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stulcrad
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CNEC1_1_Supertypes_xlm-roberta-large

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xlm-roberta
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  1. README.md +17 -17
  2. runs/Mar05_22-48-51_n21/events.out.tfevents.1709675332.n21.2238640.0 +2 -2
README.md CHANGED
@@ -25,16 +25,16 @@ model-index:
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  metrics:
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  - name: Precision
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  type: precision
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- value: 0.8294412010008341
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  - name: Recall
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  type: recall
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- value: 0.892328398384926
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  - name: F1
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  type: f1
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- value: 0.8597363302355738
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  - name: Accuracy
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  type: accuracy
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- value: 0.9629571802178071
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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
@@ -44,11 +44,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on the cnec dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2118
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- - Precision: 0.8294
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- - Recall: 0.8923
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- - F1: 0.8597
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- - Accuracy: 0.9630
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  ## Model description
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@@ -79,14 +79,14 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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- | 0.4103 | 1.7 | 500 | 0.1933 | 0.7270 | 0.8528 | 0.7849 | 0.9513 |
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- | 0.1838 | 3.4 | 1000 | 0.1799 | 0.7559 | 0.8573 | 0.8034 | 0.9573 |
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- | 0.1312 | 5.1 | 1500 | 0.1710 | 0.7855 | 0.8739 | 0.8274 | 0.9589 |
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- | 0.0949 | 6.8 | 2000 | 0.1782 | 0.7917 | 0.8766 | 0.8320 | 0.9605 |
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- | 0.0746 | 8.5 | 2500 | 0.1810 | 0.8027 | 0.8762 | 0.8378 | 0.9603 |
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- | 0.057 | 10.2 | 3000 | 0.2066 | 0.8277 | 0.8878 | 0.8567 | 0.9630 |
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- | 0.0474 | 11.9 | 3500 | 0.2138 | 0.8169 | 0.8905 | 0.8521 | 0.9612 |
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- | 0.0365 | 13.61 | 4000 | 0.2118 | 0.8294 | 0.8923 | 0.8597 | 0.9630 |
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  ### Framework versions
 
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  metrics:
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  - name: Precision
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  type: precision
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+ value: 0.8095043015157722
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  - name: Recall
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  type: recall
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+ value: 0.8864961866307761
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  - name: F1
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  type: f1
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+ value: 0.8462526766595291
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  - name: Accuracy
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  type: accuracy
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+ value: 0.9620984425621609
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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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  This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on the cnec dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2133
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+ - Precision: 0.8095
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+ - Recall: 0.8865
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+ - F1: 0.8463
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+ - Accuracy: 0.9621
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | 0.4081 | 1.7 | 500 | 0.1879 | 0.7183 | 0.8430 | 0.7756 | 0.9505 |
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+ | 0.1806 | 3.4 | 1000 | 0.1816 | 0.7703 | 0.8681 | 0.8163 | 0.9567 |
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+ | 0.131 | 5.1 | 1500 | 0.1695 | 0.7756 | 0.8712 | 0.8206 | 0.9592 |
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+ | 0.0975 | 6.8 | 2000 | 0.1861 | 0.7640 | 0.8744 | 0.8155 | 0.9571 |
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+ | 0.0778 | 8.5 | 2500 | 0.1908 | 0.7989 | 0.8807 | 0.8378 | 0.9591 |
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+ | 0.0596 | 10.2 | 3000 | 0.1922 | 0.7916 | 0.8829 | 0.8348 | 0.9592 |
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+ | 0.0506 | 11.9 | 3500 | 0.2070 | 0.8016 | 0.8811 | 0.8395 | 0.9598 |
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+ | 0.0407 | 13.61 | 4000 | 0.2133 | 0.8095 | 0.8865 | 0.8463 | 0.9621 |
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  ### Framework versions
runs/Mar05_22-48-51_n21/events.out.tfevents.1709675332.n21.2238640.0 CHANGED
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