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cbpuschmann
/
klimacoder2_v0.5

Text Classification
setfit
Safetensors
sentence-transformers
bert
generated_from_setfit_trainer
Model card Files Community
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Files changed (13) hide show
  1. 1_Pooling/config.json +10 -0
  2. README.md +1533 -0
  3. config.json +25 -0
  4. config_sentence_transformers.json +10 -0
  5. config_setfit.json +8 -0
  6. model.safetensors +3 -0
  7. model_head.pkl +3 -0
  8. modules.json +14 -0
  9. sentence_bert_config.json +4 -0
  10. special_tokens_map.json +37 -0
  11. tokenizer.json +0 -0
  12. tokenizer_config.json +66 -0
  13. vocab.txt +0 -0
1_Pooling/config.json ADDED
@@ -0,0 +1,10 @@
 
 
 
 
 
 
 
 
 
 
 
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+ {
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+ "word_embedding_dimension": 1024,
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+ "pooling_mode_cls_token": false,
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+ "pooling_mode_mean_tokens": true,
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+ "pooling_mode_max_tokens": false,
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+ "pooling_mode_mean_sqrt_len_tokens": false,
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+ "pooling_mode_weightedmean_tokens": false,
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+ "pooling_mode_lasttoken": false,
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+ "include_prompt": true
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+ }
README.md ADDED
@@ -0,0 +1,1533 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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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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+ widget:
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+ - text: Die Forderungen sind landesweit die gleichen. Es geht um die Wiedereinführung
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+ eines 9-Euro-Tickets und ein Tempolimit von 100 km/h auf den Autobahnen. Außerdem
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+ fordern wir die Einführung eines Gesellschaftsrats. Dieser soll Maßnahmen erarbeiten,
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+ wie Deutschland bis 2030 emissionsfrei wird. Die Lösungsansätze sollen von der
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+ Bundesregierung anerkannt und in der Politik umgesetzt werden.
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+ - text: Die aktivist bezeichnen sich als ›DLG›. Sie fordern von Bundeswirtschaftsminister
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+ Robert Habeck Grüne, auf fossile Energie zu verzichten. Zudem verlangen sie eine
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+ Lebenserklärung der Rektorin der Leipziger Universität. Diese soll sich ›offiziell,
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+ öffentlich und gerichtet an Robert Habeck gegen den Bau und die Finanzierung neuer
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+ fossiler Infrastruktur aussprechen. Insbesondere gegen neue Ölbohrungen in der
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+ Nordsee sowie neue Flüssiggas-Terminals›, hieß es in einer Mitteilung der Gruppe
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+ am Donnerstag.
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+ - text: Am Montag war es erneut das Amtsgericht Tiergarten, in dem ein Anwalt die
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+ Aktionen der ›DLG› mit einem fragwürdigen historischen Vergleich rechtfertigte.
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+ Verhandelt wurde an dem Tag gegen den 63-jährigen Winfried L. Wegen fünf Straßenblockaden,
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+ bei denen er teilweise seine Hand auf der Straße angeklebt hatte, musste sich
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+ L. wegen der Vorwürfe Nötigung und Widerstand gegen Vollstreckungsbeamte verantworten.
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+ - text: 'In einer am Morgen verbreiteten Mitteilung begründete die Gruppe ihre Aktion.
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+ Mit der Sitzblockade habe der "fossile Alltag" auf der Straße unterbrochen werden
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+ sollen. Auf Transparenten seien Forderungen deutlich gemacht worden: ein 9-Euro-Ticket
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+ für alle, ein Tempolimit von 100 Stundenkilometern auf Autobahnen und die Bildung
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+ eines Gesellschaftsrats zum Thema Ende der fossilen Brennstoffe bis 2030.'
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+ - text: 'aktivist feiern Festival für mehr Klimaschutz Xanten wer Die Ortsgruppe Xanten
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+ von FFF hat am Freitagnachmittag wieder für mehr Klimaschutz protestiert – aber
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+ anders als sonst. Die aktivist organisierten an der Kriemhildmühle im Kurpark
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+ ein Festival mit Musik, Essen, Getränken und Vorträgen. Viele Menschen kamen,
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+ genossen das schöne Wetter und die entspannte Atmosphäre, lauschten den Liedern
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+ und sangen mit. Ansprachen gab es auch: Seit Jahrzehnten warne die Wissenschaft
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+ vor den Folgen des Klimawandels, trotzdem unternehme die Politik zu wenig, und
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+ die Bevölkerung müsse unter den Folgen wie Dürren, Überschwemmungen und Hitze
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+ leiden, kritisierte Frederik Krohn von der Xantener Ortsgruppe der Klimaschutzbewegung.
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+ Deshalb gehe FFF immer wieder auf die Straße, um der Politik zu sagen, dass es
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+ so nicht weitergehe. Die große Teilnahme am Festival in Xanten und damit am Klimaschutz-Protest
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+ sei ein ›starkes Zeichen›, sagte Krohn.'
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+ metrics:
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+ - accuracy
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+ pipeline_tag: text-classification
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+ library_name: setfit
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+ inference: true
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+ base_model: deutsche-telekom/gbert-large-paraphrase-cosine
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+ ---
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+
50
+ # SetFit with deutsche-telekom/gbert-large-paraphrase-cosine
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+
52
+ This is a [SetFit](https://github.com/huggingface/setfit) model that can be used for Text Classification. This SetFit model uses [deutsche-telekom/gbert-large-paraphrase-cosine](https://huggingface.co/deutsche-telekom/gbert-large-paraphrase-cosine) 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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+
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+ The model has been trained using an efficient few-shot learning technique that involves:
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+
56
+ 1. Fine-tuning a [Sentence Transformer](https://www.sbert.net) with contrastive learning.
57
+ 2. Training a classification head with features from the fine-tuned Sentence Transformer.
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+
59
+ ## Model Details
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+
61
+ ### Model Description
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+ - **Model Type:** SetFit
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+ - **Sentence Transformer body:** [deutsche-telekom/gbert-large-paraphrase-cosine](https://huggingface.co/deutsche-telekom/gbert-large-paraphrase-cosine)
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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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+
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+ ### Model Sources
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+
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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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+
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+ ### Model Labels
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+ | Label | Examples |
79
+ |:-----------|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
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+ | neutral | <ul><li>'Das geplante Heizungsgesetz zielt auf eine flächendeckende Einführung von Wärmepumpen ab, stützt sich jedoch auf komplexe Wirtschaftlichkeitsberechnungen, die verschiedene Energiepreisszenarien und Netzkosten berücksichtigen. Kritiker wie Befürworter betonen die Notwendigkeit einer nachhaltigeren Heizungsinfrastruktur, während die genaue Auswirkung der Initiative noch Gegenstand der Diskussion ist.'</li><li>'Das geplante Heizungsgesetz zielt auf eine flächendeckende Einführung von Wärmepumpen ab, stützt sich dabei auf detaillierte Wirtschaftlichkeitsberechnungen, die verschiedene Energieszenarien und Kostenfaktoren berücksichtigen. Die Initiativen beziehen mögliche Entwicklungen bei CO₂-Preisen sowie Netzentgelten ein, um eine effiziente und klimafreundliche Heizungsinfrastruktur zu fördern. Die Auswirkungen auf Wirtschaft und Verbraucher bleiben vorerst offen.'</li><li>'Das vom Bundestag verabschiedete Heizungsgesetz zielt auf eine flächendeckende Einführung von Wärmepumpen ab. Der Staat fördert den Umstieg auf klimafreundliche Heizungen mit bis zu 70 Prozent der Kosten, maximal 30.000 Euro pro Einfamilienhaus. Die Initiative soll den Übergang zu erneuerbaren Energien im Wohnungssektor beschleunigen.'</li></ul> |
81
+ | opposed | <ul><li>'Skeptische Reaktionen auf das "Heizungsgesetz": CDU warnt vor unerwünschten Folgen\n\nDie geplante flächendeckende Einführung von Wärmepumpen durch die Bundesregierung stößt bei der CDU auf starke Kritik. Die Partei weist auf Bedenken hin, dass solche Initiativen zu unzumutbaren Kosten für Verbraucher führen und insbesondere ältere Menschen und Familien mit niedrigem Einkommen belasten könnten. "Fair Heizen statt verheizen" fordert die CDU-Kampagne und warnt vor einer ungedachten Umstellung, die mehr Schaden als Nutzen bringen könnte.'</li><li>'Die geplante flächendeckende Einführung von Wärmepumpen durch das sogenannte "Heizungsgesetz" stößt auf wachsenden Widerstand in der Ampelkoalition. Während die FDP bereits offen gegen das Vorhaben stimmt, äußern sich nun auch viele SPD-Politiker skeptisch – vor allem wegen der befürchteten hohen Kosten für Hausbesitzer und Mieter. Sie zweifeln an, ob die Maßnahme wirklich so umsetzbar und effektiv ist, wie Wirtschaftsminister Habeck (Grüne) behauptet.'</li><li>'"Skeptische Reaktionen auf Heizungsgesetz: Kritiker zweifeln an wirksamer Energieeinsparung"\n\nDie geplante flächendeckende Einführung von Wärmepumpen wirft ein geteiltes Echo hervor. Während die Regierung von einem "technologieoffenen" Ansatz spricht, sind viele Beobachter skeptisch: Die Abhängigkeit von Biogas als Ersatz für fossile Brennstoffe könnte sich als weniger nachhaltig erweisen, als zunächst angenommen. Kritiker argumentieren, dass ohne flächendeckende Infrastruktur und rasche Verfügbarkeit von grünem Wasserstoff der eigentliche Klimaschutz ausbleibt.'</li></ul> |
82
+ | supportive | <ul><li>'Trotz kritischer Stimmen und übertriebenen Warnungen vor hohen Kosten bleibt die flächendeckende Einführung von Wärmepumpen als nachhaltige Heizlösung ein wichtiger Schritt in Richtung Energiewende. Während die Debatte um das "Heizungsgesetz" hitzig führt, zeigen internationale Beispiele wie Norwegen, dass eine breite Akzeptanz und erfolgreiche Umsetzung möglich ist. Trotz potenzieller Herausforderungen für Hausbesitzer ist der langfristige Nutzen für Klima und Umwelt unbestreitbar.'</li><li>'Obwohl die flächendeckende Einführung von Wärmepumpen durch das geplante "Heizungsgesetz" auf gemischte Reaktionen stößt, ist der Fokus auf klimafreundliche Heizungstechnologien ein vielversprechender Schritt in Richtung Energiewende. Kritiker befürchten höhere Kosten für Hausbesitzer, doch Experten verweisen darauf, dass langfristig sowohl die Umwelt als auch die Energiesicherheit von einer solchen Maßnahme profitieren könnten. Die Förderung durch das Gesetz könnte den Übergang zu nachhaltigeren Heizsystemen beschleunigen.'</li><li>'Heizungsgesetz: Ein Schritt in die richtige Richtung, aber nicht ohne Kritikpunkte\n\nWährend die flächendeckende Einführung von Wärmepumpen durch das neue Heizungsgesetz als umweltfreundliche Alternative gelobt wird, warnen Kritiker vor pauschalen Lösungen. Experten betonen, dass nicht jede Heizung für jedes Haus geeignet ist und eine individuelle Beratung wichtig ist. Dennoch sehen sie in den aktuellen Förderprogrammen einen Anreiz für Hausbesitzer, energieeffiziente Technologien zu nutzen.'</li></ul> |
83
+
84
+ ## Uses
85
+
86
+ ### Direct Use for Inference
87
+
88
+ First install the SetFit library:
89
+
90
+ ```bash
91
+ pip install setfit
92
+ ```
93
+
94
+ Then you can load this model and run inference.
