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README.md ADDED
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+ ---
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+ base_model: roberta-large
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+ datasets:
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+ - YurtsAI/named_entity_recognition_document_context
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+ language:
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+ - en
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+ library_name: span-marker
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+ metrics:
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+ - precision
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+ - recall
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+ - f1
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+ pipeline_tag: token-classification
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+ tags:
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+ - span-marker
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+ - token-classification
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+ - ner
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+ - named-entity-recognition
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+ - generated_from_span_marker_trainer
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+ widget:
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+ - text: '* * phone call transcript: university research paper discussion * * * * date:
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+ * * 09041942 * * time: * * 3:45 pm * * participants: * * dr. emily carter (ec)
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+ - principal investigator dr. john smith (js) - co-investigator--- * * ec: * *
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+ hey john, got a minute to discuss the latest draft of our paper on crispr-cas9?'
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+ - text: monday is a chill day – beach time at barceloneta and maybe some shopping
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+ at la rambla.
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+ - text: don't forget to fast for at least 8 hours before the procedure – that means
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+ no food or drink after midnight!
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+ - text: whether it's buying a house in 5 years, saving for a killer vacation next
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+ summer, or just building an emergency fund, write it down.
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+ - text: '- * * full integration: * * all recipes from the rbso must be incorporated
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+ into event menus by november 1, 2023.'
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+ model-index:
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+ - name: SpanMarker with roberta-large on YurtsAI/named_entity_recognition_document_context
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+ results:
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+ - task:
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+ type: token-classification
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+ name: Named Entity Recognition
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+ dataset:
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+ name: Unknown
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+ type: YurtsAI/named_entity_recognition_document_context
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+ split: eval
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+ metrics:
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+ - type: f1
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+ value: 0.8349078585045542
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+ name: F1
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+ - type: precision
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+ value: 0.8308950630296387
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+ name: Precision
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+ - type: recall
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+ value: 0.8389596015495296
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+ name: Recall
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+ ---
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+
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+ # SpanMarker with roberta-large on YurtsAI/named_entity_recognition_document_context
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+
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+ This is a [SpanMarker](https://github.com/tomaarsen/SpanMarkerNER) model trained on the [YurtsAI/named_entity_recognition_document_context](https://huggingface.co/datasets/YurtsAI/named_entity_recognition_document_context) dataset that can be used for Named Entity Recognition. This SpanMarker model uses [roberta-large](https://huggingface.co/roberta-large) as the underlying encoder.
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+
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+ ## Model Details
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+
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+ ### Model Description
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+ - **Model Type:** SpanMarker
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+ - **Encoder:** [roberta-large](https://huggingface.co/roberta-large)
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+ - **Maximum Sequence Length:** 256 tokens
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+ - **Maximum Entity Length:** 11 words
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+ - **Training Dataset:** [YurtsAI/named_entity_recognition_document_context](https://huggingface.co/datasets/YurtsAI/named_entity_recognition_document_context)
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+ - **Language:** en
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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:** [SpanMarker on GitHub](https://github.com/tomaarsen/SpanMarkerNER)
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+ - **Thesis:** [SpanMarker For Named Entity Recognition](https://raw.githubusercontent.com/tomaarsen/SpanMarkerNER/main/thesis.pdf)
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+
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+ ### Model Labels
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+ | Label | Examples |
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+ |:--------------------------------------------------|:------------------------------------------------------------------------------------------------------------------------------|
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+ | DATETIME__absolute | "14:00 hrs", "15th november 2023 at 10:00 am", "october 15th , 2023" |
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+ | DATETIME__authored | "25 february 26", "sunday , 21 august , 1938", "1961-05-08" |
