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update model card README.md

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  1. README.md +7 -7
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@@ -20,10 +20,10 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.9066666666666666
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  - name: F1
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  type: f1
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- value: 0.9078947368421053
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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
@@ -33,9 +33,9 @@ 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 amazon_polarity dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2659
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- - Accuracy: 0.9067
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- - F1: 0.9079
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  ## Model description
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@@ -54,13 +54,13 @@ More information needed
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  ### Training hyperparameters
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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: 16
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  - eval_batch_size: 16
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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: 2
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  ### Training results
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.9033333333333333
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  - name: F1
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  type: f1
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+ value: 0.9042904290429042
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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 [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the amazon_polarity dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.8485
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+ - Accuracy: 0.9033
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+ - F1: 0.9043
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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: 16
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  - eval_batch_size: 16
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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: 20
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  ### Training results
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