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@@ -11,6 +11,11 @@ metrics:
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  model-index:
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  - name: distilBert_NER_finer
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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
@@ -18,7 +23,7 @@ should probably proofread and complete it, then remove this comment. -->
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  # distilBert_NER_finer
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- This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on the None dataset.
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  It achieves the following results on the evaluation set:
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  - Loss: 0.0198
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  - Precision: 0.9445
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  - F1: 0.9541
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  - Accuracy: 0.9954
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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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  ## Training and evaluation data
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- More information needed
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  ## Training procedure
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  - Transformers 4.38.2
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  - Pytorch 2.2.1+cu121
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  - Datasets 2.18.0
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- - Tokenizers 0.15.2
 
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  model-index:
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  - name: distilBert_NER_finer
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  results: []
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+ datasets:
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+ - nlpaueb/finer-139
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+ language:
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+ - en
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+ pipeline_tag: token-classification
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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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  # distilBert_NER_finer
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+ This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on the [Finer-139](https://huggingface.co/datasets/nlpaueb/finer-139) dataset.
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  It achieves the following results on the evaluation set:
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  - Loss: 0.0198
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  - Precision: 0.9445
 
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  - F1: 0.9541
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  - Accuracy: 0.9954
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  ## Training and evaluation data
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+ The training data consists of the 4 most widely available ner_tags from the Finer-139 dataset. The training and the test data were curated from this source accordingly
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  ## Training procedure
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  - Transformers 4.38.2
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  - Pytorch 2.2.1+cu121
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  - Datasets 2.18.0
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+ - Tokenizers 0.15.2