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+ | DATETIME__range | "29th of oct. , 2023", "september 2021 to august 2023", "jan 2022 - dec 2022" |
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+ | DATETIME__relative | "eod friday", "dec 15 , 11:59 pm", "10/15" |
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+ | GENERAL__art-broadcastprogram | "stranger things", "live q & a", "product design concept sketchbook for kids" |
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+ | GENERAL__art-film | "the crown", "kill bill", "stranger things" |
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+ | GENERAL__art-music | |
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+ | GENERAL__art-other | "statue of liberty", "broadway show", "wicked" |
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+ | GENERAL__art-painting | "draw your dream house", "design a superhero costume" |
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+ | GENERAL__art-writtenart | "optimization of quantum algorithms for cryptographic applications", "introduction to algorithms", "intro to cs '' by j. doe" |
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+ | GENERAL__building-airport | "ory", "charles de gaulle", "cdg" |
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+ | GENERAL__building-hospital | "green valley clinic", "department of oncology", "st. mary 's hospital" |
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+ | GENERAL__building-hotel | "le jules verne", "hôtel ritz", "the beverly hills hotel" |
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+ | GENERAL__building-library | "ancient library", "the grand library", "jefferson library" |
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+ | GENERAL__building-other | "louvre museum", "engineering building", "eiffel tower" |
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+ | GENERAL__building-restaurant | "l'ambroisie", "bella 's bistro", "in-n-out burger" |
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+ | GENERAL__building-sportsfacility | "fenway" |
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+ | GENERAL__building-theater | "gershwin theatre", "opera house", "broadway" |
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+ | GENERAL__event-attack/battle/war/militaryconflict | "1863 battle of ridgefield", "battle of gettysburg", "war of 1812" |
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+ | GENERAL__event-other | "annual science fair", "summer splash '23", "research methodology workshop" |
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+ | GENERAL__event-sportsevent | "international olympiad in informatics", "ftx", "ioi" |
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+ | GENERAL__location-GPE | "fr", "paris ,", "italy" |
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+ | GENERAL__location-bodiesofwater | "river x", "river blue", "seine river" |
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+ | GENERAL__location-island | "maldives", "similan islands", "ellis island" |
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+ | GENERAL__location-mountain | "andes mountains", "swiss alps", "pine ridge" |
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+ | GENERAL__location-other | "times square", "old market", "venice beach" |
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+ | GENERAL__location-park | "central park", "ueno park", "universal studios" |
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+ | GENERAL__location-road/railway/highway/transit | "i-95", "underground railroad", "hollywood walk of fame" |
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+ | GENERAL__organization-company | "green earth organics", "xyz corporation", "north atlantic fisheries" |
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+ | GENERAL__organization-education | "graduate school", "xyz", "xyz university" |
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+ | GENERAL__organization-government/governmentagency | "department of economic development", "moe", "ministry of environment" |
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+ | GENERAL__organization-media/newspaper | "pinterest", "yelp", "insta" |
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+ | GENERAL__organization-other | "historical society", "grants office", "admissions committee" |
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+ | GENERAL__organization-religion | "buddhist", "zen buddhist", "shinto" |
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+ | GENERAL__organization-showorganization | "phare", "the soundbytes" |
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+ | GENERAL__organization-sportsteam | "varsity soccer team", "red sox" |
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+ | GENERAL__other-astronomything | |
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+ | GENERAL__other-award | "team excellence award", "innovation award", "employee of the month" |
115
+ | GENERAL__other-biologything | "fodmap", "troponin i", "cmp" |
116
+ | GENERAL__other-chemicalthing | "co2", "pm2.5", "nitrate" |
117
+ | GENERAL__other-currency | "usd", "inr", "$ $ $" |
118
+ | GENERAL__other-disease | "mi", "irritable bowel syndrome", "myocardial infarction" |
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+ | GENERAL__other-educationaldegree | "executive mba", "phd in quantum computing ,", "phd" |
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+ | GENERAL__other-god | "inari", "athena", "inari taisha" |
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+ | GENERAL__other-language | "french", "english", "spanish" |
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+ | GENERAL__other-law | "cas", "clean air standards", "environmental protection act ( epa ) 2023" |
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+ | GENERAL__other-livingthing | "eastern box turtle", "monarch butterfly", "western burrowing owl" |
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+ | GENERAL__other-medical | "asa", "dapt", "clopidogrel" |
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+ | GENERAL__person-artist/author | "carol", "picasso", "warhol" |
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+ | GENERAL__person-other | "jamie", "sarah", "mark" |
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+ | GENERAL__person-politician | "jane doe", "vespasian", "constantine i" |
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+ | GENERAL__person-scholar | "dr. smith", "dr. lee", "dr. johnson" |
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+ | GENERAL__person-soldier | "davis", "lt. sarah johnson", "col. r. johnson" |
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+ | GENERAL__product-airplane | "hmmwvs", "uh-60s", "m1a2s" |
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+ | GENERAL__product-car | "hmmwvs", "high mobility multipurpose wheeled vehicles", "mine-resistant ambush protected" |
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+ | GENERAL__product-food | "pumpkin spice", "quinoa salad", "golden jubilee feast" |
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+ | GENERAL__product-game | "stardew valley", "valorant", "call of duty : warzone" |
