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@@ -34,7 +34,10 @@ It is designed to support the development of open language models and for lingui
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  ## Register labels and their abbreviations
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- Below is a list of the register labels predicted by the model. Note that some labels are hierarchical; when a sublabel is predicted, its parent label is also predicted. For a more detailed description, see [here](https://turkunlp.org/register-annotation-docs/).
 
 
 
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  - **MT:** Machine translated or generated
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  - **LY:** Lyrical
@@ -113,7 +116,7 @@ The model was trained using the Multilingual CORE Corpora, which will be publish
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  #### Training Hyperparameters
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  - **Batch size:** 8
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- - **Epochs:** 7
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  - **Learning rate:** 0.00005
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  - **Precision:** bfloat16 (non-mixed precision)
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  - **TF32:** Enabled
@@ -126,7 +129,19 @@ Average inference time (across 1000 iterations), using a single NVIDIA A100 GPU
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  ## Evaluation
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- Coming soon
 
 
 
 
 
 
 
 
 
 
 
 
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  ## Technical Specifications
 
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  ## Register labels and their abbreviations
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+ Below is a list of the register labels predicted by the model. Note that some labels are hierarchical; when a sublabel is predicted, its parent label is also predicted.
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+ For a more detailed description, see [here](https://turkunlp.org/register-annotation-docs/).
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+ The main labels are uppercase. To only include these main labels in the predictions, simply slice the model's output to keep only the uppercase labels.
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  - **MT:** Machine translated or generated
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  - **LY:** Lyrical
 
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  #### Training Hyperparameters
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  - **Batch size:** 8
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+ - **Epochs:** 21
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  - **Learning rate:** 0.00005
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  - **Precision:** bfloat16 (non-mixed precision)
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  - **TF32:** Enabled
 
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  ## Evaluation
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+ **Evaluation results (micro-F1 for the languages the models was trained on):**
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+ | Language | F1 (All labels) | F1 (Main labels) |
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+ | -------- | --------------- | ---------------- |
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+ | English | 0.72 |
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+ | Finnish | 0.79 |
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+ | French | 0.75 |
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+ | Swedish | 0.81 |
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+ | Turkish | 0.77 |
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+ **Zero-shot evaluation results (micro-F1):**
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  ## Technical Specifications