95
+
96
+ ```python
97
+ from setfit import SetFitModel
98
+
99
+ # Download from the 🤗 Hub
100
+ model = SetFitModel.from_pretrained("cbpuschmann/klimacoder2_v0.5")
101
+ # Run inference
102
+ preds = model("Die Forderungen sind landesweit die gleichen. Es geht um die Wiedereinführung eines 9-Euro-Tickets und ein Tempolimit von 100 km/h auf den Autobahnen. Außerdem fordern wir die Einführung eines Gesellschaftsrats. Dieser soll Maßnahmen erarbeiten, wie Deutschland bis 2030 emissionsfrei wird. Die Lösungsansätze sollen von der Bundesregierung anerkannt und in der Politik umgesetzt werden.")
103
+ ```
104
+
105
+ <!--
106
+ ### Downstream Use
107
+
108
+ *List how someone could finetune this model on their own dataset.*
109
+ -->
110
+
111
+ <!--
112
+ ### Out-of-Scope Use
113
+
114
+ *List how the model may foreseeably be misused and address what users ought not to do with the model.*
115
+ -->
116
+
117
+ <!--
118
+ ## Bias, Risks and Limitations
119
+
120
+ *What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.*
121
+ -->
122
+
123
+ <!--
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+ ### Recommendations
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+
126
+ *What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*
127
+ -->
128
+
129
+ ## Training Details
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+
131
+ ### Training Set Metrics
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+ | Training set | Min | Median | Max |
133
+ |:-------------|:----|:--------|:----|
134
+ | Word count | 22 | 60.3810 | 232 |
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+
136
+ | Label | Training Sample Count |
137
+ |:-----------|:----------------------|
138
+ | supportive | 420 |
139
+ | opposed | 420 |
140
+ | neutral | 420 |
141
+
142
+ ### Training Hyperparameters
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+ - batch_size: (16, 16)
144
+ - num_epochs: (4, 4)
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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
155
+ - l2_weight: 0.01
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+ - seed: 42
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+ - eval_max_steps: -1
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+ - load_best_model_at_end: True
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+
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+ ### Training Results
161
+ | Epoch | Step | Training Loss | Validation Loss |
162
+ |:------:|:-----:|:-------------:|:---------------:|
163
+ | 0.0001 | 1 | 0.257 | - |
164
+ | 0.0030 | 50 | 0.2617 | - |
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+ | 0.0060 | 100 | 0.2515 | - |
166
+ | 0.0091 | 150 | 0.2451 | - |
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+ | 0.0121 | 200 | 0.2235 | - |
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+ | 0.0151 | 250 | 0.2008 | - |
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+ | 0.0181 | 300 | 0.1414 | - |
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+ | 0.0212 | 350 | 0.0829 | - |
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+ | 0.0242 | 400 | 0.0379 | - |
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+ | 0.0272 | 450 | 0.0184 | - |
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+ | 0.0302 | 500 | 0.0114 | - |
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+ | 0.0333 | 550 | 0.0051 | - |
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+ | 0.0363 | 600 | 0.0024 | - |
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+ | 0.0393 | 650 | 0.0012 | - |
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+ | 0.0423 | 700 | 0.0008 | - |
178
+ | 0.0454 | 750 | 0.0006 | - |
179
+ | 0.0484 | 800 | 0.0004 | - |
180
+ | 0.0514 | 850 | 0.0003 | - |
181
+ | 0.0544 | 900 | 0.0002 | - |
182
+ | 0.0574 | 950 | 0.0003 | - |
183
+ | 0.0605 | 1000 | 0.0002 | - |
184
+ | 0.0635 | 1050 | 0.0002 | - |
185
+ | 0.0665 | 1100 | 0.0001 | - |
186
+ | 0.0695 | 1150 | 0.0001 | - |
187
+ | 0.0726 | 1200 | 0.0001 | - |
188
+ | 0.0756 | 1250 | 0.0005 | - |
189
+ | 0.0786 | 1300 | 0.0002 | - |
190
+ | 0.0816 | 1350 | 0.0001 | - |
191
+ | 0.0847 | 1400 | 0.0001 | - |
192
+ | 0.0877 | 1450 | 0.0001 | - |
193
+ | 0.0907 | 1500 | 0.0001 | - |
194
+ | 0.0937 | 1550 | 0.0001 | - |
195
+ | 0.0967 | 1600 | 0.0001 | - |
196
+ | 0.0998 | 1650 | 0.0001 | - |
197
+ | 0.1028 | 1700 | 0.0001 | - |
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+ | 0.1058 | 1750 | 0.0 | - |
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+ | 0.1088 | 1800 | 0.0 | - |
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+ | 0.1119 | 1850 | 0.0 | - |
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+ | 0.1149 | 1900 | 0.0 | - |
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+ | 0.1179 | 1950 | 0.0 | - |
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+ | 0.1209 | 2000 | 0.0019 | - |
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+ | 0.1240 | 2050 | 0.0055 | - |
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+ | 0.1270 | 2100 | 0.0035 | - |
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+ | 0.1300 | 2150 | 0.0018 | - |
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+ | 0.1330 | 2200 | 0.0008 | - |
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+ | 0.1361 | 2250 | 0.0001 | - |
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+ | 0.1391 | 2300 | 0.0 | - |
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+ | 0.1421 | 2350 | 0.0 | - |
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+ | 0.1451 | 2400 | 0.0 | - |
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+ | 0.1481 | 2450 | 0.0 | - |
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+ | 0.1512 | 2500 | 0.0 | - |
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+ | 0.1542 | 2550 | 0.0 | - |
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+ | 0.1572 | 2600 | 0.0 | - |
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+ | 0.1602 | 2650 | 0.0 | - |
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+ | 0.1633 | 2700 | 0.0 | - |
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+ | 0.1663 | 2750 | 0.0 | - |
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+ | 0.1693 | 2800 | 0.0 | - |
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+ | 0.1723 | 2850 | 0.0 | - |
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+ | 0.1754 | 2900 | 0.0 | - |
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+ | 0.1784 | 2950 | 0.0 | - |
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+ | 0.1814 | 3000 | 0.0 | - |
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+ | 0.1844 | 3050 | 0.0 | - |
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+ | 0.1874 | 3100 | 0.0 | - |
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+ | 0.1905 | 3150 | 0.0 | - |
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+ | 0.1935 | 3200 | 0.0 | - |
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+ | 0.1965 | 3250 | 0.0 | - |
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+ | 0.1995 | 3300 | 0.0 | - |
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+ | 0.2026 | 3350 | 0.0 | - |
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+ | 0.2056 | 3400 | 0.0 | - |
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+ | 0.2086 | 3450 | 0.0 | - |
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+ | 0.2116 | 3500 | 0.0 | - |
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+ | 0.2147 | 3550 | 0.0 | - |
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+ | 0.2177 | 3600 | 0.0 | - |
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+ | 0.2207 | 3650 | 0.0 | - |
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+ | 0.2237 | 3700 | 0.0 | - |
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+ | 0.2268 | 3750 | 0.0 | - |
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+ | 0.2298 | 3800 | 0.0 | - |
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+ | 0.2328 | 3850 | 0.0 | - |