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+ | GENERAL__product-other | "engagement metrics", "xj-200", "smart goal templates" |
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+ | GENERAL__product-ship | "liberty island ferry", "hms victory", "thames river cruise" |
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+ | GENERAL__product-software | "instagram", "svm", "r" |
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+ | GENERAL__product-train | "n'ex", "shinkansen", "tgv" |
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+ | GENERAL__product-weapon | "m1 abrams", "m4 carbine", "m4 carbines" |
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+
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+ ## Evaluation
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+
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+ ### Metrics
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+ | Label | Precision | Recall | F1 |
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+ |:--------------------------------------------------|:----------|:-------|:-------|
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+ | **all** | 0.8309 | 0.8390 | 0.8349 |
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+ | DATETIME__absolute | 0.8744 | 0.8577 | 0.8660 |
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+ | DATETIME__authored | 0.9956 | 0.9935 | 0.9946 |
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+ | DATETIME__range | 0.8451 | 0.9262 | 0.8838 |
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+ | DATETIME__relative | 0.8266 | 0.7498 | 0.7863 |
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+ | GENERAL__art-broadcastprogram | 0.6538 | 0.6296 | 0.6415 |
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+ | GENERAL__art-film | 0.8 | 1.0 | 0.8889 |
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+ | GENERAL__art-music | 0.0 | 0.0 | 0.0 |
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+ | GENERAL__art-other | 0.625 | 0.7143 | 0.6667 |
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+ | GENERAL__art-painting | 0.0 | 0.0 | 0.0 |
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+ | GENERAL__art-writtenart | 0.7373 | 0.8047 | 0.7695 |
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+ | GENERAL__building-airport | 0.8668 | 0.9689 | 0.9150 |
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+ | GENERAL__building-hospital | 0.8378 | 0.9323 | 0.8826 |
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+ | GENERAL__building-hotel | 0.7577 | 0.8603 | 0.8057 |
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+ | GENERAL__building-library | 0.0 | 0.0 | 0.0 |
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+ | GENERAL__building-other | 0.7597 | 0.8409 | 0.7982 |
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+ | GENERAL__building-restaurant | 0.7953 | 0.8695 | 0.8307 |
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+ | GENERAL__building-sportsfacility | 0.0 | 0.0 | 0.0 |
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+ | GENERAL__building-theater | 0.6 | 0.6667 | 0.6316 |
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+ | GENERAL__event-attack/battle/war/militaryconflict | 0.8438 | 0.9310 | 0.8852 |
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+ | GENERAL__event-other | 0.6019 | 0.6382 | 0.6195 |
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+ | GENERAL__event-sportsevent | 0.0 | 0.0 | 0.0 |
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+ | GENERAL__location-GPE | 0.7232 | 0.7888 | 0.7546 |
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+ | GENERAL__location-bodiesofwater | 0.6724 | 0.975 | 0.7959 |
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+ | GENERAL__location-island | 0.7455 | 0.9111 | 0.8200 |
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+ | GENERAL__location-mountain | 0.7436 | 0.8529 | 0.7945 |
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+ | GENERAL__location-other | 0.7186 | 0.7793 | 0.7477 |
172
+ | GENERAL__location-park | 0.7899 | 0.8704 | 0.8282 |
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+ | GENERAL__location-road/railway/highway/transit | 0.6325 | 0.7095 | 0.6688 |
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+ | GENERAL__organization-company | 0.8665 | 0.8605 | 0.8635 |
175
+ | GENERAL__organization-education | 0.8256 | 0.8608 | 0.8428 |
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+ | GENERAL__organization-government/governmentagency | 0.8344 | 0.8318 | 0.8331 |
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+ | GENERAL__organization-media/newspaper | 0.6667 | 0.4 | 0.5 |
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+ | GENERAL__organization-other | 0.7790 | 0.8105 | 0.7944 |
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+ | GENERAL__organization-religion | 0.6667 | 0.8 | 0.7273 |
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+ | GENERAL__organization-showorganization | 0.0 | 0.0 | 0.0 |
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+ | GENERAL__organization-sportsteam | 0.0 | 0.0 | 0.0 |
182
+ | GENERAL__other-astronomything | 0.0 | 0.0 | 0.0 |
183
+ | GENERAL__other-award | 0.8216 | 0.8859 | 0.8525 |
184
+ | GENERAL__other-biologything | 0.7246 | 0.8961 | 0.8013 |
185
+ | GENERAL__other-chemicalthing | 0.7687 | 0.8047 | 0.7863 |
186
+ | GENERAL__other-currency | 0.6304 | 0.6744 | 0.6517 |
187
+ | GENERAL__other-disease | 0.8594 | 0.9048 | 0.8815 |
188
+ | GENERAL__other-educationaldegree | 0.7119 | 0.75 | 0.7304 |
189
+ | GENERAL__other-god | 0.8 | 0.5714 | 0.6667 |
190
+ | GENERAL__other-language | 0.6818 | 1.0 | 0.8108 |
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+ | GENERAL__other-law | 0.7978 | 0.8462 | 0.8212 |
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+ | GENERAL__other-livingthing | 0.7385 | 0.9320 | 0.8240 |
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+ | GENERAL__other-medical | 0.7778 | 0.8343 | 0.8050 |
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+ | GENERAL__person-artist/author | 0.625 | 0.3846 | 0.4762 |
195
+ | GENERAL__person-other | 0.8839 | 0.8979 | 0.8908 |
196
+ | GENERAL__person-politician | 0.7534 | 0.7432 | 0.7483 |
197
+ | GENERAL__person-scholar | 0.8640 | 0.8769 | 0.8704 |
198
+ | GENERAL__person-soldier | 0.7674 | 0.7586 | 0.7630 |
199
+ | GENERAL__product-airplane | 0.6774 | 0.6364 | 0.6562 |
200
+ | GENERAL__product-car | 0.9286 | 0.7879 | 0.8525 |
201
+ | GENERAL__product-food | 0.7798 | 0.7859 | 0.7828 |
202
+ | GENERAL__product-game | 0.75 | 0.75 | 0.75 |
203
+ | GENERAL__product-other | 0.7175 | 0.7537 | 0.7351 |
204
+ | GENERAL__product-ship | 0.0 | 0.0 | 0.0 |
205
+ | GENERAL__product-software | 0.8093 | 0.8403 | 0.8245 |
206
+ | GENERAL__product-train | 0.75 | 0.375 | 0.5 |
207
+ | GENERAL__product-weapon | 0.7794 | 0.8833 | 0.8281 |
208
+
209
+ ## Uses
210
+
211
+ ### Direct Use for Inference
212
+
213
+ ```python
214
+ from span_marker import SpanMarkerModel
215
+
216
+ # Download from the 🤗 Hub
217
+ model = SpanMarkerModel.from_pretrained("YurtsAI/named_entity_recognition_document_context")
218
+ # Run inference
219
+ entities = model.predict("monday is a chill day – beach time at barceloneta and maybe some shopping at la rambla.")
