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update model card README.md

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@@ -19,11 +19,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.9526
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- - Accuracy: 0.5793
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- - F1: [0.63065766 0.46287992 0.50875894 0.55936944 0.73581605]
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- - Precision: [0.62955567 0.46589769 0.49282983 0.58949625 0.7198044 ]
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- - Recall: [0.63176353 0.45990099 0.52575217 0.53217223 0.75255624]
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  ## Model description
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@@ -44,23 +44,19 @@ More information needed
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  The following hyperparameters were used during training:
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  - learning_rate: 5e-05
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  - train_batch_size: 32
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- - eval_batch_size: 64
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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  - num_epochs: 1
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- - mixed_precision_training: Native AMP
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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- |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------------------------------------------------------:|:--------------------------------------------------------:|:--------------------------------------------------------:|
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- | 0.9618 | 1.0 | 2813 | 0.9526 | 0.5793 | [0.63065766 0.46287992 0.50875894 0.55936944 0.73581605] | [0.62955567 0.46589769 0.49282983 0.58949625 0.7198044 ] | [0.63176353 0.45990099 0.52575217 0.53217223 0.75255624] |
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  ### Framework versions
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- - Transformers 4.28.1
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- - Pytorch 1.13.1+cu117
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  - Datasets 2.12.0
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  - Tokenizers 0.13.3
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  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.9524
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+ - Accuracy: 0.579
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+ - F1: [0.62880121 0.47009599 0.50419753 0.55847134 0.73663068]
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+ - Precision: [0.63086233 0.46744983 0.4887506 0.58988159 0.72372965]
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+ - Recall: [0.62675351 0.47277228 0.52065273 0.53023706 0.75 ]
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 5e-05
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  - train_batch_size: 32
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+ - eval_batch_size: 8
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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  - num_epochs: 1
 
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  ### Training results
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  ### Framework versions
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+ - Transformers 4.30.2
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+ - Pytorch 2.0.1+cu117
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  - Datasets 2.12.0
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  - Tokenizers 0.13.3