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update model card README.md

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  This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the generator dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.9078
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- - Overall Precision: 0.0
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- - Overall Recall: 0.0
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- - Overall F1: 0.0
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- - Overall Accuracy: 0.9116
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- - Datasetname F1: 0.0
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- - Hyperparametername F1: 0.0
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- - Hyperparametervalue F1: 0.0
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- - Methodname F1: 0.0
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- - Metricname F1: 0.0
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- - Metricvalue F1: 0.0
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- - Taskname F1: 0.0
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 0.001
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  - train_batch_size: 4
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  - eval_batch_size: 8
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  - seed: 42
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  | Training Loss | Epoch | Step | Validation Loss | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy | Datasetname F1 | Hyperparametername F1 | Hyperparametervalue F1 | Methodname F1 | Metricname F1 | Metricvalue F1 | Taskname F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:-----------------:|:--------------:|:----------:|:----------------:|:--------------:|:---------------------:|:----------------------:|:-------------:|:-------------:|:--------------:|:-----------:|
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- | No log | 1.0 | 141 | 1.8292 | 0.0 | 0.0 | 0.0 | 0.9116 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | No log | 2.0 | 282 | 1.8221 | 0.0 | 0.0 | 0.0 | 0.9116 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | No log | 3.0 | 423 | 1.8244 | 0.0 | 0.0 | 0.0 | 0.9116 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | 1.6685 | 4.0 | 564 | 1.8683 | 0.0 | 0.0 | 0.0 | 0.9116 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | 1.6685 | 5.0 | 705 | 1.9146 | 0.0 | 0.0 | 0.0 | 0.9116 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | 1.6685 | 6.0 | 846 | 1.9078 | 0.0 | 0.0 | 0.0 | 0.9116 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the generator dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.9895
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+ - Overall Precision: 0.5201
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+ - Overall Recall: 0.3319
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+ - Overall F1: 0.4052
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+ - Overall Accuracy: 0.9326
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+ - Datasetname F1: 0.4952
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+ - Hyperparametername F1: 0.48
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+ - Hyperparametervalue F1: 0.5
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+ - Methodname F1: 0.3933
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+ - Metricname F1: 0.2488
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+ - Metricvalue F1: 0.2456
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+ - Taskname F1: 0.6393
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 3e-05
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  - train_batch_size: 4
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  - eval_batch_size: 8
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  - seed: 42
 
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  | Training Loss | Epoch | Step | Validation Loss | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy | Datasetname F1 | Hyperparametername F1 | Hyperparametervalue F1 | Methodname F1 | Metricname F1 | Metricvalue F1 | Taskname F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:-----------------:|:--------------:|:----------:|:----------------:|:--------------:|:---------------------:|:----------------------:|:-------------:|:-------------:|:--------------:|:-----------:|
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+ | No log | 1.0 | 141 | 1.2556 | 0.2784 | 0.1520 | 0.1967 | 0.9212 | 0.0 | 0.3478 | 0.2581 | 0.3750 | 0.0 | 0.0 | 0.0556 |
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+ | No log | 2.0 | 282 | 0.8945 | 0.3020 | 0.5096 | 0.3793 | 0.9088 | 0.5 | 0.1538 | 0.2778 | 0.3540 | 0.4566 | 0.0896 | 0.3756 |
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+ | No log | 3.0 | 423 | 1.0233 | 0.3702 | 0.4518 | 0.4069 | 0.9268 | 0.4211 | 0.2647 | 0.3333 | 0.3529 | 0.4658 | 0.1613 | 0.5270 |
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+ | 0.6352 | 4.0 | 564 | 1.1734 | 0.4316 | 0.4390 | 0.4352 | 0.9310 | 0.4854 | 0.3462 | 0.3415 | 0.4352 | 0.4269 | 0.2295 | 0.5827 |
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+ | 0.6352 | 5.0 | 705 | 1.3147 | 0.4840 | 0.4540 | 0.4685 | 0.9390 | 0.5143 | 0.5 | 0.625 | 0.5739 | 0.3495 | 0.2333 | 0.5865 |
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+ | 0.6352 | 6.0 | 846 | 2.1441 | 0.5618 | 0.3405 | 0.4240 | 0.9373 | 0.5185 | 0.5581 | 0.6061 | 0.4898 | 0.2365 | 0.1071 | 0.6126 |
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+ | 0.6352 | 7.0 | 987 | 1.9895 | 0.5201 | 0.3319 | 0.4052 | 0.9326 | 0.4952 | 0.48 | 0.5 | 0.3933 | 0.2488 | 0.2456 | 0.6393 |
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  ### Framework versions