220
+ ```
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+
222
+ ### Downstream Use
223
+ You can finetune this model on your own dataset.
224
+
225
+ <details><summary>Click to expand</summary>
226
+
227
+ ```python
228
+ from span_marker import SpanMarkerModel, Trainer
229
+
230
+ # Download from the 🤗 Hub
231
+ model = SpanMarkerModel.from_pretrained("YurtsAI/named_entity_recognition_document_context")
232
+
233
+ # Specify a Dataset with "tokens" and "ner_tag" columns
234
+ dataset = load_dataset("conll2003") # For example CoNLL2003
235
+
236
+ # Initialize a Trainer using the pretrained model & dataset
237
+ trainer = Trainer(
238
+ model=model,
239
+ train_dataset=dataset["train"],
240
+ eval_dataset=dataset["validation"],
241
+ )
242
+ trainer.train()
243
+ trainer.save_model("YurtsAI/named_entity_recognition_document_context-finetuned")
244
+ ```
245
+ </details>
246
+
247
+ <!--
248
+ ### Out-of-Scope Use
249
+
250
+ *List how the model may foreseeably be misused and address what users ought not to do with the model.*
251
+ -->
252
+
253
+ <!--
254
+ ## Bias, Risks and Limitations
255
+
256
+ *What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.*
257
+ -->
258
+
259
+ <!--
260
+ ### Recommendations
261
+
262
+ *What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*
263
+ -->
264
+
265
+ ## Training Details
266
+
267
+ ### Training Set Metrics
268
+ | Training set | Min | Median | Max |
269
+ |:----------------------|:----|:--------|:----|
270
+ | Sentence length | 1 | 14.6796 | 691 |
271
+ | Entities per sentence | 0 | 0.4235 | 35 |
272
+
273
+ ### Training Hyperparameters
274
+ - learning_rate: 1e-05
275
+ - train_batch_size: 32
276
+ - eval_batch_size: 32
277
+ - seed: 42
278
+ - gradient_accumulation_steps: 2
279
+ - total_train_batch_size: 64
280
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
281
+ - lr_scheduler_type: linear
282
+ - lr_scheduler_warmup_ratio: 0.1
283
+ - num_epochs: 3
284
+
285
+ ### Training Results
286
+ | Epoch | Step | Validation Loss | Validation Precision | Validation Recall | Validation F1 | Validation Accuracy |
287
+ |:------:|:-----:|:---------------:|:--------------------:|:-----------------:|:-------------:|:-------------------:|
288
+ | 0.0299 | 500 | 0.0254 | 0.5244 | 0.0116 | 0.0228 | 0.9292 |
289
+ | 0.0597 | 1000 | 0.0144 | 0.5380 | 0.3492 | 0.4235 | 0.9444 |
290
+ | 0.0896 | 1500 | 0.0099 | 0.7134 | 0.4410 | 0.5450 | 0.9534 |
291
+ | 0.1194 | 2000 | 0.0088 | 0.6461 | 0.6571 | 0.6516 | 0.9596 |
292
+ | 0.1493 | 2500 | 0.0074 | 0.7177 | 0.6363 | 0.6745 | 0.9628 |
293
+ | 0.1791 | 3000 | 0.0075 | 0.6612 | 0.7342 | 0.6958 | 0.9637 |
294
+ | 0.2090 | 3500 | 0.0073 | 0.6686 | 0.7286 | 0.6973 | 0.9634 |
295
+ | 0.2388 | 4000 | 0.0061 | 0.7552 | 0.7044 | 0.7289 | 0.9693 |
296
+ | 0.2687 | 4500 | 0.0062 | 0.7385 | 0.7150 | 0.7266 | 0.9682 |
297
+ | 0.2986 | 5000 | 0.0070 | 0.6667 | 0.7792 | 0.7186 | 0.9654 |
298
+ | 0.3284 | 5500 | 0.0063 | 0.6984 | 0.7774 | 0.7358 | 0.9689 |
299
+ | 0.3583 | 6000 | 0.0055 | 0.7941 | 0.7023 | 0.7454 | 0.9706 |
300
+ | 0.3881 | 6500 | 0.0055 | 0.7540 | 0.7640 | 0.7589 | 0.9722 |
