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  tags:
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  - generated_from_trainer
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  datasets:
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- - few-nerd
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  model-index:
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  - name: span-marker-robert-base
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  results: []
 
 
 
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -13,7 +16,7 @@ should probably proofread and complete it, then remove this comment. -->
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  # span-marker-robert-base
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- This model is a fine-tuned version of [](https://huggingface.co/) on the few-nerd dataset.
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  It achieves the following results on the evaluation set:
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  - Loss: 0.0214
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  - Overall Precision: 0.7642
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  - Overall F1: 0.7791
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  - Overall Accuracy: 0.9397
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- ## Model description
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-
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- More information needed
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-
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- ## Intended uses & limitations
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-
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- More information needed
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-
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  ## Training and evaluation data
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- More information needed
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-
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- ## Training procedure
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-
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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  - Transformers 4.30.2
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  - Pytorch 2.0.1+cu118
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  - Datasets 2.13.1
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- - Tokenizers 0.13.3
 
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  tags:
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  - generated_from_trainer
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  datasets:
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+ - DFKI-SLT/few-nerd
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  model-index:
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  - name: span-marker-robert-base
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  results: []
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+ license: apache-2.0
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+ language:
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+ - en
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
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  # span-marker-robert-base
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+ This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on [few-nerd](https://huggingface.co/datasets/DFKI-SLT/few-nerd) dataset using [SpanMarker](https://github.com/tomaarsen/SpanMarkerNER) an module for NER.
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  It achieves the following results on the evaluation set:
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  - Loss: 0.0214
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  - Overall Precision: 0.7642
 
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  - Overall F1: 0.7791
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  - Overall Accuracy: 0.9397
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  ## Training and evaluation data
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
 
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  - Transformers 4.30.2
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  - Pytorch 2.0.1+cu118
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  - Datasets 2.13.1
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+ - Tokenizers 0.13.3