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update model card README.md

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@@ -21,7 +21,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.7137067059690494
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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
@@ -31,17 +31,17 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on the silicone dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.9634
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- - Accuracy: 0.7137
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- - Micro-precision: 0.7137
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- - Micro-recall: 0.7137
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- - Micro-f1: 0.7137
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- - Macro-precision: 0.3472
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- - Macro-recall: 0.2856
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- - Macro-f1: 0.2791
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- - Weighted-precision: 0.6730
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- - Weighted-recall: 0.7137
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- - Weighted-f1: 0.6783
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  ## Model description
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@@ -72,7 +72,7 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Micro-precision | Micro-recall | Micro-f1 | Macro-precision | Macro-recall | Macro-f1 | Weighted-precision | Weighted-recall | Weighted-f1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------------:|:------------:|:--------:|:---------------:|:------------:|:--------:|:------------------:|:---------------:|:-----------:|
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- | 0.9579 | 1.0 | 2980 | 0.9634 | 0.7137 | 0.7137 | 0.7137 | 0.7137 | 0.3472 | 0.2856 | 0.2791 | 0.6730 | 0.7137 | 0.6783 |
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  ### Framework versions
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.7111274871039057
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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 [distilroberta-base](https://huggingface.co/distilroberta-base) on the silicone dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.9647
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+ - Accuracy: 0.7111
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+ - Micro-precision: 0.7111
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+ - Micro-recall: 0.7111
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+ - Micro-f1: 0.7111
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+ - Macro-precision: 0.3228
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+ - Macro-recall: 0.2866
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+ - Macro-f1: 0.2824
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+ - Weighted-precision: 0.6683
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+ - Weighted-recall: 0.7111
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+ - Weighted-f1: 0.6768
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Micro-precision | Micro-recall | Micro-f1 | Macro-precision | Macro-recall | Macro-f1 | Weighted-precision | Weighted-recall | Weighted-f1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------------:|:------------:|:--------:|:---------------:|:------------:|:--------:|:------------------:|:---------------:|:-----------:|
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+ | 0.9578 | 1.0 | 2980 | 0.9647 | 0.7111 | 0.7111 | 0.7111 | 0.7111 | 0.3228 | 0.2866 | 0.2824 | 0.6683 | 0.7111 | 0.6768 |
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  ### Framework versions