301
+ | 0.4180 | 7000 | 0.0053 | 0.7700 | 0.7614 | 0.7657 | 0.9732 |
302
+ | 0.4478 | 7500 | 0.0053 | 0.7791 | 0.7698 | 0.7744 | 0.9742 |
303
+ | 0.4777 | 8000 | 0.0054 | 0.7396 | 0.8062 | 0.7715 | 0.9729 |
304
+ | 0.5075 | 8500 | 0.0051 | 0.7653 | 0.7944 | 0.7796 | 0.9741 |
305
+ | 0.5374 | 9000 | 0.0050 | 0.7773 | 0.7844 | 0.7808 | 0.9747 |
306
+ | 0.5672 | 9500 | 0.0049 | 0.7954 | 0.7711 | 0.7830 | 0.9757 |
307
+ | 0.5971 | 10000 | 0.0049 | 0.7844 | 0.7876 | 0.7860 | 0.9754 |
308
+ | 0.6270 | 10500 | 0.0047 | 0.7898 | 0.7940 | 0.7919 | 0.9761 |
309
+ | 0.6568 | 11000 | 0.0047 | 0.7852 | 0.7929 | 0.7890 | 0.9761 |
310
+ | 0.6867 | 11500 | 0.0047 | 0.8001 | 0.7908 | 0.7954 | 0.9770 |
311
+ | 0.7165 | 12000 | 0.0050 | 0.7643 | 0.8145 | 0.7886 | 0.9755 |
312
+ | 0.7464 | 12500 | 0.0047 | 0.7991 | 0.7892 | 0.7941 | 0.9764 |
313
+ | 0.7762 | 13000 | 0.0046 | 0.7948 | 0.8084 | 0.8015 | 0.9774 |
314
+ | 0.8061 | 13500 | 0.0046 | 0.7841 | 0.8154 | 0.7994 | 0.9771 |
315
+ | 0.8359 | 14000 | 0.0043 | 0.8283 | 0.7776 | 0.8021 | 0.9783 |
316
+ | 0.8658 | 14500 | 0.0044 | 0.8054 | 0.7993 | 0.8023 | 0.9773 |
317
+ | 0.8957 | 15000 | 0.0047 | 0.7704 | 0.8152 | 0.7922 | 0.9758 |
318
+ | 0.9255 | 15500 | 0.0043 | 0.8018 | 0.8149 | 0.8083 | 0.9782 |
319
+ | 0.9554 | 16000 | 0.0043 | 0.8255 | 0.7938 | 0.8093 | 0.9789 |
320
+ | 0.9852 | 16500 | 0.0042 | 0.8201 | 0.8008 | 0.8104 | 0.9787 |
321
+ | 1.0151 | 17000 | 0.0044 | 0.7947 | 0.8175 | 0.8059 | 0.9784 |
322
+ | 1.0449 | 17500 | 0.0044 | 0.7942 | 0.8195 | 0.8066 | 0.9777 |
323
+ | 1.0748 | 18000 | 0.0043 | 0.8124 | 0.8110 | 0.8117 | 0.9789 |
324
+ | 1.1046 | 18500 | 0.0043 | 0.7987 | 0.8157 | 0.8071 | 0.9788 |
325
+ | 1.1345 | 19000 | 0.0043 | 0.8037 | 0.8171 | 0.8103 | 0.9789 |
326
+ | 1.1644 | 19500 | 0.0042 | 0.8178 | 0.8076 | 0.8127 | 0.9796 |
327
+ | 1.1942 | 20000 | 0.0044 | 0.7803 | 0.8389 | 0.8085 | 0.9780 |
328
+ | 1.2241 | 20500 | 0.0043 | 0.8040 | 0.8210 | 0.8124 | 0.9790 |
329
+ | 1.2539 | 21000 | 0.0043 | 0.8038 | 0.8245 | 0.8141 | 0.9788 |
330
+ | 1.2838 | 21500 | 0.0041 | 0.8318 | 0.7973 | 0.8142 | 0.9794 |
331
+ | 1.3136 | 22000 | 0.0041 | 0.8106 | 0.8211 | 0.8158 | 0.9796 |
332
+ | 1.3435 | 22500 | 0.0041 | 0.8288 | 0.8046 | 0.8165 | 0.9796 |
333
+ | 1.3733 | 23000 | 0.0041 | 0.8218 | 0.8170 | 0.8194 | 0.9799 |
334
+ | 1.4032 | 23500 | 0.0042 | 0.8164 | 0.8171 | 0.8168 | 0.9799 |
335
+ | 1.4330 | 24000 | 0.0041 | 0.8105 | 0.8248 | 0.8176 | 0.9793 |
336
+ | 1.4629 | 24500 | 0.0042 | 0.8073 | 0.8196 | 0.8134 | 0.9791 |
337
+ | 1.4928 | 25000 | 0.0040 | 0.8211 | 0.8162 | 0.8187 | 0.9797 |
338
+ | 1.5226 | 25500 | 0.0040 | 0.8195 | 0.8225 | 0.8210 | 0.9800 |
339
+ | 1.5525 | 26000 | 0.0040 | 0.8372 | 0.8018 | 0.8191 | 0.9799 |
340
+ | 1.5823 | 26500 | 0.0040 | 0.8263 | 0.8161 | 0.8212 | 0.9802 |
341
+ | 1.6122 | 27000 | 0.0039 | 0.8275 | 0.8141 | 0.8208 | 0.9802 |
342
+ | 1.6420 | 27500 | 0.0040 | 0.8264 | 0.8198 | 0.8231 | 0.9804 |
343
+ | 1.6719 | 28000 | 0.0040 | 0.8218 | 0.8195 | 0.8206 | 0.9799 |
344
+ | 1.7017 | 28500 | 0.0039 | 0.8286 | 0.8195 | 0.8240 | 0.9803 |
345