241
+ | 0.2358 | 3900 | 0.0 | - |
242
+ | 0.2388 | 3950 | 0.0 | - |
243
+ | 0.2419 | 4000 | 0.0 | - |
244
+ | 0.2449 | 4050 | 0.0 | - |
245
+ | 0.2479 | 4100 | 0.0 | - |
246
+ | 0.2509 | 4150 | 0.0 | - |
247
+ | 0.2540 | 4200 | 0.0 | - |
248
+ | 0.2570 | 4250 | 0.0 | - |
249
+ | 0.2600 | 4300 | 0.0 | - |
250
+ | 0.2630 | 4350 | 0.0 | - |
251
+ | 0.2661 | 4400 | 0.0 | - |
252
+ | 0.2691 | 4450 | 0.0 | - |
253
+ | 0.2721 | 4500 | 0.0 | - |
254
+ | 0.2751 | 4550 | 0.0 | - |
255
+ | 0.2781 | 4600 | 0.0 | - |
256
+ | 0.2812 | 4650 | 0.0 | - |
257
+ | 0.2842 | 4700 | 0.0 | - |
258
+ | 0.2872 | 4750 | 0.0 | - |
259
+ | 0.2902 | 4800 | 0.0 | - |
260
+ | 0.2933 | 4850 | 0.0 | - |
261
+ | 0.2963 | 4900 | 0.0 | - |
262
+ | 0.2993 | 4950 | 0.0 | - |
263
+ | 0.3023 | 5000 | 0.0 | - |
264
+ | 0.3054 | 5050 | 0.0 | - |
265
+ | 0.3084 | 5100 | 0.0 | - |
266
+ | 0.3114 | 5150 | 0.0 | - |
267
+ | 0.3144 | 5200 | 0.0 | - |
268
+ | 0.3175 | 5250 | 0.0 | - |
269
+ | 0.3205 | 5300 | 0.0 | - |
270
+ | 0.3235 | 5350 | 0.0 | - |
271
+ | 0.3265 | 5400 | 0.0 | - |
272
+ | 0.3295 | 5450 | 0.0 | - |
273
+ | 0.3326 | 5500 | 0.0 | - |
274
+ | 0.3356 | 5550 | 0.0 | - |
275
+ | 0.3386 | 5600 | 0.0 | - |
276
+ | 0.3416 | 5650 | 0.0 | - |
277
+ | 0.3447 | 5700 | 0.0 | - |
278
+ | 0.3477 | 5750 | 0.0 | - |
279
+ | 0.3507 | 5800 | 0.0 | - |
280
+ | 0.3537 | 5850 | 0.0 | - |
281
+ | 0.3568 | 5900 | 0.0 | - |
282
+ | 0.3598 | 5950 | 0.0 | - |
283
+ | 0.3628 | 6000 | 0.0 | - |
284
+ | 0.3658 | 6050 | 0.0 | - |
285
+ | 0.3688 | 6100 | 0.0 | - |
286
+ | 0.3719 | 6150 | 0.0 | - |
287
+ | 0.3749 | 6200 | 0.0 | - |
288
+ | 0.3779 | 6250 | 0.0 | - |
289
+ | 0.3809 | 6300 | 0.0 | - |
290
+ | 0.3840 | 6350 | 0.0 | - |
291
+ | 0.3870 | 6400 | 0.0 | - |
292
+ | 0.3900 | 6450 | 0.0 | - |
293
+ | 0.3930 | 6500 | 0.0 | - |
294
+ | 0.3961 | 6550 | 0.0 | - |
295
+ | 0.3991 | 6600 | 0.0 | - |
296
+ | 0.4021 | 6650 | 0.0 | - |
297
+ | 0.4051 | 6700 | 0.0 | - |
298
+ | 0.4082 | 6750 | 0.0 | - |
299
+ | 0.4112 | 6800 | 0.0 | - |
300
+ | 0.4142 | 6850 | 0.0 | - |
301
+ | 0.4172 | 6900 | 0.0 | - |
302
+ | 0.4202 | 6950 | 0.0 | - |
303
+ | 0.4233 | 7000 | 0.0 | - |
304
+ | 0.4263 | 7050 | 0.0 | - |
305
+ | 0.4293 | 7100 | 0.0 | - |
306
+ | 0.4323 | 7150 | 0.0 | - |
307
+ | 0.4354 | 7200 | 0.0 | - |
308
+ | 0.4384 | 7250 | 0.0 | - |
309
+ | 0.4414 | 7300 | 0.0 | - |
310
+ | 0.4444 | 7350 | 0.0 | - |
311
+ | 0.4475 | 7400 | 0.0 | - |
312
+ | 0.4505 | 7450 | 0.0 | - |
313
+ | 0.4535 | 7500 | 0.0 | - |
314
+ | 0.4565 | 7550 | 0.0 | - |
315
+ | 0.4595 | 7600 | 0.0 | - |
316
+ | 0.4626 | 7650 | 0.0 | - |
317
+ | 0.4656 | 7700 | 0.0 | - |
318
+ | 0.4686 | 7750 | 0.0 | - |
319
+ | 0.4716 | 7800 | 0.0 | - |
320
+ | 0.4747 | 7850 | 0.0 | - |
321
+ | 0.4777 | 7900 | 0.0 | - |
322
+ | 0.4807 | 7950 | 0.0 | - |
323
+ | 0.4837 | 8000 | 0.0 | - |
324
+ | 0.4868 | 8050 | 0.0 | - |
325
+ | 0.4898 | 8100 | 0.0 | - |
326
+ | 0.4928 | 8150 | 0.0 | - |
327
+ | 0.4958 | 8200 | 0.0 | - |
328
+ | 0.4989 | 8250 | 0.3154 | - |
329
+ | 0.5019 | 8300 | 0.2706 | - |
330
+ | 0.5049 | 8350 | 0.2635 | - |
331
+ | 0.5079 | 8400 | 0.2615 | - |
332
+ | 0.5109 | 8450 | 0.2598 | - |
333
+ | 0.5140 | 8500 | 0.258 | - |
334
+ | 0.5170 | 8550 | 0.2611 | - |
335
+ | 0.5200 | 8600 | 0.2601 | - |
336
+ | 0.5230 | 8650 | 0.2552 | - |
337
+ | 0.5261 | 8700 | 0.2561 | - |
338
+ | 0.5291 | 8750 | 0.2574 | - |
339
+ | 0.5321 | 8800 | 0.2563 | - |
340
+ | 0.5351 | 8850 | 0.2541 | - |
341
+ | 0.5382 | 8900 | 0.2569 | - |
342
+ | 0.5412 | 8950 | 0.2544 | - |
343
+ | 0.5442 | 9000 | 0.2565 | - |
344
+ | 0.5472 | 9050 | 0.2553 | - |
345
+ | 0.5502 | 9100 | 0.2567 | - |
346
+ | 0.5533 | 9150 | 0.2546 | - |
347
+ | 0.5563 | 9200 | 0.2562 | - |
348
+ | 0.5593 | 9250 | 0.2562 | - |
349
+ | 0.5623 | 9300 | 0.2582 | - |
350
+ | 0.5654 | 9350 | 0.2535 | - |
351
+ | 0.5684 | 9400 | 0.2548 | - |
352
+ | 0.5714 | 9450 | 0.2561 | - |
353
+ | 0.5744 | 9500 | 0.2571 | - |
354
+ | 0.5775 | 9550 | 0.2589 | - |
355
+ | 0.5805 | 9600 | 0.2537 | - |
356
+ | 0.5835 | 9650 | 0.256 | - |
357
+ | 0.5865 | 9700 | 0.2548 | - |
358
+ | 0.5896 | 9750 | 0.2547 | - |
359
+ | 0.5926 | 9800 | 0.2556 | - |
360
+ | 0.5956 | 9850 | 0.254 | - |
361
+ | 0.5986 | 9900 | 0.2543 | - |
362
+ | 0.6016 | 9950 | 0.254 | - |
363
+ | 0.6047 | 10000 | 0.2539 | - |
364
+ | 0.6077 | 10050 | 0.2554 | - |
365
+ | 0.6107 | 10100 | 0.2549 | - |
366
+ | 0.6137 | 10150 | 0.2537 | - |
367
+ | 0.6168 | 10200 | 0.2561 | - |
368
+ | 0.6198 | 10250 | 0.2541 | - |
369
+ | 0.6228 | 10300 | 0.256 | - |
370
+ | 0.6258 | 10350 | 0.2532 | - |
371
+ | 0.6289 | 10400 | 0.2563 | - |
372
+ | 0.6319 | 10450 | 0.2554 | - |
373
+ | 0.6349 | 10500 | 0.2549 | - |
374
+ | 0.6379 | 10550 | 0.253 | - |
375
+ | 0.6409 | 10600 | 0.2558 | - |
376
+ | 0.6440 | 10650 | 0.2529 | - |
377
+ | 0.6470 | 10700 | 0.2532 | - |
378
+ | 0.6500 | 10750 | 0.2537 | - |
379
+ | 0.6530 | 10800 | 0.2557 | - |
380
+ | 0.6561 | 10850 | 0.254 | - |
381
+ | 0.6591 | 10900 | 0.254 | - |
382
+ | 0.6621 | 10950 | 0.2529 | - |
383
+ | 0.6651 | 11000 | 0.2521 | - |
384
+ | 0.6682 | 11050 | 0.2532 | - |
385
+ | 0.6712 | 11100 | 0.2531 | - |
386
+ | 0.6742 | 11150 | 0.2542 | - |
387
+ | 0.6772 | 11200 | 0.2555 | - |
388
+ | 0.6803 | 11250 | 0.2531 | - |
389
+ | 0.6833 | 11300 | 0.2543 | - |
390
+ | 0.6863 | 11350 | 0.2556 | - |
391
+ | 0.6893 | 11400 | 0.2539 | - |
392
+ | 0.6923 | 11450 | 0.2548 | - |
393
+ | 0.6954 | 11500 | 0.2539 | - |
394
+ | 0.6984 | 11550 | 0.2545 | - |
395
+ | 0.7014 | 11600 | 0.2514 | - |
396
+ | 0.7044 | 11650 | 0.2544 | - |
397
+ | 0.7075 | 11700 | 0.2516 | - |
398
+ | 0.7105 | 11750 | 0.2524 | - |
399
+ | 0.7135 | 11800 | 0.2541 | - |
400
+ | 0.7165 | 11850 | 0.2544 | - |
401
+ | 0.7196 | 11900 | 0.2537 | - |
402
+ | 0.7226 | 11950 | 0.2538 | - |
403
+ | 0.7256 | 12000 | 0.2535 | - |
404
+ | 0.7286 | 12050 | 0.2545 | - |
405
+ | 0.7316 | 12100 | 0.2545 | - |
406
+ | 0.7347 | 12150 | 0.2531 | - |
407
+ | 0.7377 | 12200 | 0.2537 | - |
408
+ | 0.7407 | 12250 | 0.2534 | - |
409
+ | 0.7437 | 12300 | 0.2539 | - |
410
+ | 0.7468 | 12350 | 0.2548 | - |
411
+ | 0.7498 | 12400 | 0.2523 | - |
412
+ | 0.7528 | 12450 | 0.2532 | - |
413
+ | 0.7558 | 12500 | 0.2529 | - |
414
+ | 0.7589 | 12550 | 0.2551 | - |
415
+ | 0.7619 | 12600 | 0.2533 | - |
416
+ | 0.7649 | 12650 | 0.2551 | - |
417
+ | 0.7679 | 12700 | 0.2551 | - |
418
+ | 0.7710 | 12750 | 0.2542 | - |
419
+ | 0.7740 | 12800 | 0.2538 | - |
420
+ | 0.7770 | 12850 | 0.2528 | - |
421
+ | 0.7800 | 12900 | 0.2534 | - |
422
+ | 0.7830 | 12950 | 0.2528 | - |
423
+ | 0.7861 | 13000 | 0.2525 | - |
424
+ | 0.7891 | 13050 | 0.2536 | - |
425
+ | 0.7921 | 13100 | 0.2538 | - |
426
+ | 0.7951 | 13150 | 0.2533 | - |
427
+ | 0.7982 | 13200 | 0.2521 | - |
428
+ | 0.8012 | 13250 | 0.2542 | - |
429
+ | 0.8042 | 13300 | 0.2567 | - |
430
+ | 0.8072 | 13350 | 0.2517 | - |
431
+ | 0.8103 | 13400 | 0.2538 | - |
432
+ | 0.8133 | 13450 | 0.2522 | - |
433
+ | 0.8163 | 13500 | 0.2537 | - |
434
+ | 0.8193 | 13550 | 0.2528 | - |
435
+ | 0.8223 | 13600 | 0.2533 | - |
436
+ | 0.8254 | 13650 | 0.2534 | - |
437
+ | 0.8284 | 13700 | 0.2532 | - |
438
+ | 0.8314 | 13750 | 0.2525 | - |
439
+ | 0.8344 | 13800 | 0.2543 | - |
440
+ | 0.8375 | 13850 | 0.2536 | - |
441
+ | 0.8405 | 13900 | 0.2523 | - |
442
+ | 0.8435 | 13950 | 0.2547 | - |
443
+ | 0.8465 | 14000 | 0.2508 | - |
444
+ | 0.8496 | 14050 | 0.2519 | - |
445
+ | 0.8526 | 14100 | 0.2522 | - |
446
+ | 0.8556 | 14150 | 0.255 | - |
447
+ | 0.8586 | 14200 | 0.2541 | - |
448
+ | 0.8617 | 14250 | 0.2551 | - |
449
+ | 0.8647 | 14300 | 0.2542 | - |
450
+ | 0.8677 | 14350 | 0.254 | - |
451
+ | 0.8707 | 14400 | 0.2535 | - |
452
+ | 0.8737 | 14450 | 0.2539 | - |
453
+ | 0.8768 | 14500 | 0.2536 | - |
454
+ | 0.8798 | 14550 | 0.2537 | - |
455
+ | 0.8828 | 14600 | 0.2534 | - |
456
+ | 0.8858 | 14650 | 0.2514 | - |
457
+ | 0.8889 | 14700 | 0.2546 | - |
458
+ | 0.8919 | 14750 | 0.253 | - |
459
+ | 0.8949 | 14800 | 0.2546 | - |
460
