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README.md
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base_model: microsoft/xtremedistil-l6-h256-uncased
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tags:
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- generated_from_trainer
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datasets:
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- nbroad/company_names
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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: xtremedistil-l6-h256-company-names
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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: nbroad/company_names
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type: nbroad/company_names
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metrics:
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- name: Precision
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type: precision
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value: 0.6998602375960866
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- name: Recall
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type: recall
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value: 0.7154210197339048
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- name: F1
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type: f1
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value: 0.7075550845586612
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- name: Accuracy
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type: accuracy
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value: 0.9702296390871982
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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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@@ -39,7 +18,7 @@ should probably proofread and complete it, then remove this comment. -->
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# xtremedistil-l6-h256-company-names
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This model is a fine-tuned version of [microsoft/xtremedistil-l6-h256-uncased](https://huggingface.co/microsoft/xtremedistil-l6-h256-uncased) on
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It achieves the following results on the evaluation set:
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- Loss: 0.0789
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- Precision: 0.6999
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base_model: microsoft/xtremedistil-l6-h256-uncased
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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
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- accuracy
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model-index:
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- name: xtremedistil-l6-h256-company-names
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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
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# xtremedistil-l6-h256-company-names
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This model is a fine-tuned version of [microsoft/xtremedistil-l6-h256-uncased](https://huggingface.co/microsoft/xtremedistil-l6-h256-uncased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0789
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- Precision: 0.6999
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