+ | 1.7316 | 29000 | 0.0041 | 0.8004 | 0.8357 | 0.8177 | 0.9788 |
346
+ | 1.7615 | 29500 | 0.0040 | 0.8138 | 0.8304 | 0.8220 | 0.9801 |
347
+ | 1.7913 | 30000 | 0.0040 | 0.8160 | 0.8309 | 0.8234 | 0.9804 |
348
+ | 1.8212 | 30500 | 0.0039 | 0.8204 | 0.8262 | 0.8233 | 0.9802 |
349
+ | 1.8510 | 31000 | 0.0038 | 0.8292 | 0.8228 | 0.8260 | 0.9810 |
350
+ | 1.8809 | 31500 | 0.0039 | 0.8247 | 0.8246 | 0.8246 | 0.9806 |
351
+ | 1.9107 | 32000 | 0.0038 | 0.8267 | 0.8258 | 0.8262 | 0.9810 |
352
+ | 1.9406 | 32500 | 0.0039 | 0.8102 | 0.8398 | 0.8248 | 0.9805 |
353
+ | 1.9704 | 33000 | 0.0039 | 0.8321 | 0.8185 | 0.8253 | 0.9809 |
354
+ | 2.0003 | 33500 | 0.0038 | 0.8325 | 0.8261 | 0.8293 | 0.9814 |
355
+ | 2.0302 | 34000 | 0.0038 | 0.8352 | 0.8228 | 0.8289 | 0.9813 |
356
+ | 2.0600 | 34500 | 0.0041 | 0.8144 | 0.8369 | 0.8255 | 0.9809 |
357
+ | 2.0899 | 35000 | 0.0039 | 0.8274 | 0.8281 | 0.8277 | 0.9813 |
358
+ | 2.1197 | 35500 | 0.0039 | 0.8198 | 0.8353 | 0.8275 | 0.9812 |
359
+ | 2.1496 | 36000 | 0.0039 | 0.8211 | 0.8358 | 0.8284 | 0.9811 |
360
+ | 2.1794 | 36500 | 0.0039 | 0.8242 | 0.8300 | 0.8271 | 0.9809 |
361
+ | 2.2093 | 37000 | 0.0039 | 0.8194 | 0.8317 | 0.8255 | 0.9808 |
362
+ | 2.2391 | 37500 | 0.0039 | 0.8258 | 0.8344 | 0.8301 | 0.9814 |
363
+ | 2.2690 | 38000 | 0.0039 | 0.8292 | 0.8302 | 0.8297 | 0.9816 |
364
+ | 2.2989 | 38500 | 0.0039 | 0.8281 | 0.8315 | 0.8298 | 0.9813 |
365
+ | 2.3287 | 39000 | 0.0039 | 0.8174 | 0.8386 | 0.8279 | 0.9808 |
366
+ | 2.3586 | 39500 | 0.0039 | 0.8208 | 0.8364 | 0.8285 | 0.9810 |
367
+ | 2.3884 | 40000 | 0.0039 | 0.8230 | 0.8379 | 0.8304 | 0.9815 |
368
+ | 2.4183 | 40500 | 0.0038 | 0.8355 | 0.8273 | 0.8314 | 0.9816 |
369
+ | 2.4481 | 41000 | 0.0038 | 0.8290 | 0.8347 | 0.8319 | 0.9816 |
370
+ | 2.4780 | 41500 | 0.0038 | 0.8233 | 0.8403 | 0.8317 | 0.9815 |
371
+ | 2.5078 | 42000 | 0.0039 | 0.8186 | 0.8417 | 0.8300 | 0.9814 |
372
+ | 2.5377 | 42500 | 0.0038 | 0.8321 | 0.8343 | 0.8332 | 0.9818 |
373
+ | 2.5675 | 43000 | 0.0038 | 0.8239 | 0.8396 | 0.8317 | 0.9816 |
374
+ | 2.5974 | 43500 | 0.0038 | 0.8267 | 0.8378 | 0.8322 | 0.9816 |
375
+ | 2.6273 | 44000 | 0.0038 | 0.8325 | 0.8343 | 0.8334 | 0.9818 |
376
+ | 2.6571 | 44500 | 0.0038 | 0.8254 | 0.8399 | 0.8326 | 0.9817 |
377
+ | 2.6870 | 45000 | 0.0038 | 0.8339 | 0.8338 | 0.8339 | 0.9820 |
378
+ | 2.7168 | 45500 | 0.0038 | 0.8301 | 0.8381 | 0.8341 | 0.9819 |
379
+ | 2.7467 | 46000 | 0.0038 | 0.8309 | 0.8371 | 0.8340 | 0.9818 |
380
+ | 2.7765 | 46500 | 0.0038 | 0.8296 | 0.8377 | 0.8337 | 0.9817 |
381
+ | 2.8064 | 47000 | 0.0037 | 0.8337 | 0.8349 | 0.8343 | 0.9820 |
382
+ | 2.8362 | 47500 | 0.0037 | 0.8303 | 0.8387 | 0.8345 | 0.9820 |
383
+ | 2.8661 | 48000 | 0.0037 | 0.8289 | 0.8401 | 0.8344 | 0.9819 |
384
+ | 2.8960 | 48500 | 0.0037 | 0.8299 | 0.8400 | 0.8349 | 0.9820 |
385
+ | 2.9258 | 49000 | 0.0037 | 0.8289 | 0.8401 | 0.8344 | 0.9819 |
386
+ | 2.9557 | 49500 | 0.0037 | 0.8322 | 0.8380 | 0.8351 | 0.9821 |
387
+ | 2.9855 | 50000 | 0.0037 | 0.8312 | 0.8384 | 0.8348 | 0.9820 |
388
+
389
+ ### Framework Versions
390
+ - Python: 3.11.7
391
+ - SpanMarker: 1.5.0
392
+ - Transformers: 4.42.1
393