+ | 0.8979 | 14850 | 0.2521 | - |
461
+ | 0.9010 | 14900 | 0.2525 | - |
462
+ | 0.9040 | 14950 | 0.2528 | - |
463
+ | 0.9070 | 15000 | 0.2536 | - |
464
+ | 0.9100 | 15050 | 0.2531 | - |
465
+ | 0.9130 | 15100 | 0.2524 | - |
466
+ | 0.9161 | 15150 | 0.2538 | - |
467
+ | 0.9191 | 15200 | 0.2537 | - |
468
+ | 0.9221 | 15250 | 0.2522 | - |
469
+ | 0.9251 | 15300 | 0.2537 | - |
470
+ | 0.9282 | 15350 | 0.2543 | - |
471
+ | 0.9312 | 15400 | 0.2526 | - |
472
+ | 0.9342 | 15450 | 0.2517 | - |
473
+ | 0.9372 | 15500 | 0.2529 | - |
474
+ | 0.9403 | 15550 | 0.2546 | - |
475
+ | 0.9433 | 15600 | 0.254 | - |
476
+ | 0.9463 | 15650 | 0.2518 | - |
477
+ | 0.9493 | 15700 | 0.2522 | - |
478
+ | 0.9524 | 15750 | 0.256 | - |
479
+ | 0.9554 | 15800 | 0.2528 | - |
480
+ | 0.9584 | 15850 | 0.253 | - |
481
+ | 0.9614 | 15900 | 0.2524 | - |
482
+ | 0.9644 | 15950 | 0.2532 | - |
483
+ | 0.9675 | 16000 | 0.2529 | - |
484
+ | 0.9705 | 16050 | 0.2523 | - |
485
+ | 0.9735 | 16100 | 0.2531 | - |
486
+ | 0.9765 | 16150 | 0.2552 | - |
487
+ | 0.9796 | 16200 | 0.2531 | - |
488
+ | 0.9826 | 16250 | 0.253 | - |
489
+ | 0.9856 | 16300 | 0.252 | - |
490
+ | 0.9886 | 16350 | 0.2538 | - |
491
+ | 0.9917 | 16400 | 0.2537 | - |
492
+ | 0.9947 | 16450 | 0.2521 | - |
493
+ | 0.9977 | 16500 | 0.2537 | - |
494
+ | 1.0 | 16538 | - | 0.5 |
495
+ | 1.0007 | 16550 | 0.2555 | - |
496
+ | 1.0037 | 16600 | 0.2534 | - |
497
+ | 1.0068 | 16650 | 0.2545 | - |
498
+ | 1.0098 | 16700 | 0.2528 | - |
499
+ | 1.0128 | 16750 | 0.2526 | - |
500
+ | 1.0158 | 16800 | 0.253 | - |
501
+ | 1.0189 | 16850 | 0.2534 | - |
502
+ | 1.0219 | 16900 | 0.2533 | - |
503
+ | 1.0249 | 16950 | 0.2532 | - |
504
+ | 1.0279 | 17000 | 0.2519 | - |
505
+ | 1.0310 | 17050 | 0.2531 | - |
506
+ | 1.0340 | 17100 | 0.2543 | - |
507
+ | 1.0370 | 17150 | 0.2531 | - |
508
+ | 1.0400 | 17200 | 0.2534 | - |
509
+ | 1.0431 | 17250 | 0.2535 | - |
510
+ | 1.0461 | 17300 | 0.2532 | - |
511
+ | 1.0491 | 17350 | 0.253 | - |
512
+ | 1.0521 | 17400 | 0.253 | - |
513
+ | 1.0551 | 17450 | 0.2516 | - |
514
+ | 1.0582 | 17500 | 0.2533 | - |
515
+ | 1.0612 | 17550 | 0.2519 | - |
516
+ | 1.0642 | 17600 | 0.2543 | - |
517
+ | 1.0672 | 17650 | 0.2531 | - |
518
+ | 1.0703 | 17700 | 0.2533 | - |
519
+ | 1.0733 | 17750 | 0.2528 | - |
520
+ | 1.0763 | 17800 | 0.2555 | - |
521
+ | 1.0793 | 17850 | 0.2528 | - |
522
+ | 1.0824 | 17900 | 0.2526 | - |
523
+ | 1.0854 | 17950 | 0.2518 | - |
524
+ | 1.0884 | 18000 | 0.252 | - |
525
+ | 1.0914 | 18050 | 0.2548 | - |
526
+ | 1.0944 | 18100 | 0.2534 | - |
527
+ | 1.0975 | 18150 | 0.2529 | - |
528
+ | 1.1005 | 18200 | 0.2526 | - |
529
+ | 1.1035 | 18250 | 0.2524 | - |
530
+ | 1.1065 | 18300 | 0.2518 | - |
531
+ | 1.1096 | 18350 | 0.2521 | - |
532
+ | 1.1126 | 18400 | 0.2532 | - |
533
+ | 1.1156 | 18450 | 0.2516 | - |
534
+ | 1.1186 | 18500 | 0.2529 | - |
535
+ | 1.1217 | 18550 | 0.2545 | - |
536
+ | 1.1247 | 18600 | 0.2523 | - |
537
+ | 1.1277 | 18650 | 0.253 | - |
538
+ | 1.1307 | 18700 | 0.2528 | - |
539
+ | 1.1338 | 18750 | 0.2536 | - |
540
+ | 1.1368 | 18800 | 0.2535 | - |
541
+ | 1.1398 | 18850 | 0.2527 | - |
542
+ | 1.1428 | 18900 | 0.2529 | - |
543
+ | 1.1458 | 18950 | 0.2523 | - |
544
+ | 1.1489 | 19000 | 0.2522 | - |
545
+ | 1.1519 | 19050 | 0.2526 | - |
546
+ | 1.1549 | 19100 | 0.2524 | - |
547
+ | 1.1579 | 19150 | 0.2531 | - |
548
+ | 1.1610 | 19200 | 0.2524 | - |
549
+ | 1.1640 | 19250 | 0.2519 | - |
550
+ | 1.1670 | 19300 | 0.2548 | - |
551
+ | 1.1700 | 19350 | 0.2526 | - |
552
+ | 1.1731 | 19400 | 0.2516 | - |
553
+ | 1.1761 | 19450 | 0.2515 | - |
554
+ | 1.1791 | 19500 | 0.253 | - |
555
+ | 1.1821 | 19550 | 0.2528 | - |
556
+ | 1.1851 | 19600 | 0.2524 | - |
557
+ | 1.1882 | 19650 | 0.2532 | - |
558
+ | 1.1912 | 19700 | 0.2518 | - |
559
+ | 1.1942 | 19750 | 0.253 | - |
560
+ | 1.1972 | 19800 | 0.2523 | - |
561
+ | 1.2003 | 19850 | 0.2529 | - |
562
+ | 1.2033 | 19900 | 0.2519 | - |
563
+ | 1.2063 | 19950 | 0.2544 | - |
564
+ | 1.2093 | 20000 | 0.251 | - |
565
+ | 1.2124 | 20050 | 0.2522 | - |
566
+ | 1.2154 | 20100 | 0.25 | - |
567
+ | 1.2184 | 20150 | 0.2528 | - |
568
+ | 1.2214 | 20200 | 0.2513 | - |
569
+ | 1.2245 | 20250 | 0.2532 | - |
570
+ | 1.2275 | 20300 | 0.251 | - |
571
+ | 1.2305 | 20350 | 0.2521 | - |
572
+ | 1.2335 | 20400 | 0.2514 | - |
573
+ | 1.2365 | 20450 | 0.2523 | - |
574
+ | 1.2396 | 20500 | 0.2521 | - |
575
+ | 1.2426 | 20550 | 0.2525 | - |
576
+ | 1.2456 | 20600 | 0.2529 | - |
577
+ | 1.2486 | 20650 | 0.253 | - |
578
+ | 1.2517 | 20700 | 0.2529 | - |
579
+ | 1.2547 | 20750 | 0.2537 | - |
580
+ | 1.2577 | 20800 | 0.2532 | - |
581
+ | 1.2607 | 20850 | 0.251 | - |
582
+ | 1.2638 | 20900 | 0.2535 | - |
583
+ | 1.2668 | 20950 | 0.2522 | - |
584
+ | 1.2698 | 21000 | 0.2533 | - |
585
+ | 1.2728 | 21050 | 0.2535 | - |
586
+ | 1.2758 | 21100 | 0.2529 | - |
587
+ | 1.2789 | 21150 | 0.2527 | - |
588
+ | 1.2819 | 21200 | 0.2536 | - |
589
+ | 1.2849 | 21250 | 0.2526 | - |
590
+ | 1.2879 | 21300 | 0.2518 | - |
591
+ | 1.2910 | 21350 | 0.2544 | - |
592
+ | 1.2940 | 21400 | 0.253 | - |
593
+ | 1.2970 | 21450 | 0.2535 | - |
594
+ | 1.3000 | 21500 | 0.253 | - |
595
+ | 1.3031 | 21550 | 0.2527 | - |
596
+ | 1.3061 | 21600 | 0.2525 | - |
597
+ | 1.3091 | 21650 | 0.2521 | - |
598
+ | 1.3121 | 21700 | 0.2522 | - |
599
+ | 1.3152 | 21750 | 0.2513 | - |
600
+ | 1.3182 | 21800 | 0.2525 | - |
601
+ | 1.3212 | 21850 | 0.2528 | - |
602
+ | 1.3242 | 21900 | 0.2523 | - |
603
+ | 1.3272 | 21950 | 0.2527 | - |
604
+ | 1.3303 | 22000 | 0.2514 | - |
605
+ | 1.3333 | 22050 | 0.2529 | - |
606
+ | 1.3363 | 22100 | 0.252 | - |
607
+ | 1.3393 | 22150 | 0.2543 | - |
608
+ | 1.3424 | 22200 | 0.2524 | - |
609
+ | 1.3454 | 22250 | 0.2522 | - |
610
+ | 1.3484 | 22300 | 0.2526 | - |
611
+ | 1.3514 | 22350 | 0.2529 | - |
612
+ | 1.3545 | 22400 | 0.2513 | - |
613
+ | 1.3575 | 22450 | 0.2519 | - |
614
+ | 1.3605 | 22500 | 0.2533 | - |
615
+ | 1.3635 | 22550 | 0.2518 | - |
616
+ | 1.3665 | 22600 | 0.2527 | - |
617
+ | 1.3696 | 22650 | 0.2515 | - |
618
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619
+ | 1.3756 | 22750 | 0.2512 | - |
620
+ | 1.3786 | 22800 | 0.2511 | - |
621
+ | 1.3817 | 22850 | 0.251 | - |
622
+ | 1.3847 | 22900 | 0.252 | - |
623
+ | 1.3877 | 22950 | 0.2521 | - |
624
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625
+ | 1.3938 | 23050 | 0.2542 | - |
626
+ | 1.3968 | 23100 | 0.2515 | - |
627
+ | 1.3998 | 23150 | 0.252 | - |
628
+ | 1.4028 | 23200 | 0.2528 | - |
629
+ | 1.4059 | 23250 | 0.2516 | - |
630
+ | 1.4089 | 23300 | 0.2522 | - |
631
+ | 1.4119 | 23350 | 0.2524 | - |
632
+ | 1.4149 | 23400 | 0.2533 | - |
633
+ | 1.4179 | 23450 | 0.2519 | - |
634
+ | 1.4210 | 23500 | 0.254 | - |
635
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636
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637
+ | 1.4300 | 23650 | 0.2538 | - |
638
+ | 1.4331 | 23700 | 0.2512 | - |
639
+ | 1.4361 | 23750 | 0.252 | - |
640
+ | 1.4391 | 23800 | 0.2532 | - |
641
+ | 1.4421 | 23850 | 0.2512 | - |
642
+ | 1.4452 | 23900 | 0.2533 | - |
643
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644
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645
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646
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647
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648
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649
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650
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651
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652
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653
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654
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655
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656
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657
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658
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659
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660
