice><s_price> SUSPICY TEMPURA HIRAKUR</s_nm><s_unitprice> 12.027.00.0020</s_discountprice><s_price> PAK SUSHI HIRAKURURUR</s_nm><s_unitprice> 12.027.00.0020</s_unitprice><s_cnt> 1</s_cnt><s_discountprice> 12.027</s_discountprice><s_price> 4,436</s_price><sep/><s_nm> SUSHI SALT CALLOCALI</s_nm><s_unitprice> 12.027.0020</s_unitprice><s_cnt> 1</s_cnt><s_discountprice> 1,003</s_discountprice><s_price> 1,00</s_price></s_menu><s_sub_total><s_subtotal_price> 3,003</s_subtotal_price><s_discount_price> 3,003<sep/> 0.00</s_discount_price></s_sub_total><s_total><s_total_price> 3,00</s_total_price><s_cashprice> 3,00</s_cashprice><s_changeprice> 1,00</s_changeprice></s_total>") |
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``` |
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<!-- |
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### Downstream Use |
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*List how someone could finetune this model on their own dataset.* |
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--> |
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<!-- |
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### Out-of-Scope Use |
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*List how the model may foreseeably be misused and address what users ought not to do with the model.* |
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--> |
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<!-- |
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## Bias, Risks and Limitations |
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*What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.* |
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--> |
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<!-- |
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### Recommendations |
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*What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.* |
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--> |
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## Training Details |
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### Training Set Metrics |
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| Training set | Min | Median | Max | |
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|:-------------|:----|:---------|:----| |
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| Word count | 5 | 107.8041 | 763 | |
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| Label | Training Sample Count | |
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|:------|:----------------------| |
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| 0 | 47 | |
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| 1 | 51 | |
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| 2 | 50 | |
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### Training Hyperparameters |
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- batch_size: (32, 32) |
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- num_epochs: (2, 2) |
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- max_steps: -1 |
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- sampling_strategy: oversampling |
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- body_learning_rate: (2e-05, 1e-05) |
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- head_learning_rate: 0.01 |
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- loss: CosineSimilarityLoss |
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- distance_metric: cosine_distance |
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- margin: 0.25 |
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- end_to_end: False |
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- use_amp: False |
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- warmup_proportion: 0.1 |
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- seed: 42 |
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- eval_max_steps: -1 |
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- load_best_model_at_end: False |
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### Training Results |
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| Epoch | Step | Training Loss | Validation Loss | |
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|:------:|:----:|:-------------:|:---------------:| |
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| 0.0022 | 1 | 0.3004 | - | |
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| 0.1094 | 50 | 0.2457 | - | |
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| 0.2188 | 100 | 0.1464 | - | |
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| 0.3282 | 150 | 0.0079 | - | |
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| 0.4376 | 200 | 0.0028 | - | |
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| 0.5470 | 250 | 0.0027 | - | |
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| 0.6565 | 300 | 0.0017 | - | |
|
| 0.7659 | 350 | 0.0014 | - | |
|
| 0.8753 | 400 | 0.0015 | - | |
|
| 0.9847 | 450 | 0.0011 | - | |
|
| 1.0941 | 500 | 0.001 | - | |
|
| 1.2035 | 550 | 0.0011 | - | |
|
| 1.3129 | 600 | 0.001 | - | |
|
| 1.4223 | 650 | 0.0011 | - | |
|
| 1.5317 | 700 | 0.0011 | - | |
|
| 1.6411 | 750 | 0.0009 | - | |
|
| 1.7505 | 800 | 0.0008 | - | |
|
| 1.8600 | 850 | 0.001 | - | |
|
| 1.9694 | 900 | 0.0009 | - | |
|
|
|
### 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 |
|
|
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## Citation |
|
|
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### 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} |
|
} |
|
``` |
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