+ - PyTorch: 2.1.1+cu121
394
+ - Datasets: 2.14.5
395
+ - Tokenizers: 0.19.1
396
+
397
+ ## Citation
398
+
399
+ ### BibTeX
400
+ ```
401
+ @software{Aarsen_SpanMarker,
402
+ author = {Aarsen, Tom},
403
+ license = {Apache-2.0},
404
+ title = {{SpanMarker for Named Entity Recognition}},
405
+ url = {https://github.com/tomaarsen/SpanMarkerNER}
406
+ }
407
+ ```
408
+
409
+ <!--
410
+ ## Glossary
411
+
412
+ *Clearly define terms in order to be accessible across audiences.*
413
+ -->
414
+
415
+ <!--
416
+ ## Model Card Authors
417
+
418
+ *Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.*
419
+ -->
420
+
421
+ <!--
422
+ ## Model Card Contact
423
+
424
+ *Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.*
425
+ -->
added_tokens.json ADDED
@@ -0,0 +1,4 @@
 
 
 
 
 
1
+ {
2
+ "<end>": 50266,
3
+ "<start>": 50265
4
+ }
config.json ADDED
@@ -0,0 +1,601 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "architectures": [
3
+ "SpanMarkerModel"
4
+ ],
5
+ "encoder": {
6
+ "_name_or_path": "roberta-large",
7
+ "add_cross_attention": false,
8
+ "architectures": [
9
+ "RobertaForMaskedLM"
10
+ ],
11
+ "attention_probs_dropout_prob": 0.1,
12
+ "bad_words_ids": null,
13
+ "begin_suppress_tokens": null,
14
+ "bos_token_id": 0,
15
+ "chunk_size_feed_forward": 0,
16
+ "classifier_dropout": null,
17
+ "cross_attention_hidden_size": null,
18
+ "decoder_start_token_id": null,
19
+ "diversity_penalty": 0.0,
20
+ "do_sample": false,
21
+ "early_stopping": false,
22
+ "encoder_no_repeat_ngram_size": 0,
23
+ "eos_token_id": 2,
24
+ "exponential_decay_length_penalty": null,
25
+ "finetuning_task": null,
26
+ "forced_bos_token_id": null,
27
+ "forced_eos_token_id": null,
28
+ "hidden_act": "gelu",
29
+ "hidden_dropout_prob": 0.1,
30
+ "hidden_size": 1024,
31
+ "id2label": {
32
+ "0": "O",
33
+ "1": "B-GENERAL__organization-showorganization",
34
+ "2": "I-GENERAL__organization-showorganization",
35
+ "3": "B-GENERAL__product-airplane",
36
+ "4": "I-GENERAL__product-airplane",
37
+ "5": "B-GENERAL__art-film",
38
+ "6": "I-GENERAL__art-film",
39
+ "7": "B-GENERAL__building-theater",
40
+ "8": "I-GENERAL__building-theater",
41
+ "9": "B-GENERAL__art-other",
42
+ "10": "I-GENERAL__art-other",
43
+ "11": "B-GENERAL__other-disease",
44
+ "12": "I-GENERAL__other-disease",
45
+ "13": "B-GENERAL__person-artist/author",
46
+ "14": "I-GENERAL__person-artist/author",
47
+ "15": "B-GENERAL__other-biologything",
48
+ "16": "I-GENERAL__other-biologything",
49
+ "17": "B-GENERAL__organization-media/newspaper",
50
+ "18": "I-GENERAL__organization-media/newspaper",
51
+ "19": "B-GENERAL__product-food",
52
+ "20": "I-GENERAL__product-food",
53
+ "21": "B-GENERAL__building-hotel",
54
+ "22": "I-GENERAL__building-hotel",
55
+ "23": "B-GENERAL__other-chemicalthing",
56
+ "24": "I-GENERAL__other-chemicalthing",
57
+ "25": "B-GENERAL__organization-other",
58
+ "26": "I-GENERAL__organization-other",
59
+ "27": "B-GENERAL__organization-religion",
60
+ "28": "I-GENERAL__organization-religion",
61
+ "29": "B-GENERAL__building-sportsfacility",
62
+ "30": "I-GENERAL__building-sportsfacility",
63
