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@@ -3,6 +3,8 @@ license: mit
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  base_model: FacebookAI/xlm-roberta-large
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  tags:
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  - generated_from_trainer
 
 
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  metrics:
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  - precision
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  - recall
@@ -10,9 +12,29 @@ metrics:
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  - accuracy
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  model-index:
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  - name: fine_tuned_XLMROBERTA_cs_wikann
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- results: []
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- datasets:
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- - wikiann
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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
@@ -20,7 +42,7 @@ should probably proofread and complete it, then remove this comment. -->
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  # fine_tuned_XLMROBERTA_cs_wikann
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- This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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  - Loss: 0.1543
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  - Precision: 0.9203
 
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  base_model: FacebookAI/xlm-roberta-large
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  tags:
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  - generated_from_trainer
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+ datasets:
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+ - wikiann
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  metrics:
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  - precision
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  - recall
 
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  - accuracy
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  model-index:
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  - name: fine_tuned_XLMROBERTA_cs_wikann
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+ results:
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+ - task:
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+ name: Token Classification
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+ type: token-classification
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+ dataset:
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+ name: wikiann
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+ type: wikiann
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+ config: default
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+ split: validation
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+ args: default
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+ metrics:
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+ - name: Precision
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+ type: precision
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+ value: 0.920336
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+ - name: Recall
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+ type: recall
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+ value: 0.934218
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+ - name: F1
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+ type: f1
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+ value: 0.927225
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.973202
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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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  # fine_tuned_XLMROBERTA_cs_wikann
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+ This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on a czech wikiann dataset.
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  It achieves the following results on the evaluation set:
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  - Loss: 0.1543
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  - Precision: 0.9203