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@@ -5,33 +5,24 @@ tags:
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  - generated_from_trainer
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  metrics:
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  - accuracy
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- model-index:
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- - name: xtremedistil-l6-h256-uncased-OCR-quality-classification-cls
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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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- should probably proofread and complete it, then remove this comment. -->
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- # xtremedistil-l6-h256-uncased-OCR-quality-classification-cls
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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: 0.0316
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  - Accuracy: 0.994
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  - Num Input Tokens Seen: 57341952
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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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- More information needed
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-
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- ## Training and evaluation data
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-
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- More information needed
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  ## Training procedure
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@@ -67,4 +58,4 @@ The following hyperparameters were used during training:
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  - Transformers 4.40.2
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  - Pytorch 2.2.0+cu121
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  - Datasets 2.19.1
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- - Tokenizers 0.19.1
 
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  - generated_from_trainer
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  metrics:
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  - accuracy
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+ datasets:
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+ - pszemraj/OCR-quality-classification
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+ language:
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+ - en
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  ---
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+ # xtremedistil-l6-h256-uncased: OCR-quality-classification
 
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+ This model is a fine-tuned version of [microsoft/xtremedistil-l6-h256-uncased](https://hf.co/microsoft/xtremedistil-l6-h256-uncased) on `pszemraj/OCR-quality-classification`
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  It achieves the following results on the evaluation set:
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  - Loss: 0.0316
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  - Accuracy: 0.994
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  - Num Input Tokens Seen: 57341952
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  ## Intended uses & limitations
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+ predict whether a document is clean or noisy
 
 
 
 
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  ## Training procedure
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  - Transformers 4.40.2
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  - Pytorch 2.2.0+cu121
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  - Datasets 2.19.1
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+ - Tokenizers 0.19.1