+ "31": "B-GENERAL__person-other",
64
+ "32": "I-GENERAL__person-other",
65
+ "33": "B-GENERAL__building-hospital",
66
+ "34": "I-GENERAL__building-hospital",
67
+ "35": "B-GENERAL__product-weapon",
68
+ "36": "I-GENERAL__product-weapon",
69
+ "37": "B-GENERAL__person-politician",
70
+ "38": "I-GENERAL__person-politician",
71
+ "39": "B-GENERAL__product-software",
72
+ "40": "I-GENERAL__product-software",
73
+ "41": "B-GENERAL__person-scholar",
74
+ "42": "I-GENERAL__person-scholar",
75
+ "43": "B-DATETIME__relative",
76
+ "44": "I-DATETIME__relative",
77
+ "45": "B-GENERAL__other-law",
78
+ "46": "I-GENERAL__other-law",
79
+ "47": "B-GENERAL__event-other",
80
+ "48": "I-GENERAL__event-other",
81
+ "49": "B-GENERAL__location-bodiesofwater",
82
+ "50": "I-GENERAL__location-bodiesofwater",
83
+ "51": "B-GENERAL__organization-government/governmentagency",
84
+ "52": "I-GENERAL__organization-government/governmentagency",
85
+ "53": "B-DATETIME__range",
86
+ "54": "I-DATETIME__range",
87
+ "55": "B-GENERAL__product-ship",
88
+ "56": "I-GENERAL__product-ship",
89
+ "57": "B-GENERAL__other-livingthing",
90
+ "58": "I-GENERAL__other-livingthing",
91
+ "59": "B-GENERAL__product-car",
92
+ "60": "I-GENERAL__product-car",
93
+ "61": "B-GENERAL__product-game",
94
+ "62": "I-GENERAL__product-game",
95
+ "63": "B-DATETIME__authored",
96
+ "64": "I-DATETIME__authored",
97
+ "65": "B-GENERAL__building-other",
98
+ "66": "I-GENERAL__building-other",
99
+ "67": "B-GENERAL__other-language",
100
+ "68": "I-GENERAL__other-language",
101
+ "69": "B-GENERAL__other-astronomything",
102
+ "70": "I-GENERAL__other-astronomything",
103
+ "71": "B-GENERAL__building-library",
104
+ "72": "I-GENERAL__building-library",
105
+ "73": "B-GENERAL__product-train",
106
+ "74": "I-GENERAL__product-train",
107
+ "75": "B-GENERAL__location-other",
108
+ "76": "I-GENERAL__location-other",
109
+ "77": "B-GENERAL__building-airport",
110
+ "78": "I-GENERAL__building-airport",
111
+ "79": "B-GENERAL__other-god",
112
+ "80": "I-GENERAL__other-god",
113
+ "81": "B-GENERAL__art-painting",
114
+ "82": "I-GENERAL__art-painting",
115
+ "83": "B-GENERAL__other-educationaldegree",
116
+ "84": "I-GENERAL__other-educationaldegree",
117
+ "85": "B-GENERAL__art-music",
118
+ "86": "I-GENERAL__art-music",
119
+ "87": "B-GENERAL__art-writtenart",
120
+ "88": "I-GENERAL__art-writtenart",
121
+ "89": "B-GENERAL__building-restaurant",
122
+ "90": "I-GENERAL__building-restaurant",
123
+ "91": "B-GENERAL__art-broadcastprogram",
124
+ "92": "I-GENERAL__art-broadcastprogram",
125
+ "93": "B-GENERAL__location-island",
126
+ "94": "I-GENERAL__location-island",
127
+ "95": "B-DATETIME__absolute",
128
+ "96": "I-DATETIME__absolute",
129
+ "97": "B-GENERAL__organization-sportsteam",
130
+ "98": "I-GENERAL__organization-sportsteam",
131
+ "99": "B-GENERAL__event-attack/battle/war/militaryconflict",
132
+ "100": "I-GENERAL__event-attack/battle/war/militaryconflict",
133
+ "101": "B-GENERAL__product-other",
134
+ "102": "I-GENERAL__product-other",
135
+ "103": "B-GENERAL__other-award",
136
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