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@@ -139,102 +139,6 @@ The model was fine-tuned as a regular BERT-based model for NER task using Huggin
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  )
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  >>> classifier(text)
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- model.safetensors: 0%| | 0.00/496M [00:00<?, ?B/s]CommitInfo(commit_url='https://huggingface.co/guishe/nuner-v1_fewnerd_fine_super/commit/4313d72902c1e518c0f84c7884b8327c59b671d6', commit_message='Upload RobertaForTokenClassification', commit_description='', oid='4313d72902c1e518c0f84c7884b8327c59b671d6', pr_url=None, pr_revision=None, pr_num=None)
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- Token is valid (permission: write).
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- Cannot authenticate through git-credential as no helper is defined on your machine.
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- You might have to re-authenticate when pushing to the Hugging Face Hub.
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- Run the following command in your terminal in case you want to set the 'store' credential helper as default.
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- git config --global credential.helper store
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- Read https://git-scm.com/book/en/v2/Git-Tools-Credential-Storage for more details.
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- Token has not been saved to git credential helper.
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- Your token has been saved to /root/.cache/huggingface/token
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- Login successful
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- CommitInfo(commit_url='https://huggingface.co/guishe/nuner-v2_fewnerd_fine_super/commit/904729b29bb8cbaf4aa1e1a7e8ec00ada35a6e48', commit_message='Upload training_args.bin with huggingface_hub', commit_description='', oid='904729b29bb8cbaf4aa1e1a7e8ec00ada35a6e48', pr_url=None, pr_revision=None, pr_num=None)
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- DatasetDict({
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- train: Dataset({
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- features: ['id', 'tokens', 'ner_tags', 'fine_ner_tags'],
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- num_rows: 131767
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- })
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- validation: Dataset({
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- features: ['id', 'tokens', 'ner_tags', 'fine_ner_tags'],
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- num_rows: 18824
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- })
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- test: Dataset({
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- features: ['id', 'tokens', 'ner_tags', 'fine_ner_tags'],
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- num_rows: 37648
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- })
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- })
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- {'id': '0',
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- 'tokens': ['Paul', 'International', 'airport', '.'],
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- 'ner_tags': [0, 0, 0, 0]}
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- ['O',
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- 'art-broadcastprogram',
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- 'art-film',
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- 'art-music',
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- 'art-other',
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- 'art-painting',
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- 'art-writtenart',
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- 'building-airport',
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- 'building-hospital',
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- 'building-hotel',
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- 'building-library',
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- 'building-other',
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- 'building-restaurant',
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- 'building-sportsfacility',
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- 'building-theater',
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- 'event-attack/battle/war/militaryconflict',
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- 'event-disaster',
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- 'event-election',
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- 'event-other',
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- 'event-protest',
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- 'event-sportsevent',
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- 'location-GPE',
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- 'location-bodiesofwater',
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- 'location-island',
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- 'location-mountain',
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- 'location-other',
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- 'location-park',
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- 'location-road/railway/highway/transit',
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- 'organization-company',
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- 'organization-education',
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- 'organization-government/governmentagency',
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- 'organization-media/newspaper',
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- 'organization-other',
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- 'organization-politicalparty',
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- 'organization-religion',
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- 'organization-showorganization',
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- 'organization-sportsleague',
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- 'organization-sportsteam',
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- 'other-astronomything',
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- 'other-award',
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- 'other-biologything',
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- 'other-chemicalthing',
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- 'other-currency',
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- 'other-disease',
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- 'other-educationaldegree',
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- 'other-god',
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- 'other-language',
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- 'other-law',
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- 'other-livingthing',
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- 'other-medical',
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- 'person-actor',
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- 'person-artist/author',
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- 'person-athlete',
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- 'person-director',
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- 'person-other',
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- ...
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- 'product-other',
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- 'product-ship',
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- 'product-software',
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- 'product-train',
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- 'product-weapon']
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- Output is truncated. View as a scrollable element or open in a text editor. Adjust cell output settings...
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- Could not render content for 'application/vnd.jupyter.widget-view+json'
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- {"model_id":"736c5e1a1648445290af4bfe84dd9a2d","version_major":2,"version_minor":0}
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- ['<s>', 'ĠPaul', 'ĠInternational', 'Ġairport', 'Ġ.', '</s>']
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- ['O', 'O', 'O', 'O']
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- Some weights of RobertaForTokenClassification were not initialized from the model checkpoint at numind/NuNER-v1.0 and are newly initialized: ['classifier.bias', 'classifier.weight']
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- You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.
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  [{'entity_group': 'location_GPE',
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  'score': 0.96503985,
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  'word': ' Washington',
 
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  )
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  >>> classifier(text)
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  [{'entity_group': 'location_GPE',
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  'score': 0.96503985,
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  'word': ' Washington',