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update model card README.md

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  1. README.md +9 -9
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@@ -3,7 +3,7 @@ license: apache-2.0
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  tags:
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  - generated_from_trainer
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  datasets:
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- - ag_news
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  metrics:
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  - accuracy
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  model-index:
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  name: Text Classification
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  type: text-classification
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  dataset:
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- name: ag_news
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- type: ag_news
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- args: default
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.9473684210526315
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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
@@ -27,10 +27,10 @@ should probably proofread and complete it, then remove this comment. -->
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  # sentiment-model-sample
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- This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the ag_news dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.4887
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- - Accuracy: 0.9474
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  ## Model description
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@@ -63,7 +63,7 @@ The following hyperparameters were used during training:
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  ### Framework versions
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- - Transformers 4.16.2
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  - Pytorch 1.10.0+cu111
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  - Datasets 1.18.3
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  - Tokenizers 0.11.6
 
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  tags:
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  - generated_from_trainer
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  datasets:
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+ - imdb
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  metrics:
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  - accuracy
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  model-index:
 
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  name: Text Classification
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  type: text-classification
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  dataset:
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+ name: imdb
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+ type: imdb
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+ args: plain_text
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.93948
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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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  # sentiment-model-sample
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+ This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the imdb dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.5280
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+ - Accuracy: 0.9395
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  ## Model description
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  ### Framework versions
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+ - Transformers 4.17.0
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  - Pytorch 1.10.0+cu111
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  - Datasets 1.18.3
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  - Tokenizers 0.11.6