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@@ -37,7 +37,47 @@ datasets:
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  - ymoslem/tokenized-wmt-da-human-evaluation
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  model-index:
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  - name: Quality Estimation for Machine Translation
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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
@@ -51,18 +91,23 @@ It achieves the following results on the evaluation set:
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  ## Model description
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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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  ### Training hyperparameters
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  The following hyperparameters were used during training:
 
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  - ymoslem/tokenized-wmt-da-human-evaluation
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  model-index:
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  - name: Quality Estimation for Machine Translation
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+ results:
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+ - task:
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+ type: regression
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+ dataset:
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+ name: ymoslem/wmt-da-human-evaluation-long-context
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+ type: QE
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+ metrics:
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+ - name: Pearson
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+ type: Pearson Correlation
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+ value: 0.4465
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+ - name: MAE
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+ type: Mean Absolute Error
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+ value: 0.126
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+ - name: RMSE
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+ type: Root Mean Squared Error
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+ value: 0.1623
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+ - name: R-R2
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+ type: R-Squared
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+ value: 0.0801
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+ - task:
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+ type: regression
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+ dataset:
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+ name: ymoslem/wmt-da-human-evaluation
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+ type: QE
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+ metrics:
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+ - name: Pearson
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+ type: Pearson Correlation
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+ value:
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+ - name: MAE
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+ type: Mean Absolute Error
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+ value:
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+ - name: RMSE
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+ type: Root Mean Squared Error
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+ value:
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+ - name: R-R2
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+ type: R-Squared
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+ value:
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+ metrics:
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+ - pearsonr
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+ - mae
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+ - r_squared
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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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  ## Model description
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+ This model is for reference-free, sentence level quality estimation (QE) of machine translation (MT) systems.
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+ The long-context / document-level model can be found at: [ModernBERT-base-long-context-qe-v1](https://huggingface.co/ymoslem/ModernBERT-base-long-context-qe-v1),
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+ which is trained on a long-context / document-level QE dataset [ymoslem/wmt-da-human-evaluation-long-context](https://huggingface.co/datasets/ymoslem/wmt-da-human-evaluation-long-context)
 
 
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  ## Training and evaluation data
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+ This model is trained on the sentence-level quality estimation dataset: [ymoslem/wmt-da-human-evaluation](https://huggingface.co/datasets/ymoslem/wmt-da-human-evaluation)
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  ## Training procedure
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+ This version of the model uses the full lengthtokenizer.model_max_length=8192,
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+ but it is still trained on a sentence-level QE dataset [ymoslem/wmt-da-human-evaluation](https://huggingface.co/datasets/ymoslem/wmt-da-human-evaluation)
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+
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+ The long-context / document-level model can be found at: [ModernBERT-base-long-context-qe-v1](https://huggingface.co/ymoslem/ModernBERT-base-long-context-qe-v1),
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+ which is trained on a long-context / document-level QE dataset [ymoslem/wmt-da-human-evaluation-long-context](https://huggingface.co/datasets/ymoslem/wmt-da-human-evaluation-long-context)
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  ### Training hyperparameters
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  The following hyperparameters were used during training: