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@@ -120,39 +120,37 @@ If you plan to fine-tune this model on some downstream tasks, you can follow the
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  #### Task-Specific Learning Rates
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  ##### Sequence Classification:
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  | Dataset | EuroBERT-210m | EuroBERT-610m | EuroBERT-2.1B |
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  |--------------------------------------|----------------|----------------|----------------|
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  | XNLI | 3.6e-05 | 3.6e-05 | 2.8e-05 |
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  | PAWS-X | 3.6e-05 | 4.6e-05 | 3.6e-05 |
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- | QAM | 3.6e-05 | 2.8e-05 | 2.2e-05 |
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  | AmazonReviews | 3.6e-05 | 2.8e-05 | 3.6e-05 |
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  | MassiveIntent | 6.0e-05 | 4.6e-05 | 2.8e-05 |
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- | CodeDefect | 3.6e-05 | 2.8e-05 | 1.3e-05 |
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  | CodeComplexity | 3.6e-05 | 3.6e-05 | 1.0e-05 |
 
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  | MathShepherd | 7.7e-05 | 2.8e-05 | 1.7e-05 |
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  ##### Sequence Regression:
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  | Dataset | EuroBERT-210m | EuroBERT-610m | EuroBERT-2.1B |
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  |--------------------------|----------------|----------------|----------------|
 
 
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  | SeaHorse | 3.6e-05 | 3.6e-05 | 2.8e-05 |
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- | SummevalMultilingual | 3.6e-05 | 2.8e-05 | 3.6e-05 |
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- | WMT | 2.8e-05 | 2.8e-05 | 1.3e-05 |
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-
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- ##### Retrieval:
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- | Dataset | EuroBERT-210m | EuroBERT-610m | EuroBERT-2.1B |
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- |-----------------------------------------|----------------|----------------|----------------|
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- | MIRACL | 4.6e-05 | 3.6e-05 | 2.8e-05 |
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- | MLDR | 2.8e-05 | 2.2e-05 | 4.6e-05 |
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- | CC-News | 4.6e-05 | 4.6e-05 | 3.6e-05 |
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- | Wikipedia | 2.8e-05 | 3.6e-05 | 2.8e-05 |
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- | CodeSearchNet | 4.6e-05 | 2.8e-05 | 3.6e-05 |
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- | CqaDupStackMath | 4.6e-05 | 2.8e-05 | 3.6e-05 |
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- | MathFormula | 1.7e-05 | 3.6e-05 | 3.6e-05 |
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- **Disclaimer**: These are suggested hyperparameters based on our experiments. We recommend conducting your own grid search for best results on your specific downstream task.
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  ## License
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  #### Task-Specific Learning Rates
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+ ##### Retrieval:
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+ | Dataset | EuroBERT-210m | EuroBERT-610m | EuroBERT-2.1B |
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+ |-----------------------------------------|----------------|----------------|----------------|
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+ | MIRACL | 4.6e-05 | 3.6e-05 | 2.8e-05 |
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+ | MLDR | 2.8e-05 | 2.2e-05 | 4.6e-05 |
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+ | CC-News | 4.6e-05 | 4.6e-05 | 3.6e-05 |
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+ | Wikipedia | 2.8e-05 | 3.6e-05 | 2.8e-05 |
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+ | CodeSearchNet | 4.6e-05 | 2.8e-05 | 3.6e-05 |
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+ | DupStackMath | 4.6e-05 | 2.8e-05 | 3.6e-05 |
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+ | MathFormula | 1.7e-05 | 3.6e-05 | 3.6e-05 |
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+
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  ##### Sequence Classification:
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  | Dataset | EuroBERT-210m | EuroBERT-610m | EuroBERT-2.1B |
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  |--------------------------------------|----------------|----------------|----------------|
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  | XNLI | 3.6e-05 | 3.6e-05 | 2.8e-05 |
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  | PAWS-X | 3.6e-05 | 4.6e-05 | 3.6e-05 |
 
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  | AmazonReviews | 3.6e-05 | 2.8e-05 | 3.6e-05 |
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  | MassiveIntent | 6.0e-05 | 4.6e-05 | 2.8e-05 |
 
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  | CodeComplexity | 3.6e-05 | 3.6e-05 | 1.0e-05 |
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+ | CodeDefect | 3.6e-05 | 2.8e-05 | 1.3e-05 |
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  | MathShepherd | 7.7e-05 | 2.8e-05 | 1.7e-05 |
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  ##### Sequence Regression:
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  | Dataset | EuroBERT-210m | EuroBERT-610m | EuroBERT-2.1B |
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  |--------------------------|----------------|----------------|----------------|
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+ | WMT (Ref-based) | 2.8e-05 | 2.8e-05 | 1.3e-05 |
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+ | WMT (Ref-free) | 2.8e-05 | 2.8e-05 | 1.3e-05 |
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  | SeaHorse | 3.6e-05 | 3.6e-05 | 2.8e-05 |
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ## License
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