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661
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662
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663
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664
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665
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666
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667
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668
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669
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670
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671
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672
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673
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674
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675
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676
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677
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678
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679
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680
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681
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682
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683
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684
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685
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686
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687
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688
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689
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690
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691
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692
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693
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694
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695
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696
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697
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698
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699
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700
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701
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702
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703
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704
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705
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706
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707
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708
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709
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710
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711
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712
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713
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714
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715
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716
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717
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718
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719
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720
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721
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722
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723
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724
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725
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726
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727
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728
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729
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730
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731
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732
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733
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734
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735
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736
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737
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738
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739
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740
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741
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742
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743
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744
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745
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746
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747
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748
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749
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750
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751
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752
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753
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754
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755
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756
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757
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758
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759
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760
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761
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762
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763
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764
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765
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766
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767
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768
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769
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770
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771
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772
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773
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774
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775
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776
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777
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778
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779
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780
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781
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782
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783
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784
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785
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786
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787
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788
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789
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790
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791
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792
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793
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794
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795
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796
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797
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798
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799
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800
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801
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802
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803
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804
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805
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806
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807
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808
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809
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810
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811
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812
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813
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814
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815
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816
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817
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818
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819
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820
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821
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822
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823
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824
+ | 1.9954 | 33000 | 0.2512 | - |
825
+ | 1.9984 | 33050 | 0.2507 | - |
826
+ | 2.0 | 33076 | - | 0.5 |
827
+ | 2.0015 | 33100 | 0.2517 | - |
828
+ | 2.0045 | 33150 | 0.2526 | - |
829
+ | 2.0075 | 33200 | 0.2505 | - |
830
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831
+ | 2.0135 | 33300 | 0.2504 | - |
832
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833
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834
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835
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836
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837
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838
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839
+ | 2.0377 | 33700 | 0.2532 | - |
840
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841
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842
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843
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844
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845
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846
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847
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848
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849
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850
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851
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852
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853
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854
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855
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856
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857
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858
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859
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860
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861
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862
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863
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864
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865
+ | 2.1163 | 35000 | 0.2509 | - |
866
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867
+ | 2.1224 | 35100 | 0.2522 | - |
868
+ | 2.1254 | 35150 | 0.2512 | - |
869
+ | 2.1284 | 35200 | 0.2541 | - |
870
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871
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872
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873
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874
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875
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876
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877
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878
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879
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880
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881
+ | 2.1647 | 35800 | 0.252 | - |
882
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883
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884
+ | 2.1738 | 35950 | 0.2509 | - |
885
+ | 2.1768 | 36000 | 0.2523 | - |
886
+ | 2.1798 | 36050 | 0.251 | - |
887
+ | 2.1829 | 36100 | 0.2516 | - |
888
+ | 2.1859 | 36150 | 0.2519 | - |
889
+ | 2.1889 | 36200 | 0.2515 | - |
890
+ | 2.1919 | 36250 | 0.2516 | - |
891
+ | 2.1949 | 36300 | 0.2515 | - |
892
+ | 2.1980 | 36350 | 0.2518 | - |
893
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894
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895
+ | 2.2070 | 36500 | 0.2509 | - |
896
+ | 2.2101 | 36550 | 0.252 | - |
897
+ | 2.2131 | 36600 | 0.2505 | - |
898
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899
+ | 2.2191 | 36700 | 0.2523 | - |
900
+ | 2.2222 | 36750 | 0.2512 | - |
901
+ | 2.2252 | 36800 | 0.2525 | - |
902
+ | 2.2282 | 36850 | 0.2521 | - |
903
+ | 2.2312 | 36900 | 0.2517 | - |
904
+ | 2.2342 | 36950 | 0.2516 | - |
905
+ | 2.2373 | 37000 | 0.2513 | - |
906
+ | 2.2403 | 37050 | 0.2523 | - |
907
+ | 2.2433 | 37100 | 0.2515 | - |
908
+ | 2.2463 | 37150 | 0.2518 | - |
909
+ | 2.2494 | 37200 | 0.2527 | - |
910
+ | 2.2524 | 37250 | 0.2533 | - |
911
+ | 2.2554 | 37300 | 0.2527 | - |
912
+ | 2.2584 | 37350 | 0.2516 | - |
913
+ | 2.2615 | 37400 | 0.2519 | - |
914
+ | 2.2645 | 37450 | 0.2522 | - |
915
+ | 2.2675 | 37500 | 0.2514 | - |
916
+ | 2.2705 | 37550 | 0.2522 | - |
917
+ | 2.2736 | 37600 | 0.2517 | - |
918
+ | 2.2766 | 37650 | 0.2526 | - |
919
+ | 2.2796 | 37700 | 0.2511 | - |
920
+ | 2.2826 | 37750 | 0.2518 | - |
921
+ | 2.2856 | 37800 | 0.252 | - |
922
+ | 2.2887 | 37850 | 0.2517 | - |
923
+ | 2.2917 | 37900 | 0.2516 | - |
924
+ | 2.2947 | 37950 | 0.2517 | - |
925
+ | 2.2977 | 38000 | 0.2503 | - |
926
+ | 2.3008 | 38050 | 0.2524 | - |
927
+ | 2.3038 | 38100 | 0.2512 | - |
928
+ | 2.3068 | 38150 | 0.2525 | - |
929
+ | 2.3098 | 38200 | 0.2526 | - |
930
+ | 2.3129 | 38250 | 0.2498 | - |
931
+ | 2.3159 | 38300 | 0.2508 | - |
932
+ | 2.3189 | 38350 | 0.2526 | - |
933
+ | 2.3219 | 38400 | 0.252 | - |
934
+ | 2.3249 | 38450 | 0.2516 | - |
935
+ | 2.3280 | 38500 | 0.2517 | - |
936
+ | 2.3310 | 38550 | 0.2525 | - |
937
+ | 2.3340 | 38600 | 0.2519 | - |
938
+ | 2.3370 | 38650 | 0.2512 | - |
939
+ | 2.3401 | 38700 | 0.2512 | - |
940
+ | 2.3431 | 38750 | 0.2519 | - |
941
+ | 2.3461 | 38800 | 0.2514 | - |
942
+ | 2.3491 | 38850 | 0.2508 | - |
943
+ | 2.3522 | 38900 | 0.2514 | - |
944
+ | 2.3552 | 38950 | 0.2515 | - |
945
+ | 2.3582 | 39000 | 0.2517 | - |
946
+ | 2.3612 | 39050 | 0.2512 | - |
947
+ | 2.3643 | 39100 | 0.2508 | - |
948
+ | 2.3673 | 39150 | 0.2512 | - |
949
+ | 2.3703 | 39200 | 0.25 | - |
950
+ | 2.3733 | 39250 | 0.251 | - |
951
+ | 2.3763 | 39300 | 0.2527 | - |
952
+ | 2.3794 | 39350 | 0.2534 | - |
953
+ | 2.3824 | 39400 | 0.2511 | - |
954
+ | 2.3854 | 39450 | 0.2511 | - |
955
+ | 2.3884 | 39500 | 0.2511 | - |
956
+ | 2.3915 | 39550 | 0.2516 | - |
957
+ | 2.3945 | 39600 | 0.2516 | - |
958
+ | 2.3975 | 39650 | 0.2509 | - |
959
+ | 2.4005 | 39700 | 0.2517 | - |
960
+ | 2.4036 | 39750 | 0.2515 | - |
961
+ | 2.4066 | 39800 | 0.2532 | - |
962
+ | 2.4096 | 39850 | 0.2517 | - |
963
+ | 2.4126 | 39900 | 0.252 | - |
964
+ | 2.4156 | 39950 | 0.2513 | - |
965
+ | 2.4187 | 40000 | 0.2522 | - |
966
+ | 2.4217 | 40050 | 0.2524 | - |
967
+ | 2.4247 | 40100 | 0.2518 | - |
968
+ | 2.4277 | 40150 | 0.2521 | - |
969
+ | 2.4308 | 40200 | 0.2522 | - |
970
+ | 2.4338 | 40250 | 0.2524 | - |
971
+ | 2.4368 | 40300 | 0.2512 | - |
972
+ | 2.4398 | 40350 | 0.252 | - |
