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update model card README.md

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@@ -21,10 +21,10 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.7266401590457257
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  - name: F1
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  type: f1
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- value: 0.7258317874418239
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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
@@ -34,9 +34,9 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [asafaya/bert-base-arabic](https://huggingface.co/asafaya/bert-base-arabic) on the emotone_ar dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.9079
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- - Accuracy: 0.7266
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- - F1: 0.7258
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  ## Model description
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@@ -67,12 +67,12 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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- | 1.2471 | 1.0 | 142 | 0.8635 | 0.7078 | 0.6951 |
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- | 0.7906 | 2.0 | 284 | 0.8124 | 0.7266 | 0.7202 |
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- | 0.5983 | 3.0 | 426 | 0.8331 | 0.7336 | 0.7262 |
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- | 0.4615 | 4.0 | 568 | 0.8542 | 0.7266 | 0.7240 |
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- | 0.3573 | 5.0 | 710 | 0.8924 | 0.7286 | 0.7274 |
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- | 0.2969 | 6.0 | 852 | 0.9079 | 0.7266 | 0.7258 |
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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: 0.7415506958250497
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  - name: F1
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  type: f1
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+ value: 0.7406006078114171
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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 [asafaya/bert-base-arabic](https://huggingface.co/asafaya/bert-base-arabic) on the emotone_ar dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.8965
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+ - Accuracy: 0.7416
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+ - F1: 0.7406
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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+ | 1.3476 | 1.0 | 142 | 0.8911 | 0.7008 | 0.6812 |
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+ | 0.8204 | 2.0 | 284 | 0.8175 | 0.7276 | 0.7212 |
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+ | 0.6227 | 3.0 | 426 | 0.8392 | 0.7376 | 0.7302 |
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+ | 0.4816 | 4.0 | 568 | 0.8531 | 0.7435 | 0.7404 |
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+ | 0.378 | 5.0 | 710 | 0.8817 | 0.7396 | 0.7388 |
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+ | 0.3134 | 6.0 | 852 | 0.8965 | 0.7416 | 0.7406 |
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  ### Framework versions