973
+ | 2.4429 | 40400 | 0.2512 | - |
974
+ | 2.4459 | 40450 | 0.2521 | - |
975
+ | 2.4489 | 40500 | 0.2517 | - |
976
+ | 2.4519 | 40550 | 0.2516 | - |
977
+ | 2.4550 | 40600 | 0.251 | - |
978
+ | 2.4580 | 40650 | 0.2527 | - |
979
+ | 2.4610 | 40700 | 0.2518 | - |
980
+ | 2.4640 | 40750 | 0.2518 | - |
981
+ | 2.4670 | 40800 | 0.2521 | - |
982
+ | 2.4701 | 40850 | 0.2521 | - |
983
+ | 2.4731 | 40900 | 0.2519 | - |
984
+ | 2.4761 | 40950 | 0.2514 | - |
985
+ | 2.4791 | 41000 | 0.252 | - |
986
+ | 2.4822 | 41050 | 0.2516 | - |
987
+ | 2.4852 | 41100 | 0.2519 | - |
988
+ | 2.4882 | 41150 | 0.2517 | - |
989
+ | 2.4912 | 41200 | 0.2513 | - |
990
+ | 2.4943 | 41250 | 0.252 | - |
991
+ | 2.4973 | 41300 | 0.2513 | - |
992
+ | 2.5003 | 41350 | 0.2512 | - |
993
+ | 2.5033 | 41400 | 0.2504 | - |
994
+ | 2.5063 | 41450 | 0.2509 | - |
995
+ | 2.5094 | 41500 | 0.2523 | - |
996
+ | 2.5124 | 41550 | 0.2514 | - |
997
+ | 2.5154 | 41600 | 0.2529 | - |
998
+ | 2.5184 | 41650 | 0.2526 | - |
999
+ | 2.5215 | 41700 | 0.2519 | - |
1000
+ | 2.5245 | 41750 | 0.2503 | - |
1001
+ | 2.5275 | 41800 | 0.2517 | - |
1002
+ | 2.5305 | 41850 | 0.2528 | - |
1003
+ | 2.5336 | 41900 | 0.2519 | - |
1004
+ | 2.5366 | 41950 | 0.2497 | - |
1005
+ | 2.5396 | 42000 | 0.2527 | - |
1006
+ | 2.5426 | 42050 | 0.2521 | - |
1007
+ | 2.5457 | 42100 | 0.2522 | - |
1008
+ | 2.5487 | 42150 | 0.2512 | - |
1009
+ | 2.5517 | 42200 | 0.2519 | - |
1010
+ | 2.5547 | 42250 | 0.2525 | - |
1011
+ | 2.5577 | 42300 | 0.2518 | - |
1012
+ | 2.5608 | 42350 | 0.2517 | - |
1013
+ | 2.5638 | 42400 | 0.2509 | - |
1014
+ | 2.5668 | 42450 | 0.2508 | - |
1015
+ | 2.5698 | 42500 | 0.2513 | - |
1016
+ | 2.5729 | 42550 | 0.251 | - |
1017
+ | 2.5759 | 42600 | 0.2512 | - |
1018
+ | 2.5789 | 42650 | 0.2527 | - |
1019
+ | 2.5819 | 42700 | 0.2531 | - |
1020
+ | 2.5850 | 42750 | 0.2504 | - |
1021
+ | 2.5880 | 42800 | 0.2523 | - |
1022
+ | 2.5910 | 42850 | 0.2506 | - |
1023
+ | 2.5940 | 42900 | 0.2529 | - |
1024
+ | 2.5970 | 42950 | 0.252 | - |
1025
+ | 2.6001 | 43000 | 0.2516 | - |
1026
+ | 2.6031 | 43050 | 0.2504 | - |
1027
+ | 2.6061 | 43100 | 0.2519 | - |
1028
+ | 2.6091 | 43150 | 0.2504 | - |
1029
+ | 2.6122 | 43200 | 0.2518 | - |
1030
+ | 2.6152 | 43250 | 0.2515 | - |
1031
+ | 2.6182 | 43300 | 0.2517 | - |
1032
+ | 2.6212 | 43350 | 0.2526 | - |
1033
+ | 2.6243 | 43400 | 0.2507 | - |
1034
+ | 2.6273 | 43450 | 0.2511 | - |
1035
+ | 2.6303 | 43500 | 0.2504 | - |
1036
+ | 2.6333 | 43550 | 0.2512 | - |
1037
+ | 2.6364 | 43600 | 0.251 | - |
1038
+ | 2.6394 | 43650 | 0.2519 | - |
1039
+ | 2.6424 | 43700 | 0.2509 | - |
1040
+ | 2.6454 | 43750 | 0.2517 | - |
1041
+ | 2.6484 | 43800 | 0.2516 | - |
1042
+ | 2.6515 | 43850 | 0.2509 | - |
1043
+ | 2.6545 | 43900 | 0.2526 | - |
1044
+ | 2.6575 | 43950 | 0.2524 | - |
1045
+ | 2.6605 | 44000 | 0.2507 | - |
1046
+ | 2.6636 | 44050 | 0.2527 | - |
1047
+ | 2.6666 | 44100 | 0.2511 | - |
1048
+ | 2.6696 | 44150 | 0.252 | - |
1049
+ | 2.6726 | 44200 | 0.2519 | - |
1050
+ | 2.6757 | 44250 | 0.2503 | - |
1051
+ | 2.6787 | 44300 | 0.2517 | - |
1052
+ | 2.6817 | 44350 | 0.2524 | - |
1053
+ | 2.6847 | 44400 | 0.2521 | - |
1054
+ | 2.6877 | 44450 | 0.2533 | - |
1055
+ | 2.6908 | 44500 | 0.2526 | - |
1056
+ | 2.6938 | 44550 | 0.2513 | - |
1057
+ | 2.6968 | 44600 | 0.2509 | - |
1058
+ | 2.6998 | 44650 | 0.2525 | - |
1059
+ | 2.7029 | 44700 | 0.2521 | - |
1060
+ | 2.7059 | 44750 | 0.2521 | - |
1061
+ | 2.7089 | 44800 | 0.2528 | - |
1062
+ | 2.7119 | 44850 | 0.2513 | - |
1063
+ | 2.7150 | 44900 | 0.2509 | - |
1064
+ | 2.7180 | 44950 | 0.2515 | - |
1065
+ | 2.7210 | 45000 | 0.2507 | - |
1066
+ | 2.7240 | 45050 | 0.2516 | - |
1067
+ | 2.7271 | 45100 | 0.2518 | - |
1068
+ | 2.7301 | 45150 | 0.2519 | - |
1069
+ | 2.7331 | 45200 | 0.2518 | - |
1070
+ | 2.7361 | 45250 | 0.2522 | - |
1071
+ | 2.7391 | 45300 | 0.2525 | - |
1072
+ | 2.7422 | 45350 | 0.2522 | - |
1073
+ | 2.7452 | 45400 | 0.2501 | - |
1074
+ | 2.7482 | 45450 | 0.2515 | - |
1075
+ | 2.7512 | 45500 | 0.2505 | - |
1076
+ | 2.7543 | 45550 | 0.2505 | - |
1077
+ | 2.7573 | 45600 | 0.252 | - |
1078
+ | 2.7603 | 45650 | 0.2507 | - |
1079
+ | 2.7633 | 45700 | 0.2519 | - |
1080
+ | 2.7664 | 45750 | 0.2523 | - |
1081
+ | 2.7694 | 45800 | 0.252 | - |
1082
+ | 2.7724 | 45850 | 0.2515 | - |
1083
+ | 2.7754 | 45900 | 0.2512 | - |
1084
+ | 2.7784 | 45950 | 0.2509 | - |
1085
+ | 2.7815 | 46000 | 0.2516 | - |
1086
+ | 2.7845 | 46050 | 0.2512 | - |
1087
+ | 2.7875 | 46100 | 0.2516 | - |
1088
+ | 2.7905 | 46150 | 0.2518 | - |
1089
+ | 2.7936 | 46200 | 0.2504 | - |
1090
+ | 2.7966 | 46250 | 0.2511 | - |
1091
+ | 2.7996 | 46300 | 0.2518 | - |
1092
+ | 2.8026 | 46350 | 0.2513 | - |
1093
+ | 2.8057 | 46400 | 0.2514 | - |
1094
+ | 2.8087 | 46450 | 0.2522 | - |
1095
+ | 2.8117 | 46500 | 0.2524 | - |
1096
+ | 2.8147 | 46550 | 0.2499 | - |
1097
+ | 2.8178 | 46600 | 0.2506 | - |
1098
+ | 2.8208 | 46650 | 0.2514 | - |
1099
+ | 2.8238 | 46700 | 0.2515 | - |
1100
+ | 2.8268 | 46750 | 0.2524 | - |
1101
+ | 2.8298 | 46800 | 0.2508 | - |
1102
+ | 2.8329 | 46850 | 0.2516 | - |
1103
+ | 2.8359 | 46900 | 0.2508 | - |
1104
+ | 2.8389 | 46950 | 0.2528 | - |
1105
+ | 2.8419 | 47000 | 0.2523 | - |
1106
+ | 2.8450 | 47050 | 0.2517 | - |
1107
+ | 2.8480 | 47100 | 0.2514 | - |
1108
+ | 2.8510 | 47150 | 0.2522 | - |
1109
+ | 2.8540 | 47200 | 0.2511 | - |
1110
+ | 2.8571 | 47250 | 0.2508 | - |
1111
+ | 2.8601 | 47300 | 0.2518 | - |
1112
+ | 2.8631 | 47350 | 0.2515 | - |
1113
+ | 2.8661 | 47400 | 0.2501 | - |
1114
+ | 2.8691 | 47450 | 0.252 | - |
1115
+ | 2.8722 | 47500 | 0.251 | - |
1116
+ | 2.8752 | 47550 | 0.252 | - |
1117
+ | 2.8782 | 47600 | 0.2524 | - |
1118
+ | 2.8812 | 47650 | 0.2505 | - |
1119
+ | 2.8843 | 47700 | 0.2511 | - |
1120
+ | 2.8873 | 47750 | 0.251 | - |
1121
+ | 2.8903 | 47800 | 0.2518 | - |
1122
+ | 2.8933 | 47850 | 0.2516 | - |
1123
+ | 2.8964 | 47900 | 0.252 | - |
1124
+ | 2.8994 | 47950 | 0.2516 | - |
1125
+ | 2.9024 | 48000 | 0.2525 | - |
1126
+ | 2.9054 | 48050 | 0.2519 | - |
1127
+ | 2.9085 | 48100 | 0.2512 | - |
1128
+ | 2.9115 | 48150 | 0.2513 | - |
1129
+ | 2.9145 | 48200 | 0.251 | - |
1130
+ | 2.9175 | 48250 | 0.2517 | - |
1131
+ | 2.9205 | 48300 | 0.2513 | - |
1132
+ | 2.9236 | 48350 | 0.2524 | - |
1133
+ | 2.9266 | 48400 | 0.2512 | - |
1134
+ | 2.9296 | 48450 | 0.2521 | - |
1135
+ | 2.9326 | 48500 | 0.2512 | - |
1136
+ | 2.9357 | 48550 | 0.2501 | - |
1137
+ | 2.9387 | 48600 | 0.2507 | - |
1138
+ | 2.9417 | 48650 | 0.2514 | - |
1139
+ | 2.9447 | 48700 | 0.2518 | - |
1140
+ | 2.9478 | 48750 | 0.2517 | - |
1141
+ | 2.9508 | 48800 | 0.2507 | - |
1142
+ | 2.9538 | 48850 | 0.2516 | - |
1143
+ | 2.9568 | 48900 | 0.2513 | - |
1144
+ | 2.9599 | 48950 | 0.2505 | - |
1145
+ | 2.9629 | 49000 | 0.252 | - |
1146
+ | 2.9659 | 49050 | 0.2515 | - |
1147
+ | 2.9689 | 49100 | 0.2513 | - |
1148
+ | 2.9719 | 49150 | 0.2523 | - |
1149
+ | 2.9750 | 49200 | 0.2502 | - |
1150
+ | 2.9780 | 49250 | 0.2514 | - |
1151
+ | 2.9810 | 49300 | 0.2527 | - |
1152
+ | 2.9840 | 49350 | 0.2515 | - |
1153
+ | 2.9871 | 49400 | 0.2519 | - |
1154
+ | 2.9901 | 49450 | 0.251 | - |
1155
+ | 2.9931 | 49500 | 0.2513 | - |
1156
+ | 2.9961 | 49550 | 0.2515 | - |
1157
+ | 2.9992 | 49600 | 0.2504 | - |
1158
+ | 3.0 | 49614 | - | 0.5 |
1159
+ | 3.0022 | 49650 | 0.2525 | - |
1160
+ | 3.0052 | 49700 | 0.2507 | - |
1161
+ | 3.0082 | 49750 | 0.2514 | - |
1162
+ | 3.0112 | 49800 | 0.251 | - |
1163
+ | 3.0143 | 49850 | 0.2512 | - |
1164
+ | 3.0173 | 49900 | 0.2514 | - |
1165
+ | 3.0203 | 49950 | 0.251 | - |
1166
+ | 3.0233 | 50000 | 0.2513 | - |
1167
+ | 3.0264 | 50050 | 0.2518 | - |
1168
+ | 3.0294 | 50100 | 0.2503 | - |
1169
+ | 3.0324 | 50150 | 0.2507 | - |
1170
+ | 3.0354 | 50200 | 0.2509 | - |
1171
+ | 3.0385 | 50250 | 0.2516 | - |
1172
+ | 3.0415 | 50300 | 0.2517 | - |
1173
+ | 3.0445 | 50350 | 0.2512 | - |
1174
+ | 3.0475 | 50400 | 0.2509 | - |
1175
+ | 3.0506 | 50450 | 0.2514 | - |
1176
+ | 3.0536 | 50500 | 0.252 | - |
1177
+ | 3.0566 | 50550 | 0.2513 | - |
1178
+ | 3.0596 | 50600 | 0.2501 | - |
1179
+ | 3.0626 | 50650 | 0.2503 | - |
1180
+ | 3.0657 | 50700 | 0.2514 | - |
1181
+ | 3.0687 | 50750 | 0.2504 | - |
1182
+ | 3.0717 | 50800 | 0.251 | - |
1183
+ | 3.0747 | 50850 | 0.2511 | - |
1184
+ | 3.0778 | 50900 | 0.2511 | - |
1185
+ | 3.0808 | 50950 | 0.2505 | - |
1186
+ | 3.0838 | 51000 | 0.2509 | - |
1187
+ | 3.0868 | 51050 | 0.2508 | - |
1188
+ | 3.0899 | 51100 | 0.2521 | - |
1189
+ | 3.0929 | 51150 | 0.2515 | - |
1190
+ | 3.0959 | 51200 | 0.2519 | - |
1191
+ | 3.0989 | 51250 | 0.2511 | - |
1192
+ | 3.1019 | 51300 | 0.2522 | - |
1193
+ | 3.1050 | 51350 | 0.2519 | - |
1194
+ | 3.1080 | 51400 | 0.2524 | - |
1195
+ | 3.1110 | 51450 | 0.2527 | - |
1196
+ | 3.1140 | 51500 | 0.2512 | - |
1197
+ | 3.1171 | 51550 | 0.2515 | - |
1198
+ | 3.1201 | 51600 | 0.2519 | - |
1199
+ | 3.1231 | 51650 | 0.2502 | - |
1200
+ | 3.1261 | 51700 | 0.2517 | - |
1201
+ | 3.1292 | 51750 | 0.2511 | - |
1202
+ | 3.1322 | 51800 | 0.2516 | - |
1203
+ | 3.1352 | 51850 | 0.2504 | - |
1204
+ | 3.1382 | 51900 | 0.2508 | - |
1205
+ | 3.1413 | 51950 | 0.2514 | - |
1206
+ | 3.1443 | 52000 | 0.2505 | - |
1207
+ | 3.1473 | 52050 | 0.2515 | - |
1208
+ | 3.1503 | 52100 | 0.2514 | - |
1209
+ | 3.1533 | 52150 | 0.2509 | - |
1210
+ | 3.1564 | 52200 | 0.2515 | - |
1211
+ | 3.1594 | 52250 | 0.251 | - |
1212
+ | 3.1624 | 52300 | 0.2521 | - |
1213
+ | 3.1654 | 52350 | 0.2507 | - |
1214
+ | 3.1685 | 52400 | 0.2518 | - |
1215
+ | 3.1715 | 52450 | 0.2509 | - |
1216
+ | 3.1745 | 52500 | 0.2517 | - |
1217
+ | 3.1775 | 52550 | 0.25 | - |
1218
+ | 3.1806 | 52600 | 0.251 | - |
1219
+ | 3.1836 | 52650 | 0.2517 | - |
1220
+ | 3.1866 | 52700 | 0.25 | - |
1221
+ | 3.1896 | 52750 | 0.2514 | - |
1222
+ | 3.1926 | 52800 | 0.2506 | - |
1223
+ | 3.1957 | 52850 | 0.2517 | - |
1224
+ | 3.1987 | 52900 | 0.2516 | - |
1225
+ | 3.2017 | 52950 | 0.2503 | - |
1226
+ | 3.2047 | 53000 | 0.2517 | - |
1227
+ | 3.2078 | 53050 | 0.2513 | - |
1228
+ | 3.2108 | 53100 | 0.2508 | - |
1229
+ | 3.2138 | 53150 | 0.2509 | - |
1230
+ | 3.2168 | 53200 | 0.2517 | - |
1231
+ | 3.2199 | 53250 | 0.2504 | - |
1232
+ | 3.2229 | 53300 | 0.2513 | - |
1233
+ | 3.2259 | 53350 | 0.2519 | - |
1234
+ | 3.2289 | 53400 | 0.2518 | - |
1235
+ | 3.2320 | 53450 | 0.2514 | - |
1236
+ | 3.2350 | 53500 | 0.2512 | - |
1237
+ | 3.2380 | 53550 | 0.2525 | - |
1238
+ | 3.2410 | 53600 | 0.2501 | - |
1239
+ | 3.2440 | 53650 | 0.2517 | - |
1240
+ | 3.2471 | 53700 | 0.2516 | - |
1241
+ | 3.2501 | 53750 | 0.2513 | - |
1242
+ | 3.2531 | 53800 | 0.2504 | - |
1243
+ | 3.2561 | 53850 | 0.2495 | - |
1244
+ | 3.2592 | 53900 | 0.25 | - |
1245
+ | 3.2622 | 53950 | 0.2522 | - |
1246
+ | 3.2652 | 54000 | 0.2519 | - |
1247
+ | 3.2682 | 54050 | 0.2519 | - |
1248
+ | 3.2713 | 54100 | 0.2514 | - |
1249
+ | 3.2743 | 54150 | 0.2516 | - |
1250
+ | 3.2773 | 54200 | 0.2512 | - |
1251
+ | 3.2803 | 54250 | 0.2511 | - |
1252
+ | 3.2833 | 54300 | 0.2513 | - |
1253
+ | 3.2864 | 54350 | 0.2509 | - |
1254
+ | 3.2894 | 54400 | 0.2514 | - |
1255
+ | 3.2924 | 54450 | 0.2516 | - |
1256
+ | 3.2954 | 54500 | 0.2515 | - |
1257
+ | 3.2985 | 54550 | 0.2512 | - |
1258
+ | 3.3015 | 54600 | 0.2504 | - |
1259
+ | 3.3045 | 54650 | 0.2506 | - |
1260
+ | 3.3075 | 54700 | 0.2512 | - |
1261
+ | 3.3106 | 54750 | 0.2502 | - |
1262
+ | 3.3136 | 54800 | 0.25 | - |
1263
+ | 3.3166 | 54850 | 0.252 | - |
1264
+ | 3.3196 | 54900 | 0.252 | - |
1265
+ | 3.3227 | 54950 | 0.2512 | - |
1266
+ | 3.3257 | 55000 | 0.2504 | - |
1267
+ | 3.3287 | 55050 | 0.252 | - |
1268
+ | 3.3317 | 55100 | 0.2515 | - |
1269
+ | 3.3347 | 55150 | 0.2512 | - |
1270
+ | 3.3378 | 55200 | 0.2508 | - |
1271
+ | 3.3408 | 55250 | 0.2507 | - |
1272
+ | 3.3438 | 55300 | 0.2505 | - |
1273
+ | 3.3468 | 55350 | 0.252 | - |
1274
+ | 3.3499 | 55400 | 0.2509 | - |
1275
+ | 3.3529 | 55450 | 0.2512 | - |
1276
+ | 3.3559 | 55500 | 0.251 | - |
1277
+ | 3.3589 | 55550 | 0.2503 | - |
1278
+ | 3.3620 | 55600 | 0.2511 | - |
1279
+ | 3.3650 | 55650 | 0.2516 | - |
1280
+ | 3.3680 | 55700 | 0.2511 | - |
1281
+ | 3.3710 | 55750 | 0.2517 | - |
1282
+ | 3.3740 | 55800 | 0.2509 | - |
1283
+ | 3.3771 | 55850 | 0.2519 | - |
1284
+ | 3.3801 | 55900 | 0.2518 | - |
1285
+ | 3.3831 | 55950 | 0.2504 | - |
1286
+ | 3.3861 | 56000 | 0.2511 | - |
1287
+ | 3.3892 | 56050 | 0.252 | - |
1288
+ | 3.3922 | 56100 | 0.252 | - |
1289
+ | 3.3952 | 56150 | 0.2511 | - |
1290
+ | 3.3982 | 56200 | 0.2507 | - |
1291
+ | 3.4013 | 56250 | 0.2504 | - |
1292
+ | 3.4043 | 56300 | 0.2508 | - |
1293
+ | 3.4073 | 56350 | 0.2505 | - |
1294
+ | 3.4103 | 56400 | 0.2514 | - |
1295
+ | 3.4134 | 56450 | 0.2503 | - |
1296
+ | 3.4164 | 56500 | 0.2509 | - |
1297
+ | 3.4194 | 56550 | 0.2517 | - |
1298
+ | 3.4224 | 56600 | 0.2507 | - |
1299
+ | 3.4254 | 56650 | 0.2518 | - |
1300
+ | 3.4285 | 56700 | 0.2504 | - |
1301
+ | 3.4315 | 56750 | 0.2524 | - |
1302
+ | 3.4345 | 56800 | 0.2507 | - |
1303
+ | 3.4375 | 56850 | 0.2511 | - |
1304
+ | 3.4406 | 56900 | 0.2518 | - |
1305
+ | 3.4436 | 56950 | 0.2514 | - |
1306
+ | 3.4466 | 57000 | 0.2511 | - |
1307
+ | 3.4496 | 57050 | 0.251 | - |
1308
+ | 3.4527 | 57100 | 0.2521 | - |
1309
+ | 3.4557 | 57150 | 0.2505 | - |
1310
+ | 3.4587 | 57200 | 0.2505 | - |
1311
+ | 3.4617 | 57250 | 0.2519 | - |
1312
+ | 3.4647 | 57300 | 0.2515 | - |
1313
+ | 3.4678 | 57350 | 0.252 | - |
1314
+ | 3.4708 | 57400 | 0.2501 | - |
1315
+ | 3.4738 | 57450 | 0.2509 | - |
1316
+ | 3.4768 | 57500 | 0.2514 | - |
1317
+ | 3.4799 | 57550 | 0.2505 | - |
1318
+ | 3.4829 | 57600 | 0.2509 | - |
1319
+ | 3.4859 | 57650 | 0.2505 | - |
1320
+ | 3.4889 | 57700 | 0.2505 | - |
1321
+ | 3.4920 | 57750 | 0.2517 | - |
1322
+ | 3.4950 | 57800 | 0.251 | - |
1323
+ | 3.4980 | 57850 | 0.2507 | - |
1324
+ | 3.5010 | 57900 | 0.2509 | - |
1325
+ | 3.5041 | 57950 | 0.2502 | - |
1326
+ | 3.5071 | 58000 | 0.2517 | - |
1327
+ | 3.5101 | 58050 | 0.2517 | - |
1328
+ | 3.5131 | 58100 | 0.252 | - |
1329
+ | 3.5161 | 58150 | 0.2504 | - |
1330
+ | 3.5192 | 58200 | 0.2513 | - |
1331
+ | 3.5222 | 58250 | 0.2507 | - |
1332
+ | 3.5252 | 58300 | 0.251 | - |
1333
+ | 3.5282 | 58350 | 0.2499 | - |
1334
+ | 3.5313 | 58400 | 0.2519 | - |
1335
+ | 3.5343 | 58450 | 0.2514 | - |
1336
+ | 3.5373 | 58500 | 0.2504 | - |
1337
+ | 3.5403 | 58550 | 0.2505 | - |
1338
+ | 3.5434 | 58600 | 0.2506 | - |
1339
+ | 3.5464 | 58650 | 0.2517 | - |
1340
+ | 3.5494 | 58700 | 0.251 | - |
1341
+ | 3.5524 | 58750 | 0.2509 | - |
1342
+ | 3.5554 | 58800 | 0.2514 | - |
1343
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+
1492
+ ### Framework Versions
1493
+ - Python: 3.11.11
1494
+ - SetFit: 1.1.1
1495
+ - Sentence Transformers: 3.4.1
1496
+ - Transformers: 4.49.0
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+ - PyTorch: 2.4.1.post300
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+ - Datasets: 3.4.0
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+ - Tokenizers: 0.21.0
1500
+
1501
+ ## Citation
1502
+
1503
+ ### BibTeX
1504
+ ```bibtex
1505
+ @article{https://doi.org/10.48550/arxiv.2209.11055,
1506
+ doi = {10.48550/ARXIV.2209.11055},
1507
+ url = {https://arxiv.org/abs/2209.11055},
1508
+ author = {Tunstall, Lewis and Reimers, Nils and Jo, Unso Eun Seo and Bates, Luke and Korat, Daniel and Wasserblat, Moshe and Pereg, Oren},
1509
+ keywords = {Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences},
1510
+ title = {Efficient Few-Shot Learning Without Prompts},
1511
+ publisher = {arXiv},
1512
+ year = {2022},
1513
+ copyright = {Creative Commons Attribution 4.0 International}
1514
+ }
1515
+ ```
1516
+
1517
+ <!--
1518
+ ## Glossary
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+
1520
+ *Clearly define terms in order to be accessible across audiences.*
1521
+ -->
1522
+
1523
+ <!--
1524
+ ## Model Card Authors
1525
+
1526
+ *Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.*
1527
+ -->
1528
+
1529
+ <!--
1530
+ ## Model Card Contact
1531
+
1532
+ *Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.*
1533
+ -->
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